method and device for calibrating a mass flow sensor, and, method for providing a calibration factor

专利摘要:
METHOD AND DEVICE FOR CALIBRATING A MASS FLOW SENSOR, AND, METHOD FOR PROVIDING A CALIBRATION FACTOR FOR A MASS FLOW SENSOR A method of calibrating a mass flow sensor during grain harvesting includes sensing an accumulated mass of a grain portion inside the grain tank with a first sensor. A mass flow sensor is calibrated based at least in part on a signal from the first sensor.
公开号:BR102015015315B1
申请号:R102015015315-5
申请日:2015-06-24
公开日:2020-12-29
发明作者:James J. Phelan；Aaron J. Bruns；Robert McNaull；Jeremiah K. Johnson；Matthew J. Darr
申请人:Deere & Company；Iowa State University Research Foundation, Inc；
IPC主号:

专利说明:

FUNDAMENTALS
[001] Mass flow measurement devices are used in harvesting machines, such as a combination to measure the mass flow of grain that flows into a grain tank. A mass flow sensor can be positioned to sense grain when it is draining into a grain tank. A mass flow is derived from a signal from the mass flow sensor. SUMMARY
[002] In one embodiment, a method of calibrating a mass flow sensor during grain harvesting includes sensing an accumulated mass of a first portion of grain inside the grain tank with a first sensor. A mass flow sensor is calibrated based at least in part on a signal from the first sensor.
[003] In another embodiment, a method of calibrating a mass flow sensor during grain harvesting into a grain tank includes sensing the volume of at least a first portion of the grain within the grain tank with a first sensor; and calibrating the mass flow sensor based at least in part on the grain volume in the grain tank while the grain is being deposited inside the grain tank.
[004] In another embodiment, an apparatus for calibrating a mass flow sensor during grain harvesting includes a non-transient, computer-readable medium containing computer-readable code, which directs one or more processing units to calculate the change in mass of grain within the grain tank over a period of time based at least in part on a signal from the first sensor and a signal from the second sensor and to recalibrate the flow signal from the mass flow sensor based at least in part in the change in mass over the period of time.
[005] In yet another embodiment, an apparatus comprises a grain tank; a first sensor to provide first signals based on the sensed grain flow into the grain tank; a second sensor to emit second signals based on a sensed accumulated mass of grain inside the grain tank; and at least one processing unit for adjusting an estimated grain flow, determined from the first signals based on the second signals. BRIEF DESCRIPTION OF THE DRAWINGS
[006] The figure is a schematic diagram of an example of a grain mass flow estimation system.
[007] FIG. 1A is an isometric view of a sample harvester including the grain mass flow estimation system of figure 1.
[008] FIG. 2 is a schematic view of the mass flow calibration system of figure 3 with the grain tank having a second amount of grain.
[009] FIG. 3 is a schematic view of the mass flow calibration system of figure 3 with the grain tank having a second amount of grain.
[0010] FIG. 4 is a flow chart of an example method for calibrating a mass flow sensor.
[0011] FIG. 5 is a flow chart of the Method for calibrating a mass flow sensor of FIG. 4 including sensing an accumulated mass of a second portion of grain.
[0012] FIG. 6 is a flow chart of another example method for calibrating a mass flow sensor.
[0013] FIG. 7 is a flow chart of another example method for calibrating a mass flow sensor.
[0014] FIG. 8 is a flow chart of another example method for calibrating a mass flow sensor.
[0015] FIG. 9 is a flow chart of another example method for calibrating a mass flow sensor.
[0016] FIG. 10 is an example graph illustrating the relationship between load cell signals and grain weight in a tank. DETAILED DESCRIPTION
[0017] Figure 1 illustrates an example of a grain mass flow estimation system 10. As will be described hereinafter, system 10 dynamically adjusts or calibrates the grain flow measurement into a grain receptacle, such as like a grain tank. As a result, system 10 facilitates more accurate grain flow measurements to facilitate more accurate grain harvest data.
[0018] In the illustrated example, the mass grain flow estimation system 10 comprises grain tank 11, the grain mass flow sensor 12, sometimes referred to as a production monitor, the grain accumulation sensor 13 , the flow estimator 14 and outlet 15. The grain tank 11 comprises a grain receptacle or hopper for receiving grain. In one implementation, the grain tank 11 comprises a grain receptacle for receiving grain when it is, or is being harvested. In one implementation, the grain tank 11 is incorporated as part of a machine or harvester that harvests the grain, such as a combination or similar. In yet another implementation, the grain tank 11 is transported along the side of the harvester, in which grain is transported or moved from the harvester to the grain tank when the harvester crosses a field. Although illustrated as having a rectangular cross section, the 11 grain tank can have any of a variety of different sizes, shapes and configurations.
[0019] The grain mass flow sensor 12 comprises one or more sensors that provide signals based on actual grain flow within the grain tank 11. In one implementation, the grain mass flow sensor 12 comprises one or more impact sensors that are impacted by grain when the grain is flowing into the grain tank 11. In other implementations, the grain flow sensor 12 may comprise other types of flow sensing devices, including, but not limited to, non-contact sensors. Examples of non-contact sensors include, but are not limited to, a radiation or photoelectric sensing device, in which a light or radiation source is provided and directed through the grain flow when the grain is being deposited in the grain tank 11 from the combine 12. A receiver senses the amount of light or radiation received through the grain flow providing a mass flow rate of the grain.
[0020] The grain accumulation sensor 13 comprises one or more sensors that emit signals based on a sensed accumulation of grain inside the grain tank 11. In one implementation, the signals emitted by sensor 13 are based on a format, size or configuration of a grain mass accumulated within the grain tank 11. In one implementation, the signals emitted by sensor 13 are alternatively or additionally based on a sensed weight of the grain being accumulated within the grain tank 11. In one implementation, the grain accumulation sensor 13 comprises one or more sensing elements that sesame different portions of the pile or pile of grains within the grain tank 11. In an implementation, sensor 13 emits signals continuously or periodically as the grain is being accumulated inside the grain tank 11.
[0021] The flow estimator 14 comprises an electronic component that estimates the grain flow or grain flow into the grain tank 11 based at least in part on signals from the grain mass flow sensor 12. The flow estimator 14 comprises processor 16 and memory 18. Processor 16 comprises one or more processing units that calculate or estimate grain flow based at least in part on signals from the grain mass flow sensor 12 and according to instructions from memory 18. Memory 18 comprises a non-transient computer-readable medium or programmed logic that directs processor 16 in determining or estimating grain flow and calibrating or adjusting the flow sensed by the sensor .
[0022] According to an implementation, the term "processing unit" means a really developed processing unit or processing unit to be developed in the future, which executes instruction sequences contained in a memory, such as memory 18. The execution of instruction sequences causes the processing unit to perform steps, such as generating control signals. Instructions can be loaded into random access memory (RAM) by execution by the processing unit from read-only memory (ROM), a mass storage device, or some other persistent storage. In other embodiments, wired circuits may be used in place of, or in combination with, software instructions to implement the described functions. For example, the flow estimator 14 can be incorporated as part of one or more application specific integrated circuits (ASICs). Unless specifically noted to the contrary, the controller is not limited to any specific combination of hardware and software circuitry, nor to any particular source for instructions executed by the processing unit.
[0023] Flow estimator 14 dynamically adjusts or calibrates the grain flow measurement into the grain tank 11. As will be described hereinafter, in one implementation, flow estimator 14 uses signals from sensor 13 to determine a calibration flow, a first estimate of a rate at which grain is flowing into the grain tank 11. Flow estimator 14 uses signals from sensor 12 to estimate a sensed flow, a second rate at which grain is flowing to inside the grain tank 11. The flow estimator 14 compares the sensed flow and the calibration flow and calibrates the grain flow measurement based on this comparison. As a result, the flow estimator 14 facilitates more accurate grain flow measurements to facilitate more accurate grain harvest data. In one implementation, processor 16 of flow estimator 14 determines an initial estimate of grain flow into the grain tank 11 based on signals from the grain mass flow sensor 12. Processor 16, following instructions contained in in memory 18, it then adjusts or calibrates the initial grain flow estimate into the grain tank 11 based at least in part on signals received from the grain accumulation sensor 13.
[0024] In another implementation, the flow estimator 14 calibrates the actual operation of the grain mass flow sensor 12 based on signals received from the grain accumulation sensor 13. For example, processor 16 can emit control signals , which cause a sensitivity, scale or other parameter of sensor 12 to be adjusted or calibrated so that sensor 12 emits adjusted signals. Processor 16 estimates grain flow based on the adjusted signals emitted from sensor 12.
[0025] Output 15 comprises a device, by means of which the estimated grain flow is used or displayed. In an implementation, output 15 comprises a display or monitor, whereby the estimated grain flow is presented for viewing by a combine operator, an off-site manager or someone else. In one implementation, output 15 comprises a memory, such as memory 18, and / or another memory, which stores the estimated grain flow for subsequent use or analysis. For example, in an implementation, output 15 stores estimated grain flow values, which correspond to different times or different geo-referenced locations in a field or other region being harvested. In one implementation, output 15 stores estimated grain flow values, which correspond to different operational settings for the combine. In an implementation, the estimated grain flow values are transmitted to one or more off-site locations for display and / or analysis.
[0026] Figure 1A illustrates a grain flow estimation system for grain 10, provided as part of a combine 20 (shown as a combination). As shown in figure 1A, grain tank 11 is transported as part of harvester 20. When harvester 20 crosses a field containing crops 21 being harvested, the harvested grain flows into the grain tank 11. In one implementation, the system grain mass flow estimation 10 continuously or periodically adjusts or calibrates the grain flow measurement into the grain tank 11 when the combine 20 crosses a field based on signals from the grain accumulation sensor 13. The flow of grain measured into the grain tank 11 is provided at outlet 15.
[0027] As noted above, in other implementations, the grain flow estimation system for grain 10 is alternatively associated with a grain tank 11 carried along the side of the harvester 20 when harvester 20 crosses a field and when the grain is being deposited into the grain tank 11 via chute 22. For example, the grain tank 11 may be in a separate vehicle or trailer that moves adjacent to the harvester 20. Although flow estimator 14 and outlet 15 are illustrated as being incorporated as part of harvester 20, in other implementations, the flow estimator 14 and / or outlet 15 are alternatively remotely located with respect to harvester 20, in which signals from sensors 12 and 13 are communicated to the flow estimator 14, located remotely.
[0028] Figure 2 illustrates the grain flow estimation system 110, an example implementation of the grain flow estimation system 10. System 110 is similar to system 10, except that system 110 is specifically illustrated as comprising the grain mass flow sensor 112 and grain accumulation sensor 113 instead of the grain mass flow sensor 12 and accumulation sensor 13, respectively. Those remaining components or elements of system 110, which correspond to the components of system 10 are listed similarly.
[0029] In the illustrated example, system 110 calibrates the grain mass flow sensor 112 to improve the accuracy of the mass flow generated from the grain mass flow sensor 112. The calibration of the grain mass flow sensor 112 is based on additional information obtained from the grain accumulation sensor 113. In one embodiment, the actual mass of the grain collected during a given period can be compared with the mass flow calculated by the mass flow sensor 112 during that same period . The difference between the actual mass of the collected grain and the mass flow calculated by the mass flow sensor 112 can be used to calibrate the grain mass flow sensor to provide a more accurate mass flow while the grain is being harvested. In one embodiment, the grain mass flow sensor 112 calibration is done in real time while the grain is being harvested and while the grain is filling the tank 11.
[0030] In the illustrated example, the grain mass flow sensor 112, sometimes referred to as a grain flow sensor, comprises an impact based on the mass flow device, which includes an impact surface 124, on which the grain impacts before being deposited into the grain tank 11. However, other types of grain flow sensors can also be used including, but not limited to, a non-contact sensor. An example of a non-contact sensor includes a radiation or photoelectric sensing device, in which a light or radiation source is provided and directed through the grain flow when the grain is being deposited within the grain tank 11. A receiver senses the amount of light or radiation received through the grain flow providing a mass flow of the grain.
[0031] In one embodiment, the grain mass flow sensor 112 is located near an outlet 25 of a chute 26, so that the harvested grain coming out of the chute 26 impacts the surface 124 of the mass flow sensor 112. A load cell, such as a transducer, operably connected to surface 124, provides an electronic signal as a function of the amount, rate and / or weight of grain impacting the surface 124 of the mass flow sensor 112. The flow sensor Grain mass flow 112 provides an electronic signal as a function of the grain impacting the sensor. In still other implementations, other types of mass flow sensors are employed to provide a signal as a function of the grain being harvested by the harvester 20. In one implementation, the mass flow is determined as a function of the generated electronic signal from the sensor of mass flow 112.
[0032] As shown by figures 2 and 3, when the grain is driven by endless screw 114, the grain leaves the chute 26 and falls towards the floor 142 of the grain tank 11 to form the grain pile 154. The stack 154 has a known geometric shape based in part on the geometry of the grain tank 11 and the position of the chute 26 and the impact surface 124 of the mass flow sensor 113. The shape of the stack 154 may also depend on the speed at which grain exiting trough 126. In one embodiment, stack 154 generally defines the shape of a cone with an outer wall 156 and an apex 158. With reference to Figs. 3, when the additional grain is deposited within the grain tank 11, the grain pile will grow to form a larger pile 160 having a similar geometric cone shape having a new outer wall 162 and a new apex 164. The new apex 164 being higher from the ground and / or the floor 142 than the summit 158. In other words, the distance between the new summit 164 and the floor 142 of the grain tank 11 is greater than the distance between the summit 158 and the 142th floor of the 11th grain tank.
[0033] In one implementation, the shape of at least an upper portion of the grain pile inside the grain tank takes on a similar cone shape after a certain amount of grain is deposited inside the tank. When the grain is first deposited inside the grain tank 11, the individual grains impact against the floor of the grain tank 11 and only begin to form a predetermined shape with an apex and having a conical shape with a circular and / or arched cross section after a sufficient amount of grain has been deposited inside the tank 11. In an example implementation, this amount of grain, required in the grain tank 11 to form the predetermined shape, is referred to as the minimum amount of grain. Similarly, when the grain is continuously added to the grain tank, there comes a point at which the bottom of the grain pile spreads across the width of the grain tank 11, so that the bottom or base portion of the grain pile will begin. to assume the shape of the periphery of the grain tank. In an example implementation, the amount of grain deposited within tank 11 so that the grain pile maintains its predetermined shape is referred to as the maximum amount of grain. Consequently, the grain pile will have a certain geometric shape when the amount of grain in the grain tank is between a minimum amount of grain and a maximum amount of grain.
[0034] In one embodiment, the shape of the grain pile is symmetrical, while in other modalities, the shape of the grain pile is not symmetrical. The apex of the grain pile can be centrally located over the grain pile or it can be geometrically displaced when measured from a central point at the base of the grain pile or some horizontal cross section of the grain pile. Depending on the manner in which the grain is deposited within the grain tank 11, there may be more than one region of the grain pile, which is higher than other regions. In one embodiment, the grain pile includes a first portion having a higher height from the ground than other portions of the grain pile within the grain tank. In one embodiment, the apex of the grain pile is not equidistant from at least two opposite walls of the grain tank 11.
[0035] The grain accumulation sensor 113 senses the weight of different portions of the pile or pile 154 of grain. In the illustrated example, the grain accumulation sensor 113 senses different vertical columns of grain within the stack 154 at different times to determine the rate at which the weight of such portions of the stack 154 is changing. In the illustrated example, the grain accumulation sensor 113 comprises sensors 126, 130 and 134. Sensor 126 detects or senses the actual mass of a first column portion 128 of the grain harvested and deposited in the grain tank 11. Sensor 130 senses a second portion of column 132 of grain within the grain tank 11. Sensor 134 senses a third portion of column 133 of grain within grain tank 11. Flow estimator 14 uses signals from each of sensors 126, 130 and 134 to determine a calibration factor to be applied to sensor 112.
[0036] In the illustrated example, flow estimator 14 compares changes in signals from sensors 126, 130, and 134 over time to calculate or estimate the change in mass of each portion of the grain pile within the grain tank 11. Flow estimator 14 uses the estimated change in the weight of each portion to calculate a first flow estimate or calibration flow estimate. Flow estimator 14 uses signals from sensor 112 to calculate a second flow estimate or sensed flow. By comparing the calibration flow estimate and the sensed flow estimate, the flow estimator 14 determines whether and how sensor 112 should be adjusted or calibrated. In one implementation, the flow estimator 14 continuously or periodically calibrates or adjusts the operation of sensor 112 based on comparing the estimated change in grain mass for each portion of the grain pile within the grain tank 11 based on signals from sensors 126, 130, 134 with the expected change in grain mass based on signals from sensor 112.
[0037] In one implementation, flow estimator 14 determines a calibration flow estimate based on changes in the total grain weight within the grain tank 11. Flow estimator 14 uses signals from sensors 126, 130 and 134 to estimate changes in the total grain weight within the grain tank 11 over a period of time. Flow estimator 14 compares the change in the total grain weight within the grain tank 11 based on signals from sensors 126, 130 and 134 for the second flow rate determined from signals from sensor 112. Based on in this comparison, the flow estimator 14 calibrates or adjusts sensor 112.
[0038] In the illustrated example, one of the sensors 126, 130 and 134 is positioned on the floor 142 of the grain tank 11 in a position that will be directly below the predicted apex location. The others of the first, second or third sensors are placed at a predetermined distance from below the apex. In the illustrated example, sensor 126 is positioned directly below the predicted apex location, while sensors 130 and 134 are positioned at predetermined distances when measured horizontally and perpendicularly from a vertical vector extending downward in the direction of gravity from the summit. The general shape of the grain pile can be determined based on the known shape of the grain tank 11, at the location of the trough 26 in relation to a grain tank 11 and / or at the location of the grain flow sensor, near the grain tank. , and exit from the trough. In the illustrated example, sensor 130 is located closer to the second wall 150 than to the first wall 146, while sensor 126 is located closer to the first wall 146 than to the second wall 150. Sensor 134 is positioned intermediate between sensor 126 and the sensor 130. In other implementations, sensors 126, 130 and 134 have other relative locations within the grain tank 11.
[0039] In the illustrated example, each of the sensors 126, 130 and 134 comprises load sensors having surfaces 140, 164 and 165, respectively. In one implementation, each of the sensors 126, 130 and 134 comprises a load cell or transducer that converts the force of the grain on surfaces 140, 164 and 165 into an electrical signal, from which the weight and mass of the grain above surface 140 can be determined. In the illustrated example, each of the sensors 126, 130 and / or 134 specifically comprises a mechanical or electromechanical device, such as a scale on which the weight and mass of the grain above surface 40 can be determined. In one implementation, sensors 126, 130 and / or 134 provide a pressure reading of the grain located above a portion of the sensor.
[0040] In the illustrated example, each of the sensors 126, 130, 134 is in direct contact with a portion of the grain inside the grain tank 11. In the illustrated example, each of the sensors 126, 130, 134 does not sense the total weight the grain tank 11, but instead senses the weight of the volume or portion of grain column vertically above the sensing surfaces 140, 164, 165 inside the grain tank 11. In the example circumstance, illustrated in figures 2 and 3, the column portion 128 of the stack 154 comprises the grain mass above the surface 140 of the sensor 126 and extending to the outer surface 156 of the first grain stack 154. In the example embodiment illustrated, the “up” direction is the direction opposite to the gravity direction. The force exerted by portion 128 is sensed by sensor 126. In this way, the weight of portion 128 of stack 154 is determined. Similarly, in one embodiment, portion 132 is a portion of stack 154 located directly above surface 164 of sensor 130. Column portion 132 covers surface 164 of second sensor 130 and the top or top end of the second grain portion 132 corresponds to a portion of the outer surface 162 of the grain pile 160. The force exerted by portion 132 is recorded or sensed by the second sensor 130. Likewise, sensor 134 senses the column portion of the pile 154 extending above the sensing surface 165 and ending along the upper surface 156 of the stack 154.
[0041] In the illustrated example, where the sensing surfaces 140, 164, 165 are illustrated as being circular, each of the sensors 126, 130, 134 senses the weight of a cylindrical column of grain extending above such sensing surfaces 140, 164, 165. As shown in figures 2 and 3, the bottom of the vertical column is defined by the shape, size and orientation of the sensing surface 140, 164, 165 from the top of the vertical column varies depending on the shape of the upper surface of the pile of grains inside the grain tank 11. In other implementations, instead of circular surfaces 140, 164 and 165, such sensing surfaces 140, 164, 165 have other sizes and shapes, in which sensors 126, 130, 134 sense the grain columns within the grain tank 11 having corresponding cross-sectional shapes. Although each of the sensing surfaces 140, 164, 165 is illustrated as being similarly shaped, in other implementations, the sensing surfaces 140, 164 and 165 have different shapes and / or sizes in relation to each other.
[0042] In the illustrated example, surfaces 140, 164 and 165 define coplanar planes. In one embodiment, surfaces 140, 164 and 165 define planes that are parallel to each other. In one embodiment, surfaces 140, 164 and 165 define planes that are neither coplanar nor parallel to each other. In one embodiment, surfaces 140, 164 and 165 are located at a distance above floor 142 and are all in a horizontal position. In one embodiment, one or more of the surfaces 140, 164 and 165 are positioned at a distance above the floor 142.
[0043] In the illustrated example, surfaces 140, 164 and 165 are horizontal so that the gravity direction is perpendicular to a plane defined by floor 142 when the grain tank 11 is in a neutral, not inclined orientation. In one embodiment, the horizontal term is defined by a plane perpendicular to the direction of gravity. In other implementations, surfaces 140, 164, 165 have other orientations, depending on the orientation of the corresponding underlying or overlying portions of the floor 142 of the tank 11. For example, in another implementation, the floor 142 comprises a first portion that slopes downwards. in the direction of gravity from a base 144 of the side wall 146 and a second portion that slopes downward in the direction of gravity from a base 148 of an opposite side wall 150. In such an implementation, the floor 142 forms a lower linear line, in which the first portion and the second portion meet. In one implementation, the first portion and the second portion of the floor 142 pivot away from each other or include a trap to allow the grain to be dumped down from the grain tank 11. In such an implementation, surfaces 140, 164 and 165 of sensors 126, 130, 134, respectively, extend parallel to their associated portions of the floor 142, not perpendicular or inclined with respect to the direction of gravity.
[0044] Although illustrated as load sensors, in other implementations, sensors 126, 130 and 134 comprise other types of sensors. In still other implementations, sensors 126, 130 and 134 can comprise different types of sensors. For example, sensor 126 comprises a first type of sensor, sensor 130 comprises a second type of sensor and sensor 134 comprises a third type of sensor. Although the grain accumulation sensor 113 is illustrated as comprising three spaced sensors 126, 130 and 134, in other implementations, the grain accumulation sensor 113 alternatively comprises a greater or lesser number of such sensors. For example, in other implementations, the grain accumulation sensor 113 may comprise a single load sensor, where the flow estimator 14 calibrates sensor 112 based on signals from the single sensor. Although the grain accumulation sensor 113 is illustrated as comprising sensors located along, or within, the floor of the grain tank 11, in other implementations, the grain accumulation sensor 113 comprises sensors located elsewhere along the, or inside the grain tank 11 at the same locations illustrated or at other locations.
[0045] As shown in figure 3, when the grain continues to flow into the grain tank 11, the size and shape of the pile 154 grows to form the pile 160. As a result, the height and possibly the upper surface of the portions column 128, 132 and 135 also change. Column portion 129 is added to column portion 128. Column portion 133 is added to column portion 132. Column portion 136 is added to column portion 135. Additional weights of column portions 129, 133 and 135 are sensed by sensors 126, 130 and 134, respectively. The flow estimator 14 uses such sensed weights and the shape of the stacks 154 and 164 to calculate the flow estimate, which is used to calibrate the sensor 112.
[0046] In one embodiment, the general shape of the grain pile inside the grain tank is mathematically modeled. If the geometric shape of the grain pile is a symmetrical shape, the shape can be modeled with a proposed mathematical algorithm and / or geometric modeling. Once a geometric model is created, the volume of the grain pile is determined inside the grain tank and / or a mass of the grain pile inside the grain tank is determined based only on the accumulated mass above a known weight sensor. load inside the tank or based on one or more of the accumulated masses above known load sensors.
[0047] In the illustrated example, the locations of sensors 126, 130 and 134 and any additional sensors within the grain tank 11 are known and / or determined before grain is deposited within the grain tank 11. The mathematical model of the format The general grain pile provides the total volume and total mass of the entire grain pile based on information provided by at least one of the first, second and additional sensors. Since the ratio of the volume and mass of the grain portion, located directly above a given sensor to the entire grain pile, is known, a mass of the entire grain pile volume is determined based at least in part on a mass detected by the given sensor.
[0048] Signals from multiple sensors provide improved accuracy for the total mass of the entire grain pile. Although the grain pile cannot provide a pure cone shape, a mathematical model and / or equation can provide the grain pile shape. In one embodiment, the mathematical model of the grain pile shape can be more accurate when the amount of grain in the grain tank 11 is between a predetermined minimum amount of grain and a predetermined maximum amount of grain. The minimum quantity and the maximum quantity of grain, as discussed above, may correspond to the situation in which the grain pile is sufficient to assume the characteristics of the predicted shape, but not so large that the shape is modified by the sides of the storage tank. grain 11.
[0049] In yet another implementation, the shape of the grain pile inside the grain tank 11 is determined using one or more non-contact sensors 170, such as at least one camera, emitter-detector pair, infrared device and device a ultrasound. In one implementation, sensor 170 is mounted inside, along the side or above the grain tank 11. In one implementation, sensors 170 are used to confirm the expected shape of the grain pile based on modeling. In yet another implementation, the shape of the grain pile inside the grain tank 11 is determined only from signals from sensors 170. In still other implementations, other types of sensors can be used to sense or detect the volume and / or shape of the grain pile being accumulated inside the grain tank 11.
[0050] In an implementation, the predetermined location of the first sensor is selected to maximize the accuracy of the mathematical model that provides the total mass of the grain pile. In an implementation, at least one sensor is usually located below the predicted apex location. In another mode, at least one sensor is positioned at a horizontal distance away from a vertical vector from the apex, so that the sensor is not directly below the apex. In another embodiment, a first sensor is usually positioned in the area below the apex, and a second sensor is positioned inside the grain tank 11, so that it is not usually below the apex of the grain pile, but below another portion of the grain pile. In another embodiment, a third sensor or more sensors are placed inside the grain tank 11 to determine the mass and / or weight of a portion of the grain pile at positions different from the location of the first and second sensors.
[0051] In one embodiment, a position of the grain pile and the location of the first sensor are assumed to be fixed. In this case, the entire volume and mass of the grain pile can be determined by the signal provided by the first sensor. In one embodiment, a position of the grain pile is determined based on the signals provided by at least the first sensor and the second sensor. Once the distance between the first sensor and the second sensor is known, the signals from the first sensor and the second sensor are adjusted to the expected shape of the grain pile there by determining a position of the grain pile inside the grain tank and calculation of the volume and mass of the whole grain pile. In one embodiment, the entire grain mass within the grain tank is determined. In one embodiment, the shape of the grain tank is used to determine the entire mass of the grain within the grain tank.
[0052] In one embodiment, the mass change of grain within the grain tank over a period of time is determined. In this mode, it is not required to determine the entire amount of grain within the grain tank. As described in more detail below, a mathematical model is used to determine the change in a grain mass from a first point in time to a second point in time. If the shape of the grain pile is known, it is possible to determine the change in a grain mass by determining the change in the grain pile size from a first point in time to a second point in time. In this mode, it is not necessary to know the quantity of grains at the first point in time, only the change in the quantity of grains between the first point in time and a second point in time. In one embodiment, the shape of the grain tank below the grain pile is not required to determine the mass change of grain within the grain tank over a period of time.
[0053] In one embodiment, the grain in the grain tank forms a cone shape having an apex 158 in the first time and a second higher apex 164 in a second time later, in which grain is being deposited within the grain tank between the first half and the second half later. In one embodiment, apex 158 and / or apex 164 is positioned at a first distance from a first wall 146 of the grain tank 11 and at a second distance from a second wall 148 of the grain tank. In one mode, the first distance is not the same as the second distance.
[0054] Figure 4 illustrates an example method 80, in which a single sensor element for the accumulation sensor 113 is used to calibrate the mass flow sensor 112. As shown by block 82, sensor 126 senses an accumulated mass grain 28 in grain tank 11. As noted above, in one implementation, sensor 126 comprises a load sensor, which senses the column portion of the grain pile within grain tank 11, in which an estimate of the flow of grain grain into the grain tank 11 is determined based on sensed changes in the weight of the column portion of the grain pile and an expected shape of the grain pile. Changes in the weight of the particular portion of the grain pile being sensed by sensor 126 are determined based on signals from sensor 126, taken at different times during the growth of the grain pile inside the grain tank 11.
[0055] As indicated by block 84, the flow estimator 14 calibrates the mass flow sensor 112 based at least in part on a signal from sensor 126. In one implementation, the flow estimator 14 compares the flow that is determined based on signals from sensor 126 with the flow rate being determined based on signals from sensor 112 to determine how sensor 112 is to be adjusted or calibrated. Using this comparison, flow estimator 14 calibrates sensor 112. In one implementation, such calibrations are performed by flow estimator 14 either continuously or in a pre-defined periodic manner while grain tank 11 is being filled with grain during harvest.
[0056] Figure 5 illustrates an example method 180. Method 180 is similar to method 80, except that method 180 involves sensing two portions of the grain pile being formed inside the grain tank 11 during grain harvest to determine the calibration flow estimate. As shown by block 186, sensor 130 senses an accumulated mass of the second portion 132. In an implementation, like sensor 126, sensor 130 comprises a load sensor, which senses changes in the weight of the column portion of the sensor stack above 130.
[0057] As indicated by block 188, the flow estimator 14 calculates or determines a calibration flow, a first estimate of the rate at which grain is flowing into the grain tank 11, by determining the rate at which the weight of particular portions of the pile or pile of grain within the grain tank 11 is changing over time, in combination with the expected shape of the grain pile. The flow estimator 14 determines the rate at which the estimated weight of the particular portions of the grain pile in the grain tank is changing over the particular time period by determining the weight of the portions above sensors 126 and 130 at different times using signals from sensor 126, sensor 130.
[0058] In one implementation, instead of using signals from all of the available sensors 126, 130, 134 at different times, in combination with the shape of the grain pile inside the grain tank 11 to determine a calibration flow for calibrating sensor 112 over different times, flow estimator 14 uses signals from a selected subset of the total available number or set of sensors in combination with the shape of the grain stack to determine the calibration flow estimate. In one implementation, the grain accumulation sensor 113 comprises an array of individual sensor elements, similar to sensor elements 126, 130 and 134. In such an implementation, the flow estimator 14 selectively uses the change detected by weight of different portions in different times depending on the shape of the grain pile or the extent to which the grain tank 11 is filled. For example, in an implementation, when the grain pile has a first shape, the flow estimator 14 uses signals from a subset of the entire set of sensor elements to determine the calibration flow estimate to calibrate sensor 112. Subsequently , when the grain pile has a second different shape, the flow estimator 14 uses signals from a different subset of the entire set of sensor elements to determine the calibration flow estimate to calibrate sensor 112 at a later time. By using different subsets of sensors or sensor elements at different times, based on the shape of the grain pile, to determine the calibration flow estimate, the flow estimator 14 increases the accuracy or reliability of the calibration flow estimate and the accuracy or reliability of the calibration or adjustment applied to sensor 112 at different times.
[0059] As indicated by block 190, flow estimator 14 calculates or determines a second mass flow or a sensed flow using signals from sensor 112. As indicated by block 192, flow estimator 14 uses a calibration flow determined in block 188 and the sensed flow determined in block 190 to calibrate sensor 112. In one implementation, flow estimator 14 compares a calibration flow with the sensed flow, to determine whether and how sensor 112 should be adjusted or calibrated.
[0060] In an implementation, the calibration of sensor 112 in block 192 is performed in response to one or more predefined criteria or limits being satisfied. For example, in one implementation, flow estimator 14 adjusts or calibrates sensor 112 only when or after the weight of a selected portion of the grain pile is greater than a predetermined value and less than a second largest predetermined value. For example, in one implementation, flow estimator 14 only calibrates sensor 112 on the weight of the sensor above portion 126 exceeds a predefined limit. In another implementation, the flow estimator 14 automatically adjusts or recalibrates sensor 112 in response to determining a change in the weight of a selected portion of the stack exceeding a predefined limit or criterion.
[0061] In one embodiment, calibration is only started after a determination is made to determine whether the amount of grain collected, deposited within the grain tank, falls within acceptable limits to allow the calibration procedure to provide sufficiently accurate results . The grain range collected, within the grain tank, which is necessary to provide sufficiently accurate results for calibration purposes with a mass flow sensor, is determined at least in part by the geometry of the grain tank 11. As discussed above in a modality, a predicted shape of the grain stack in the grain tank 11 may require a minimum amount of grain deposited within the grain tank 11. Similarly, the predicted shape of the grain pile in the grain tank 11 may require that the amount of grain deposited within the grain tank 11 is below a maximum amount of grain. In one embodiment, if the amount of grain collected exceeds the maximum predetermined amount of grain, the calibration and / or recalibration process is aborted.
[0062] Figure 6 illustrates an example method 200 to calibrate sensor 112. Method 200 is similar to method 80, except that method 200 uses a sensed volume of grain as a parameter to calibrate sensor 112. As indicated by block 204, the flow estimator 14 uses signals from sensor 170 (shown in figure 2) to sense or determine a volume of at least a portion of the grain pile. As indicated by block 206, flow sensor 14 calibrates a mass flow sensor 112 based at least in part on the volume of the first grain portion in the grain tank 11. As noted above, in one implementation, sensor 170 comprises at least less a non-contact sensor, such as at least one camera, and an infrared device and / or an ultrasound device, which senses changes in the grain volume inside the grain tank 11.
[0063] In one implementation, sensor 170 comprises a vision sensor that obtains an image that is processed to determine the shape of at least a portion of the grain pile. As schematically shown in figure 2, in an implementation, sensor 170 is located close to the grain tank 11 to allow a view of the interior of the grain tank 11. In one implementation, sensor 170 is attached to the grain tank 11 or is attached to the outer structure of the grain tank 11.
[0064] In the illustrated example, based on instructions in memory 18, processor 16 of flow estimator 14 models the volume of the grain pile at least in part as a function of the image. The sensor 70 records the shape of the grain pile surface, from which the entire volume of the grain pile is determined. In such an implementation, the flow estimator 14 uses the entire estimated volume of the grain pile at different times to determine a calibration flow, which is compared with the sensed flow from sensor 112, to calibrate sensor 112.
[0065] In another implementation, the flow estimator 14 determines a calibration flow based on a determined change in volume of one or more distinct portions, smaller than the total, of the grain pile inside the grain tank 11, in different times. For example, in one implementation, the flow estimator 14 determines a first shape of at least part of the exposed surface of the grain pile at first based on signals from sensor 170 and then determines a second shape of at least part of the exposed surface of the grain pile in a second time. By comparing the different shapes of the exposed upper surfaces of the same portion of the grain pile at different times, the flow estimator 14 determines a change in the volume of the particular portion of the grain pile. In one embodiment, the change in volume of the grain pile portion from the first time to the second time is determined using an algorithm that models the difference or change in volume of the grain pile portion from the first time to the second time. time. In one embodiment, the algorithm is based at least in part on a predicted grain pile format. Using this volume-determined change, the flow estimator 14 determines a calibration flow to adjust sensor 112.
[0066] Figure 7 is a flow chart illustrating an example method 210, in particular the implementation of method 200. Method 210 is similar to method 200, except that method 210 calculates a calibration flow rate additionally based on a change in weight over time of each of one or more portions of the grain pile that accumulates within the grain tank 11. As indicated by block 212, the flow estimator 14 receives signals from sensor 170 and determines a volume of the particular portion of the grain pile. In another implementation, the flow estimator 14 uses signals from sensor 170 to determine a volume of the entire grain pile that accumulates within the grain tank 11.
[0067] As indicated by block 214, the flow estimator 14 additionally receives signals from the one or more sensing elements 126, 130, 134 of the accumulation sensor 113 (shown in figure 2) indicating the sensed weight of each of the portions of the grain pile extending above the sensing elements 126, 130, 134. As indicated by block 216, the flow estimator 14 uses the sensed weight of each portion of the grain pile to calculate a first mass flow mass flow calibration In one implementation, the flow estimator 14 determines a calibration flow based on changes in the weight of the individual portions of the grain pile extending above the sensing elements 126, 130, 134 and the shape of the grain pile that accumulates within from grain tank 11. In yet another implementation, flow estimator 14 determines a calibration flow based on changes in the weight of the entire grain pile that accumulates within grain tank 11, where flow estimator 14 determines changes in the weight of the entire grain pile based on signals from sensing elements 126, 130, 134 at different times and based on the shape of the pile or pile of grain within the grain tank 11. In one implementation, the weight of the whole grain pile is additionally based on a weight of the grain tank 11 when the grain tank 11 is empty.
[0068] As indicated by block 218, flow estimator 14 calculates or determines a second mass flow or sensed mass flow using signals from sensor 112. As indicated by block 220, flow estimator 14 uses a calibration flow and the sensed flow to calibrate sensor 112. In one implementation, flow estimator 14 compares a calibration flow with the sensed flow to determine whether and how sensor 112 should be adjusted or calibrated. In one implementation, calibration of sensor 112 in block 220 is performed continuously or at a pre-defined frequency based on time, the movement of the combine and / or grain harvest.
[0069] Figure 8 is a flow chart illustrating an example method 300 to calibrate sensor 112. In one implementation, flow estimator 14 is configured to perform method 300. Method 300 controls whether, when and how sensor 112 is calibrated based on additional operating data or parameters. As indicated by block 302, flow estimator 14 determines a calibration flow for use in calibration sensor 112. As described above, in one implementation, flow estimator 14 determines a calibration flow based on a shape of the grains and the determined change in mass and / or volume of at least a first portion of the grain stack in the grain tank 11 over a period of time as a function of signals received from at least one sensor, such as one or more sensors 126 , 130, 134 and / or 170, as described above.
[0070] As indicated by block 304, the flow estimator 14 still receives one or more operational data received from at least one first device. The operational data includes, but is not limited to, either alone or in any combination: the volume of grain within the grain tank; the extent of "spacing or rotation" of the grain tank; the intensity of vibrations of the grain tank; the angle and speed at which the grain tank was turned; the ground speed of the grain tank; the acceleration and deceleration of the grain tank; the speed of a harvested grain coming out of the gutter; the non-harvest hitch period; the change in mass flow over a given period of time; the moisture content of the grain; the type of grain; Meteorological conditions; and the harvest land including, but not limited to, the slope of the land on which the grain was harvested.
[0071] As indicated by block 306, the flow estimator 14 evaluates the operational data to determine the probability that an accurate calibration flow estimate can be determined. In the illustrated example, the flow estimator 14 uses a decision algorithm, stored in memory 18, to determine a probability that the change in mass of at least the first portion of the grain column in the grain tank will provide an accurate estimate of the change in mass of whole grain within the grain tank. As indicated by block 308 and block 310, if the flow estimator 14 determines from the operational evaluated data that the probability that a calibration flow is not sufficiently accurate, the flow estimator 14 aborts or delays the programmed calibration of sensor 112 in particular time. Alternatively, as indicated by block 308 and block 310, if the flow estimator 14 determines from the evaluated operational data that the probability that a calibration flow is sufficiently accurate, the flow estimator 14 proceeds with the calibration sensor 112 using the determined calibration flow. In one implementation, the flow estimator 14 determines a calibration factor for sensor 112 based on a comparison of a calibration flow and the sensed flow.
[0072] In one implementation, the flow estimator 14 receives the operational data comprising the sensed mass flow, based on sensor 112 signals, over the period of time in which a harvested grain was deposited inside the grain tank 11 to determine whether the sensed mass flow falls within predetermined limits. The flow estimator 14 assesses the flow sensed in block 306 to determine if the mass flow sensed grain within the grain tank varies to a greater extent than a pre-defined limit. Per block 310, if the flow estimator 14 determines that the sensed mass flow rate is not sufficiently constant so that the calibration flow calculated based in part on the shape of the grain pile cannot provide acceptable accuracy, sensor calibration 112 using the calibration flow it is temporarily aborted or delayed until a later time. Alternatively, if the flow estimator 14 determines that the sensed mass flow is sufficiently constant, having a certain variability below a pre-defined limit, the flow estimator 14 proceeds with calibration sensor 112 using a calibration flow.
[0073] In another implementation, the flow estimator 14 receives the operational data, such as a real state of the harvester, to determine whether the calibration of sensor 112 should be performed. In one implementation, per block 304, the flow estimator 14 receives signals indicating a "spacing or rotation" of the grain tank 11.
[0074] Per block 306, the flow estimator 14 evaluates such signals to determine if the amount of "offset or rotation" of the grain tank 11 is outside an acceptable range. When the combine 20 and / or the grain tank 11 provides the offset and / or rotation, the shape of the grain pile within the grain tank 11 can be modified from its predicted shape. The slope of the ground where the grain is being harvested, the vibrations of the grain tank 11, the extent to which the grain tank is turned abruptly or rapidly, by the extent to which the grain tank is subject to rapid accelerations and decelerations, and the soil speed of the combine and / or grain tank 11 during grain harvest will impact the shape of the grain pile collected inside the grain tank. If the shape of the stack in the grain tank deviates from the predicted shape used in the mathematical model, the accuracy of the mathematical model to determine the grain accumulated during the relevant period of time will be impacted. In an implementation, if the amount of "offset or rotation" of the grain tank 11 falls outside predetermined limits, the calibration and / or recalibration process is terminated or delayed by block 310.
[0075] Figure 9 is a flow chart of method 350, different from the example implementation of method 300. Method 350 is similar to method 300, except that method 350 determines whether any possible inaccuracies identified from the evaluation of the operational data can compensated, allowing the continuous calibration of sensor 112. Those steps or blocks of method 350, which correspond to the steps or blocks of method 300 are listed similarly.
[0076] As shown in figure 9, compared to method 300, method 350 additionally comprises blocks 314 and 316. In decision block 314, flow estimator 14 determines whether flow estimator 14 can compensate for possible inaccuracies identified in block 308. As indicated by block 310, if such inaccuracies cannot be compensated for, the calibration of sensor 112 is aborted or delayed. Alternatively, as indicated by block 316, if such possible inaccuracies, identified as a result of the evaluation of the operational data in block 306, can be compensated, the flow estimator 14 applies one or more compensation factors or amounts to a calibration flow for address identified inaccuracies. Once the compensation factor has been added to a calibration flow, the flow estimator 14 proceeds with the calibration or adjustment of the mass flow sensor 112, as indicated by block 312.
[0077] In an implementation of method 350, for block 304, the flow estimator 14 receives signals indicating an amount of "spacing or rotation" from the grain tank 11. According to block 306, the flow estimator 14 evaluates the such operational data to identify possible inaccuracies at a determined calibration flow using the results of block 302. According to block 312, flow estimator 14 determines whether the amount of "offset or rotation" of the grain tank 11 during the period where the grain in the grain tank 11 was collected falls outside the predetermined limits, so that inaccuracies can result. As indicated by block 314, the flow estimator 14 determines whether the effects of "spacing or rotation" can be compensated. As indicated by block 316, the flow estimator 14 compensates for the identified inaccuracies. In one implementation, the flow estimator 14 reviews the mathematical model of the geometric shape of the grain pile inside the grain tank 11 to take into account the impact that "spacing or rotation" has on the geometric shape of the grain pile. In this way, the mathematical model will provide accurate results even though the "spacing or rotation" has the shape of the grain pile.
[0078] In one implementation, the flow estimator 14 compensates for inaccuracies, such as those inaccuracies caused by the "spacing or rotation" of the grain tank 11, by selectively adjusting which of the sensing elements of the grain accumulation sensor 113 are used to determine a calibration flow. For example, in one implementation, the grain accumulation sensor 113 comprises an arrangement of the sensing elements in different locations or having different sensing characteristics. The flow estimator 14 selects and uses signals from a subset of the available sensing elements to determine a calibration flow in step 302.
[0079] In one embodiment, if the "spacing and / or rotation" were constant, mathematical modeling is used to adjust a position of the grain pile in relation to gravity and the impact on sensor 126 and / or sensor 130 e / or additional sensors, such as sensor 134, are considered. In one embodiment, the "spacing and / or rotation" of the grain tank 11 is determined based on sensors 171 (schematically shown in Figure 2) that are either located in the grain tank 11 or close to the grain tank 11 so that sensors 171 provide an accurate representation of the "spacing and rotation" of the grain tank 11. For example, if the grain tank is integral and / or has the same "spacing and / or rotation" as the combine 20, the 171 sensors they can be placed on, or in relation to, the combine 20, to sense and report "spacing and / or rotation". In one embodiment, the “spacing and / or rotation” can be evaluated and stored for the entire period or at selected time intervals, in which the grain in the 11 grain tank was collected. Alternatively, the "offset and / or rotation" data from a sensor is only sent to processor 16 of flow estimator 14 if a certain predetermined threshold is exceeded. The orientation of the grain tank 11 can be determined to evaluate the data from at least one of the sensor 126, the sensor 130 and additional sensors 134 for compensation inside the grain tank being in a non-neutral orientation, which, in a modality, means an orientation by design of the grain tank in relation to the gravity direction.
[0080] The non-harvest hitch can include the period of time between the point at which the harvester enters a harvest and re-enters the harvest. In one embodiment, hitching or not hitching the crop, which can occur when the combine moves in and out of the crop, such as between rows or area of a crop where no harvest occurs. In one embodiment, this time period is taken into account for determining grain mass changes over a period of time and / or a calibration process. In one embodiment, the time period in which the harvester is out of harvest is taken into account for, and deducted from, or subtracted from, the total time period in which grain is being harvested. This eliminates the time period, in which no harvest is being carried out. The time delay between harvest and the deposit of grain inside the grain tank is also taken into account as a factor. It may be the case that grain is continued to be deposited inside the grain tank while the harvester is physically out of the harvest, while the harvester leaves, turns and re-enters the harvest field. The period of time during which the harvest is interrupted can be taken into account and adjusted accordingly. In addition, the time delay between cutting the plant material and the grain being deposited within the grain tank can also be taken into account for the determination of the mass flow and / or load weight accumulated over a given period of time. The time being adjusted for the time period when the combine is out of the field and / or when no grain is being harvested.
[0081] In one embodiment, the operational data includes the moisture content of the grain being harvested. The moisture content of the grain being harvested is determined with a sensor near the grain tank, while the grain is being harvested, or, alternatively, a moisture content factor can be fed through a user interface for the grain estimator. flow 14.
[0082] In a modality, where the operational data falls outside the acceptable limits that would provide an accurate determination of the mass flow rate of grain during a period of interest, the calibration process will be aborted. In a modality, in which the operating data falls outside the ideal limits, but not outside the acceptable limits, the calibration process is continued and an accuracy indicator is provided. The precision indicator increases the probability that the mathematical model will provide accurate results. The operator can then assess whether to calibrate the mass flow sensor based on whether the results of the mathematical model would provide an improved calibration of the mass flow sensor 112.
[0083] In another modality, the operational data are evaluated before a determination as to whether the data is sufficient to calculate an accumulated load mass and / or mass flow change. In one modality, a quality metric is applied to each operational data measurement obtained. The quality metric of each operational data measurement obtained may be a binary value or a probability that the measurement obtained will result in a quality or erroneous calculation of the accumulated mass and / or mass flow of the grain. The quality and / or probability metrics for each measurement can be combined together in such a way to determine an accumulative probability that the accumulated grain mass and / or flow taken over a period of time will not be erroneous and / or of value. The probability of the quality of the estimated accumulated mass accuracy is determined based on a function of the quality of the individual measurements and the collective use of the individual measurements. In one embodiment, the operational data is evaluated from at least one first device and a decision algorithm can be used to determine a probability that the estimate of a grain mass in the grain tank is accurate.
[0084] The methods and devices described here can be applied while the combine is in the field, out of the field and / or in motion. For purposes of a modality, moving describes the period while the harvester is actually moving within the field, harvesting grain, so that grain is being picked up from the field, processed in the harvester and deposited inside a grain tank. Rather, the term in the field describes where the harvester is located in the field, but it may or may not be harvesting grain at a particular time. While out of the field it describes the situation where the harvester is no longer in the field and / or harvesting grain. In one embodiment, the accumulated grain mass estimate and mass flow sensor calibration are conducted while in motion. It is also contemplated that the estimation of the accumulated grain mass and / or calibration of the mass flow sensor can be conducted in the field and outside the field.
[0085] Figure 10 is a graph illustrating the relationship between three different sensors and the total grain weight in the grain tank 11. The response of the load cells or sensors is a relatively linear one. In the example illustrated in figure 5, this initial response region is from approximately 0.1 mV / V to 0.6 mV / V. Several pieces of information can be extracted from this region to provide the grain flow estimate into the grain tank 11 and provide some sense of the accuracy of the estimate. This information is then applied to a regression equation that provides a resulting mass flow rate estimated in kg-s-1.
[0086] Load cell placement and equations are specific to a given combine design. In one implementation, modifications to the source worm 114 and the way in which the grain is expelled into tank 111 use a different regression equation to obtain the acceptable level of accuracy. The same information is expected to be extracted from the load cell responses, which is described in more detail in this document for a different hardware configuration with possibly additional modifications to the specified calibration ranges.
[0087] In one embodiment, a general regression equation for estimating grain flow in the grain tank
LC1SlopeI is the Response Rate of Load Cell 1 in the first specified range; LClSlopelI is the Response Rate of Load Cell 1 in the 2 specified range; LC3Slope is the Response Rate of Load Cell 3 in the specified calibration range; AoR2 is the estimated angle for grain rest between Load Cell 3 and Load Cell 2; and SudoMassFlow is the mass flow proxy estimate based on the Load Cell 1 response, time interval, and estimated angle of rest between Load Cell 1 and Load Cell 2
[0088] In one embodiment, the parameters selected for the regression equation are developed by evaluating the load cell responses to determine the most accurate and repeatable method for estimating the grain mass flow. In one embodiment, parameters are selected based on their statistical significance to the reduction of error in a mass flow estimate.
[0089] In one embodiment, in which multiple sensors 126, 130, 134 are used and in different locations within the grain tank 11, one of the sensors can respond after the other two sensors. The linear regions of the responses of the three sensors may overlap slightly, but are dependent on the angle of rest and grain density. This introduces some variability in the estimation of a flow as the information from the sensors. Two of the sensors can be extracted during a different flow rate than the third sensor based on the difference in time in which the grain stack reaches each sensor.
[0090] In one embodiment, the rate of change of the sensors has a high correlation to a mass flow of grain into the grain tank with a linear response to increase grain flow. All three sensor responses can be included in a regression analysis to reduce the error in estimating grain mass flow.
[0091] In one embodiment, the calibration algorithm can take into account the calibration history before calibration, based on the probability of the accuracy of the measurements. For example, for an initial calibration, a lower probability of precision quality can be used in the calibration process. However, after the calibration has been performed, a higher probability of precision quality of the accumulated grain mass and / or mass flow, which was previously obtained, will be required to ensure that the calibration or recalibration does not result in a more poor accuracy mass flow.
[0092] It is possible to estimate the amount of grain in the grain tank to enter in a first time and then to estimate the amount of grain in the grain tank in a second time later. It is also possible to estimate the grain flow between a first time and a second time without actually estimating the entire grain mass within the grain tank. The calibration algorithm can estimate the mass change of the grain between the first time and the second time without estimating the entire grain mass in the grain tank through either the first time or the second time, which signals are received from the sensors or load cells. The second time refers to a period of time after the first time, during which grain is deposited within the grain tank.
[0093] In one embodiment, the calibration process begins once when the grain pile inside the grain tank reaches a minimum volume. The calibration process is completed before a predetermined maximum amount of grain is there within the grain pile in the grain tank. In another embodiment, the calibration process begins when the grain tank is empty and ends once when the minimum predetermined amount of grain has been deposited within the grain tank. In another mode, the calibration and / or recalibration process takes place while the grain is being harvested and a calibration factor is applied to the mass flow rate for the rest of the harvest period. In another embodiment, a calibration factor is applied to the mass flow data that has been stored in memory to provide a more accurate mass flow for the entire harvest period. In this way, the mass flow of grain obtained and subsequently analyzed from the mass flow sensor is more accurate from the beginning of the grain harvest. A grain production map can be provided, showing the mass flow of grain to areas of the field or crop being harvested. The grain production map can be based on the mass flow rate of the mass flow sensor, adjusted with the calibration and / or recalibration factor or factors obtained during the calibration process.
[0094] In one mode, operational data can be collected and stored in memory over a period of time. Operational data can be evaluated over various time periods, in which the operating data was collected. A particular time period can be selected from the global time period, in which data was collected to obtain or calculate an estimated accumulation of grain mass and to calibrate the mass flow sensor. For example, if the operational data is obtained every ten seconds over a period of ten minutes, and it is determined by an algorithm that the probability of precisely estimating the accumulated grain mass is the maximum over a period of three minutes between the fourth minute and the seventh minute, then the operational data obtained during this three minute period can be used to estimate the accumulated grain mass and to calibrate the mass flow sensor. In one example, mass flow sensor calibration can be performed multiple times as the probability that operating data during data time intervals will provide greater accuracy of the estimate. As noted above, in one embodiment, the mass flow sensor calibration can be done in motion. The accumulated mass, once calculated, is determined both in a first time and in a second time. The mass change accumulated between the first half and the second half can be used to determine the mass change over the time period between the second half and the first half. As an example, if the estimated accumulated mass in the first time is determined to be an “x” value and the estimated accumulated mass in the second time is determined to be an “y” value, the accumulated mass during the period between the second time and the first time is “y - x”.
[0095] The signal from the mass flow sensor can be stored in memory and, once the mass flow sensor calibration is done, the data stored from the mass flow sensor before calibration can be adjusted to provide a more accurate mass flow over the entire period in which the harvester was operational for a particular field over a particular period of time.
[0096] In one modality, multidimensional calibrations can be used based on the moisture of the grain, production rate, and / or conditions of the ground. This would allow calibration of the mass flow sensor based on certain harvest conditions and would allow instant calibrations in the calibration based on grain moisture sensor input, terrain conditions, flow and other measurements identified here either alone or in combination with other measurements. In one embodiment, different calibration curves can be used to calibrate the mass flow sensor based on sensor data related to grain moisture from a 172 sense (schematically shown in Figure 2) or terrain and / or other measurements operational data. Calibration can be done in motion to reflect grain moisture and / or other selected metrics, thus providing a higher level of mass flow accuracy.
[0097] Although the present description has been described with reference to example modalities, workers skilled in the art will recognize that changes can be made in form and detail without departing from the spirit and scope of the claimed matter. For example, although different example modalities have been described as including one or more features that provide one or more benefits, it is contemplated that the described features can be interchanged with one another or alternatively be combined with another in the described example modalities or in other alternative modalities. Because the technology of the present description is relatively complex, not all changes in technology are predictable. The present description, described with reference to the exemplary modalities and set out in the following claims, is clearly intended to be as broad as possible. For example, unless specifically noted to the contrary, claims that cite a single particular element also encompass a plurality of such particular elements.

权利要求:
Claims (22)
[0001]
1. Method for calibrating a mass flow sensor (12, 112), comprising: determining a change in mass of at least a first grain portion in a grain tank (11) over a period of time as a function of signals received from at least one sensor (13, 113, 126, 170); evaluate operational data received from at least one first device, used a decision-making algorithm to determine a probability that the change in mass of at least one portion of grain in the grain tank will provide an accurate estimate of the change in mass of at least all the grain inside the grain tank (11); and determine a calibration factor for a mass flow sensor (12, 112) based at least in part as a function of the signals received from at least one sensor (13, 113, 126, 170), characterized by the fact that the at least one sensor comprises a first sensor having a surface for contacting grains in the grain tank (11), the first sir to provide a signal indicating a total mass of a grain column located directly above the first sensor, the grain column having a cross-sectional area corresponding to a surface area of the surface of the first sensor.
[0002]
2. Method according to claim 1, characterized by the fact that the evaluation of the operational data includes the attribution of a probability value that the change in the mass of grains in the grain tank as a function of at least one sensor during the period of time is accurate.
[0003]
3. Method according to claim 1, characterized by the fact that the operational data includes one or more measurements of at least one member of the group consisting of a combine, a land for cultivation, and grain moisture, and the evaluation of the operational data it includes assigning a probability value that the estimate of the change in grain mass in the grain deposit is accurate, and additionally including mass flow sensor calibration only if the probability value exceeds a given value.
[0004]
4. Method according to claim 1, characterized by the fact that determining the change in mass of the grain with the grain tank includes applying the signals from the first sensor to a predetermined model of the geometric shape of the grain in the grain tank.
[0005]
5. Method according to claim 1, characterized by the fact that the operational data includes at least one member of the group consisting of: the quantity of grains in the grain tank, and the moisture of the grain during the period in which the grain was deposited in the grain tank.
[0006]
6. Method according to claim 1, characterized by the fact that the first sensor (13, 113, 126, 170) is a non-contact vision sensor (170).
[0007]
7. Method according to claim 1, characterized by the fact that the first sensor (13, 113, 126, 170) is a chamber (70) that captures an outline of an upper surface of a pile (154, 160) of the grain inside the grain tank.
[0008]
8. Method according to claim 1, characterized by the fact that the determination of the change in mass of the grain within the grain tank over time is more a function of the change in mass of a second portion of the grain within the tank of grain over the time period.
[0009]
9. Method according to claim 1, characterized by the fact that the calibration factor is determined in motion while the grain is being harvested.
[0010]
10. Method according to claim 1, characterized by the fact that it repeats the steps of determination and evaluation after an additional quantity of grain has been deposited in the grain tank.
[0011]
11. Method according to claim 1, characterized by the fact that determining the change in grain mass in the grain tank includes applying the output of the first sensor (13, 113, 126) to a model of a geometric shape that has a portion of the apex of the grain inside the grain tank higher than the other top parts of a pile (156, 160) of grain in the grain tank (11).
[0012]
12. Method according to claim 1, characterized in that the at least one sensor comprises a second sensor having a second surface for contacting grains in the grain tank, the second sensor for providing a second signal indicating a mass total of a second column of grain located directly above the second sensor, the second column of grain having an area of cross section corresponding to a surface area of the surface of the second sensor.
[0013]
13. Method according to claim 1, characterized by the fact that at least one sensor comprises a set of sensors and in which the determination of the calibration factor for the mass flow sensor is based on signals received from the first subset of the set of sensors in a first time when the grain pile has a first shape and a second subset, different from the first subset, of the sensor set, in a second time when the pilot grain has a second shape different from the first shape.
[0014]
Method according to claim 1, characterized in that said determination of the change in mass of at least a first portion of grain in the grain tank over a period of time as a function of the signals received from at least one sensor comprises determine the change in mass of a smaller than complete portion of the grain within the grain tank without determining the entire amount of grain within the grain tank.
[0015]
15. Device for calibrating a mass flow sensor (12, 112), characterized by the fact that it comprises: a processor (16); and a non-transitory computer-readable medium (18) operatively coupled to the processor (16), the computer-readable medium (18) having computer-readable instructions stored therein, when executed by the processor, makes the processor; determine a change in mass of at least a first grain portion in a grain tank (11) over a period of time as a function of the signals received from at least one second sensor (13, 113, 126) in direct contact with the grain in the grain tank; evaluate the operational data received from at least a second device, over the period of time; and determining whether the operational data is within a predetermined range to calibrate the mass flow sensor (12, 112) as a function of the change in mass in at least a first grain portion.
[0016]
16. Device according to claim 15, characterized by the fact that the processor (16) further determines the change in mass of at least all the grain in the grain tank (11) as a function of at least the signals received from at least a second sensor.
[0017]
17. Device according to claim 15, characterized by the fact that the estimate of the mass change of all grains within the grain tank includes the application of the signals received from at least one second sensor to a predetermined model of a geometric shape of a pile of grain inside the grain tank.
[0018]
18. Device according to claim 15, characterized by the fact that the at least one operational data includes the quantity of grains inside the grain tank.
[0019]
19. Device according to claim 15, characterized in that the evaluation of the operational data includes determining a probability that the change in mass of at least the first portion of grains within the grain tank will provide an accurate estimate of the change in the whole the grain in the grain tank during the time period in which the operational data was obtained, and calibrate the mass flow sensor only if the probability is greater than a predetermined probability value.
[0020]
20. Device according to claim 15, characterized in that the at least one second sensor comprises a second sensor, and in which the processor additionally makes the estimate of the change in the total grain mass in the grain tank during the time period as a function of the change in mass of a second grain portion in the grain tank during the time period as a function of the signals received from the second sensor.
[0021]
21. Device according to claim 20, characterized in that the processor additionally provides a calibration factor as a function of the change in the mass of the first grain portion in the grain tank and the change in the mass of the second grain portion in the tank of grain.
[0022]
22. Method for providing a calibration factor for a mass flow sensor (12, 112), characterized by the fact that it comprises: estimating a mass change in a grain pile in a grain tank (11) over a period of time as a function of signals from at least one intermediate sensor (134), from one stage to the grain tank and from the grain using a predetermined model of a geometric shape of the grain pile in the grain tank, where the shape it has a higher apex than other regions of the grain pile; evaluate the operational data received from at least one first device, using a decision-making algorithm to determine whether the operational data is within an acceptable range to assess the mass flow of a mass flow sensor; and determining a calibration factor for a mass flow sensor based, at least in part, on the estimated change in mass of at least the entire grain stack in the grain tank as a function of at least one sensor.

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CN105210541A|2016-01-06|

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CN105210541B|2020-08-04|

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US20150377690A1|2015-12-31|

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AU2015203446A1|2016-01-21|

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US9645006B2|2017-05-09|

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BR102015015315A2|2017-10-24|

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法律状态:
2017-10-24| B03A| Publication of a patent application or of a certificate of addition of invention [chapter 3.1 patent gazette]|

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2018-10-30| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|

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2020-04-22| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|

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2020-10-06| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|

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2020-12-29| B16A| Patent or certificate of addition of invention granted [chapter 16.1 patent gazette]|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 24/06/2015, OBSERVADAS AS CONDICOES LEGAIS. |

优先权:

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申请号 | 申请日 | 专利标题

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US14/318254|2014-06-27|

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US14/318,254|US9645006B2|2014-06-27|2014-06-27|Calibration of grain mass measurement|

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US14/318,254|2014-06-27|

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