• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    METHODS FOR DETERMINING CLOUD WATER DROP SIZE DISTRIBUTIONS. In one aspect, methods of determining a water droplet size distribution in a cloud are described herein. In some embodiments, a method of determining a water droplet size distribution in a cloud comprises a sampling depth of the cloud with an electromagnetic radiation beam, measuring a scattering signal from the electromagnetic radiation returned from the cloud over a range of field of view angles to provide a measured spread curve [Ptotal (theta)], removal of a portion of the measured spread curve, replacement of the removed part with an extrapolation of the remaining measured spread curve to provide an estimated scattering curve, and determining a first estimated droplet size distribution [n (1) (D)] from the estimated scattering curve.
    公开号:BR102012019441B1
    申请号:R102012019441-4
    申请日:2012-07-25
    公开日:2020-10-27
    发明作者:Mark D. Ray；Kaare J. Anderson；Michael P. Nesnidal
    申请人:Rosemount Aerospace Inc.；
    IPC主号:
    专利说明:

    FIELD
    The present invention relates to methods for determining water droplet distributions from clouds. FUNDAMENTALS
    The detection of water droplets in the air and their classification in a droplet size distribution is an important function in aircraft operation. Different cloud formations may have different water droplet size distributions and associated cloud liquid water content (LWC), which poses different risks to aircraft, such as ice formation.
    The water droplet size distribution and the LWC of a cloud can be determined or estimated in several ways. Several existing methods are based on diffraction droplet sizing techniques. However, such diffractive sizing techniques are limited to a maximum detectable droplet diameter due to the small angle spread of large water droplets. For example, diffractive scattering by large droplets at angles within the angle of divergence of the probing laser beam is insoluble from the laser beam itself with current detection systems. As a result, information about the presence of a large droplet distribution in excess of the maximum resolvable diameter is lost, potentially leading to errors in determining the water droplet size distribution and associated cloud LWC. SUMMARY
    In one aspect, methods for determining the water droplet size distribution of a cloud are described herein, the method representing the presence of droplets greater than the maximum detectable droplet diameter. In addition, the methods described here include estimating the cloud LWC using the determined water droplet size distribution.
    In some embodiments, a method of determining a water droplet size distribution in a cloud comprises a sampling depth of the cloud with an electromagnetic radiation beam, measuring a scattering signal from the electromagnetic radiation returned from the cloud over a viewing angle field range [totai (©)] 3- in order to provide a measured scattering curve, removing part of the measured scattering curve, replacing the removed part with an extrapolation of the remaining measured scattering curve in order to provide an estimated scattering curve, and determining a first estimated droplet size distribution [n (1! (D)] from the estimated scattering curve. In some embodiments, the first estimate of the droplet size distribution is determined using an advanced spreading model.
    In some modalities, the method also includes the provision of a scattering curve calculated from air n (MW1 — used — am — modetQ — of — direct backscatter and an advanced scattering model and comparison with the scattering curve measured in order to determine whether the calculated spread curve follows the measured spread curve within an adjusted tolerance. In some modalities where the calculated spread curve does not follow the measured spread curve within the adjusted tolerance, a first estimate of a median volume diameter droplet (DMVD <: L)) and shape parameter (p1) are derived from n (1) (D). The DMVD value (1) in response to the calculated spread curve that does not follow the spread curve measured within the adjusted tolerance in order to provide a second estimate of the median droplet volume diameter (DMVD (2>) and using (DMVD <2)) and p (l) to provide a second estimate of the droplet size distribution n (2) (D).
    The second scattering curve calculated is provided from n (2) (D) using the direct backscattering model and the advanced scattering model, and the second calculated scattering curve is compared with the measured scattering curve in order to determine if the second scattering curve follows the scattering curve measured within the adjusted tolerance. In some embodiments, the second scattering curve calculated follows the scattering curve measured within the adjusted tolerance, and n (2) (D) represents the distribution of water droplets that have a diameter beyond the maximum detectable droplet diameter. In such embodiments, the method may further comprise determining the effective droplet diameter (Deff) using n <2) (D) and determining the liquid water content of the cloud using Deff.
    Alternatively, the second spread curve calculated does not follow the spread curve measured within the adjusted tolerance, and the method comprises the additional steps. In some modalities, for example, the method further comprises changing the DfíW value <2) in response to the calculated spreading curve that does not follow the spreading curve measured within the adjusted tolerance to provide a third estimate of the median volume diameter of the DMVD droplet (3). A third water droplet size distribution estimate [n <3) (D)] is provided using n (3) (D) and p1.
    A third spread curve calculated is provided from n (3) (D) using the direct backscatter model and the advanced spread model, and the third calculated spread curve is compared with the measured spread curve in order to determine if the third scattering curve follows the scattering curve measured within the Deffinida tolerance. In some embodiments, the calculated spreading curve follows the spreading curve measured within the set tolerance, and n (3) (D) represents the distribution of water droplets that have a diameter beyond the maximum detectable droplet diameter. In such modalities, the method can also comprise the determination of the effective droplet diameter (Deff) using level 3) (D) and the determination of the liquid water content of the cloud using O Deff •
    Alternatively, the calculated spread curve does not follow the spread curve measured within the Deffinida tolerance, the method comprises additional steps. For example, in some embodiments, the method is an iterative method comprising iterative steps that are repeated until a calculated spread curve follows the spread curve measured within the Deffinida tolerance. Therefore, in some embodiments, the method further comprises changing the DJWD * 11 'value in response to a calculated umpteenth spread curve that does not follow the spread curve measured within the Deffinida tolerance to provide an estimate n of the median volume diameter droplet [DAfVD <n + 1)], where n is an integer greater than 3. An estimated droplet size distribution (n + 1) of [n (n + 1) (D)] is provided using D (n + l) ~ ,, 1
    A calculated (n + l) scattering curve is provided from n (n + 1) (D) using the direct backscattering model and the advanced scattering model, the (n + l) scattering curve calculated following the curve scattering measured within the Deffinida tolerance, en (n + 1) (D) represents the distribution of water droplets having a diameter in addition to the detectable droplet diameter. In some embodiments, the method also comprises the determination of Deff using n (n + 1) (D) and the determination of LWC of the cloud using Deff.
    These and other modalities are described in more detail in the detailed description below. BRIEF DESCRIPTION OF THE DRAWINGS
    Figure 1 illustrates an example of a scattering curve measured according to some of the modalities described here.
    Figure 2 illustrates the measured spread curve of Figure 1, in which part of the measured spread curve has been removed according to some of the modalities described herein.
    Figure 3 illustrates the measured spread curve of Figure 2, in which the removed part has been replaced with an extrapolation of the remaining measured spread curve according to some of the modalities described herein.
    Figure 4 is a flow chart illustrating an embodiment of a method described here. DETAILED DESCRIPTION
    The embodiments described herein can be more readily understood with reference to the following detailed description and drawings. The elements, apparatus and methods described here, however, are not limited to the specific modalities presented in the detailed description and in the drawings. It should be recognized that these modalities are merely illustrative of the principles of the present invention. The numerous modifications and adaptations will be easily evident to those skilled in the art without departing from the spirit and scope of the invention.
    In one aspect, methods for determining the water droplet size distribution of a cloud are described herein, the method representing the presence of droplets greater than the maximum detectable droplet diameter. In addition, the methods described here include estimating the cloud LWC using the determined water droplet size distribution.
    Returning now to the specific steps of a method described here, a method described here comprises a sampling depth of a cloud with "electromagnetic radiation. A cloud can be sampled with electromagnetic radiation at any depth that is not incompatible with the objectives of the present invention. In some modalities, the cloud is sampled at a depth no greater than the distance over which the cloud is homogeneous, or substantially homogeneous. In some modalities, the cloud is sampled at a depth of up to about 30 meters (m) In some modalities, the cloud is sampled at a depth of up to about 20 meters (m).
    In some modalities, the cloud is sampled at a depth of about 10 m to about 30 m. The cloud, in some modalities, is sampled at a depth greater than 30 m.
    The beam of electromagnetic radiation can comprise any beam that is not incompatible with the purposes of the present invention. In some embodiments, the beam of electromagnetic radiation comprises a light beam emitted from a laser. In some embodiments, the beam is polarized. In some embodiments, the beam is linearly polarized or circularly polarized. In some embodiments, the beam comprises a pulsed laser beam or a continuous wave laser beam. In some embodiments, the continuous-wave laser beam is bitten. In addition, in some embodiments, the beam of electromagnetic radiation is emitted from a light-emitting diode.
    The electromagnetic radiation beam can comprise any wavelength distribution that is not incompatible with the purposes of the present invention. In some fashion, for example The beam is a monochromatic or substantially monochromatic beam. In some embodiments, the electromagnetic radiation beam has a wavelength in the infrared (IR) region of the electromagnetic spectrum, including, among others, the infrared (NIR) region close to the spectrum. In some embodiments, the electromagnetic radiation beam has a wavelength in the visible region of the spectrum in the ultraviolet (UV) region of the spectrum. The beam of electromagnetic radiation, in some modalities, has a wavelength not absorbed or substantially absorbed by water. In some embodiments, the electromagnetic radiation beam has one or more wavelengths that fall into an optical window that is not absorbed by water. In some embodiments, for example, the beam of electromagnetic radiation has a wavelength of about 905 nm.
    In addition, the electromagnetic radiation beam can comprise any energy that is not incompatible with the objectives of the present invention. In some embodiments, the electromagnetic radiation beam has an energy or mW to tens of Mw.
    As described here, a scattering signal [totai (θ)] of electromagnetic radiation that has returned from the cloud is measured over a range of field of view angles (FOV) in order to provide a measured scattering curve. The scattering signal can be measured with a suitable detector or operable detection system to resolve the angular dependencies of the scattering signal. In some embodiments, the detector comprises a solid-state photoelectric ceiling, such as a set of photodiodes or concentric photodiode. The photodiode, in some modalities, comprises one or more of silicon (Si), germanium (Ge), gallium-indium arsenide (InGaxAsi-x), lead (II) sulfide (PbS), and combinations of these. In some embodiments, the detector comprises at least one photosensitive element and one or more circuits for processing the output of at least one photosensitive element. The one or more circuits, in some embodiments, comprise filtering circuits and / or amplification circuits.
    In addition, the range of FOV angles over which the scattering signal is measured can comprise any range of FOV angles that are not incompatible with the objectives of the present invention. In some embodiments, the FOV angle range is about 0 mrad to about 60 mrad or about 0 mrad to about 90 mrad.
    In some modalities, sampling a depth of the cloud and measuring the scattering signal are performed with a single device. In some modalities, a device used for sampling a depth of the cloud and measuring the scattering signal is coupled to an aircraft. In some modalities, the sampling of a cloud depth and the measurement of the scattering signal are performed during the flight of the aircraft. A non-limiting device for sampling a depth of the cloud and measuring the scattering signal is disclosed in North American Order Publication No. 2011/0019188, the entirety of which is incorporated herein by reference. Alternatively, sampling the cloud depth and spreading signal measurement can be done with more than one device. If applicable, one or more devices used for sampling the depth of the cloud and measuring the scattering signal can also be used to obtain other information about the cloud, in addition to determining the distribution of the cloud's droplet size and / or LWC.
    In addition, the methods described herein comprise removing a portion of the measured spreading curve and replacing the removed part with an extrapolation of the remaining measured spreading curve to provide an estimated spreading curve. The removal and replacement of a portion of the measured spread curve can be carried out in any form that is not incompatible with the purposes of the present invention. In some embodiments, for example, the measured spread curve is removed at FOV angles below a cut angle. In some embodiments, the cutting angle is the angle of divergence of the beam of electromagnetic radiation. In some embodiments, the cutting angle is the angle of divergence of the beam of electromagnetic radiation. The cutting angle can be varied according to several considerations, including, among others, the amount of direct backscatter and / or diffractive dispersion for removal from the measured spreading curve.
    In some embodiments, the portion removed from the measured scattering curve comprises a signal corresponding to the direct backscatter of electromagnetic radiation [jPdíreto (®)] and the remaining measured scattering curve comprises a corresponding signal from the advanced dispersion of electromághetícã radiation [disp (θTl ” In ^ '^ guma ^^ no'dalidadesr * the part removed from the measured scattering curve comprises a signal corresponding to the direct backscattering of electromagnetic radiation below the cutting angle In some embodiments, the cutting angle is chosen to ensure the removal of all or substantially all of the jPdirect (θ) •
    In addition, extrapolation of the remaining measured scattering curve can be performed in any way that is not incompatible with the objectives of the preDeffinida invention. In some embodiments, extrapolation comprises linear extrapolation. In some embodiments, the extrapolation comprises a parabolic extrapolation or a monotonous extrapolation. In some embodiments, extrapolation comprises a spline function. The extrapolation of the remaining measured scattering curve satisfies the conditions of meeting the remaining dispersion curve at the cutting angle and disappearance at θ = 0.
    Figures 1 to 3 show a non-limiting example of a measured spread curve and the subsequent operation on the measured spread curve to remove a portion of the curve and replace the removed portion with an extrapolation to provide an estimated spread curve. As shown in Figure 1, the scattering curve measured at FOV angles below the cut angle is a composite (triangular line) of the laser beam's backscatter from the sampled droplets (dotted curve) and the advanced diffractive dispersion of the droplets ( solid curve). The scattering curve measured at FOV angles less than the Oõte angle is removed and replaced with a linear extrapolation of the remaining scattering curve measured as shown in Figures 2 and 3, respectively. Linear extrapolation satisfies the bounding conditions of matching or substantially matching the remaining scattering curve measured at the cut angle and the disappearance or substantial disappearance at θ = 0 to complete the estimated scattering curve.
    A first estimated droplet size distribution [n (1) (D)] is determined from the estimated spread curve. The determination of n (1) (D) from the estimated spread curve can be performed in a way that is not inconsistent with the objectives of the present invention. In some embodiments, n (1) (D) is determined from the estimated spread curve using an advanced spread model. In some embodiments, the estimated scattering curve provides a first estimate of the advanced dispersion of electromagnetic radiation [n (1) (D)], and n (1) (D) is determined according to the function:
    where S is a matrix that incorporates the advanced spreading model. Any suitable advanced spreading model can be used. Advanced spreading models suitable for use in some of the modalities described here are described, for example, in Hogan, RJ, "Fast approximate calculation of multiply-scattered deal returns," Applied Optics, 2006, 45 (23), pp. 5984-5992, and Eloranta, EW, "Practical model for the calculation of multiply scattered t ± give returns," Applied Optics, 1998, 37 (12), pp. 2464-2472, whose totalities are hereby incorporated by reference (hereinafter referred to as "Hogan" and "Eloranta", respectively).
    A scattering curve is calculated from n (1) (D) using a direct backscatter model and an advanced scattering model. The provision of a scattering curve calculated from n (1) (D) using a direct backscatter model and the advanced scattering model can be performed in any way that is not incompatible with the objectives of the present invention. In some modalities, the calculated spreading curve is determined according to the function:
    where C is a matrix that incorporates a direct backscattering model and S is a matrix that incorporates the advanced scattering model. Any suitable direct backscatter model and advanced dispersion model can be used. Direct backscattering models suitable for use in some of the modalities described herein are described, for example, in Hogan and Eloranta. In addition, matrix C, in some modalities, includes elements associated with one or more of the divergence of the electromagnetic radiation beam, the focal length of the detector's lenses, and the geometry of the sampled cloud band.
    The scattering curve calculated from n (1) (D) compared to the measured scattering curve in order to determine whether the scattering curve measured within a tolerance
    Deffinida. The comparison of the curves can be managed in any desired way. For example, in some modalities, the comparison is made using the calculated whole spreading curve and the whole measured spreading curve. In some embodiments, only a portion of the calculated spread curve is compared to a portion of the measured spread curve. In some modalities, for example, the comparison of the curves is administered at small angles, such as the angles below the cutting angle.
    In addition, the Deffinida tolerance can comprise any desired tolerance that is not incompatible with the objectives of the present invention. In some embodiments, the Deffinida tolerance comprises an agreement between the calculated spreading curve and the measured spreading curve based on a reduced square x test, as discussed, for example, in John Mandel, The Statistical Analysis of Experimental Data, Dover Publications (1964), the entirety of which is incorporated by reference. The reduced square can be expressed as follows:
    where the k index indicates the FOV range, and (N-2) is the number of degrees of freedom. The number of degrees of freedom is the number of measured Ptotai points (θk) minus the two em adjustment parameters for the droplet distribution. The x computed for (N-2) degrees of freedom is compared to the previously tabulated values of ProbN_2 (X agreement probability). The acceptable level of probability can vary based on the signal-to-noise ratio. In some embodiments, the acceptable probability of settlement is at least about 70 percent. In some embodiments, the acceptable probability of settlement is at least about 80 percent or at least 90 percent. In some embodiments, the acceptable probability of settlement is at least about 95 percent.
    In some modalities, the scattering curve calculated from n (1) (D) follows the scattering curve measured within the Deffinida tolerance. In such embodiments, the method may further comprise determining Deff using n (1) (D) and determining the cloud LWC using Deff as described below.
    In some modalities, the scattering curve calculated from n (1) (D) follows the scattering curve measured within the Deffinida tolerance. In some modalities in which the calculated scattering curve does not follow the scattering curve measured within the Deffinida tolerance, a first estimate of a median droplet volume diameter (DMVD (1>) and shape parameter (p1) is derived from of n (1) (D) The determination of n {1 -) (D) and p1 from n (1) (D) can be performed in a way that is not inconsistent with the objectives of the present invention in the modalities , Dmvd (1) can be of the equation:
    from ac
    dl is a first droplet diameter less than DMVD * 1 'and D2 is a second droplet diameter less than DMVD (1>' In some embodiments, Dl and D2 are small enough that any exponential part of n (1) (D) is considered the same for D1 and D2. Some possible exponential components of droplet size distributions are described, for example, in Shah, AD, "Droplet Size Distribution and Ice shapes," American Institute of Aeronautics and Astronautics (AIAA) International Conference of Aircraft Inflight Icing, May 1996, 1-20, the entirety of which is hereby incorporated by reference.
    The DMVD * 11 value is changed in response to the calculated scattering curve that does not follow the scattering curve measured within the set tolerance in order to provide a second estimate of the median droplet volume diameter (DMVJ / 25). In some modalities, the value of DMVD11 'is increased in order to provide DMVD (2) • In some modalities, the value of DMVD (1) is decreased in order to provide DMvD <2) -For example, in some modalities , the DMVD value (1) can be decreased or increased depending on whether the calculated scattering curve fails to follow the scattering curve measured within the Defined tolerance because it is too high at small scattering angles or too low at small scattering angles.
    A second water droplet size distribution estimated water estimate n (2) (D) is provided using [DMVD (2) 1 and in some embodiments, n (2) (D) is provided according to the equation:
    'where n0 is the concentration of droplet number per droplet diameter unit in m'3µ (1).
    In some modalities, it is not measured. In some modalities, n0 is determined according to the equation:

    The second scattering curve calculated is provided from n <2) (D) using the direct backscattering model and the advanced scattering model, and the second calculated scattering curve is compared with the measured scattering curve in order to determine if the second scattering curve follows the scattering curve measured within the Dθffinida tolerance. The delivery of the second scattering curve calculated from n (2> (D) using a direct backscattering model and advanced spreading model can be done in any desired way. In some embodiments, for example, the second calculated scattering curve is determined according to the function:
    where S and C are as described herein. In addition, the comparison of the calculated second spread curve to the measured spread curve can be performed in any desired manner. For example, in some modalities, the curves can be compared — using — a —periodual — x-square test as described here.
    In some embodiments, the second scattering curve calculated follows the scattering curve measured within the set tolerance, and n (1> (D) represents the distribution of water droplets that have a diameter beyond the maximum detectable droplet diameter. modalities, the method can also comprise the determination of the effective droplet diameter (Deff) using n (1) (D) and the determination of the liquid water content of the cloud using O Deff •
    Alternatively, the calculated second spread curve does not follow the spread curve measured within the Deffinida tolerance, and the method comprises additional steps. In some modalities, for example, the method further comprises changing the DMVD value <2) in response to the calculated spread curve that does not follow the spread curve measured within the adjusted tolerance to provide a third estimate of the median volume diameter of the DMVD droplet (3). In some embodiments, the DMVD value (2) is increased in order to provide DMVD <3> • In some embodiments, the DMVD value (2> is decreased in order to provide DMVD <3) • For example, in In some embodiments, the DMVD value (2) may be decreased or increased depending on whether the calculated spreading curve fails to follow the spreading curve measured within the Defined tolerance because it is too high at small scattering angles or too low at small angles of scattering. DMVD (3) is used in conjunction with p1 to provide a third estimated droplet size distribution [h "(3) (D)]. In some fashion ages 1, n (3i (Erj is ~ determined according to the equation:
    / / where n0 is the concentration of droplet number per droplet diameter unit in m'3p (1). In some modes, n0 is measured. In some modalities, n0 is determined out of 10 according to the equation:

    A third calculated scattering curve is provided from n (3) (D) using the direct backscattering model and the advanced scattering model, and the calculated third scattering curve is compared with the measured scattering curve after 20 determine whether the third scattering curve follows the scattering curve measured within the defined tolerance. The provision of a third scattering curve calculated from n <3) (D) using a direct backscatter model and the advanced scattering model 25 can be performed in any way that is not incompatible with the objectives of the present invention. In some embodiments, for example, the calculated third scattering curve is determined according to the function:
    where S and C are as described herein. In addition, the comparison of the third spread curve calculated to the 735 measured spread curve can be performed in any desired manner. For example, in some modalities, the curves can be compared using a test percentage of x squared as described here.
    In some embodiments, the third scattering curve calculated follows the scattering curve measured within the set tolerance, and n (3> (D) represents the distribution of water droplets that have a diameter beyond the maximum detectable droplet diameter. modalities, the method can also comprise the determination of the effective droplet diameter (Deff) using n (3) (D) and the determination of the liquid water content of the cloud using the Deff, as described below.
    Alternatively, the third scattering curve calculated from n (3) (D) does not follow the scattering curve measured within the Deffinida tolerance, and the method comprises additional steps, including interactive steps. For example, in some embodiments, the methods described here further comprise changing the DMVD * 11 'value in response to a calculated umpteenth spread curve that does not follow the spread curve measured within the Deffinida tolerance to provide an n + 1 estimate. of the median droplet volume diameter [DMVD (n + 1>], where n is an integer greater than 3. In some embodiments, the DMVD (II) value is decreased in order to provide the DMVD (Π + 1) - The umpteenth spread curve calculated, in some modalities, is determined from n (n + 1) (D) using the direct backscattering model and advanced spreading model described here.
    DMvDXn + 1) is used in conjunction with p1 — a — f ± m ~ —de ~ to provide a (n + l) droplet size distribution determined according to the equation:
    where n0 is the concentration of droplet number per droplet diameter unit in m'3p-1. In some modalities, n0 is measured. In some modalities, n0 is determined according to the equation:

    A calculated (n + 1) scattering curve is provided from n (n + 1) using the direct backscattering model and the advanced scattering model, compared with the measured scattering curve in order to determine whether (n + 1) spreading curve follows the spreading curve measured within the Deffinida tolerance. The delivery of the scattering curve (n + 1) from n <n + i;) using the direct backscattering model and the advanced scattering model, in some modalities, is determined according to the function
    where S and C are as described herein. Furthermore, as described herein, the comparison of the calculated (n + 1) spread curve to the measured spread curve can be performed in any desired manner. For example, in some modalities, the curves can be compared using a test percentage of x squared as described here.
    In some embodiments, the calculated (n + 1) scattering curve follows the scattering curve measured within the set tolerance, and n (1 + 1) (D) represents the distribution of water droplets that have a diameter beyond the maximum diameter detectable droplets.
    In some modalities in which the scattering curve calculated from n (n + 1) (p) follows the scattering curve measured within the defined tolerance, the method can also comprise the Deff determination using n (n + i) and determination LWC using Deff.
    In some modalities of the methods described here, Deff is determined according to the equation:
    2 0 where n (D) is the desired estimated droplet size distribution [for example, n (1) (D), n (2) (D), n <3) (D), n (n + 1) (D)].
    In addition, the methods described herein may further comprise determining the cloud LWC using Deff. 25 In some modalities, the LWC is determined according to the equation:
    where the water density is and the optical extinction coefficient. In some modalities, for example, the optical extinction coefficient is measured. In some 35 modalities, the extinction coefficient — optical — is — calculated or inferred.
    Figure 5 illustrates a flow chart of a method according to an embodiment described here.
    It is contemplated that the methods described herein can be at least partially executed and / or applied in computer or processor based systems. In some 5 modalities, computer or processor based systems are part of an operational aircraft system.
    Various embodiments of the invention have been described in compliance with the various objects of the invention. It should be recognized that these modalities are merely illustrative of the principles of the present invention. The numerous modifications and adaptations will be easily evident to those skilled in the art without departing from the spirit and scope of the invention.
    权利要求:
    Claims (31)
    [0001]
    1. Method for determining a water droplet size distribution in a cloud characterized by the fact that it comprises: sampling a depth of the cloud with an electromagnetic radiation beam the electromagnetic radiation beam comprising a beam emitted from a laser; measuring an electromagnetic radiation scattering signal returned from the cloud over a range of field of view angles [ptotai (θ)] in order to provide a measured scattering curve; removing a portion of the measured spread curve; replacing the removed part with an extrapolation of the remaining spreading curve measured to provide an estimated spreading curve; and determining a first estimated droplet size distribution [na) (D)] from the estimated spread curve using an advanced spread model; supply of a scattering curve calculated from n (1) (D) using a direct backscattering model and the advanced spreading model; comparing the calculated spreading curve with the measured spreading curve in order to determine whether the calculated spreading curve follows the measured spreading curve within an adjusted tolerance; determining a first estimate of a median droplet volume diameter (Dwr (1)) from n'1) (D) and determining a first estimate of a shape parameter (pii;) from n! 1 ) (D); and changing the Djwr (1) value in response to the calculated scattering curve that does not follow the scattering curve measured within the adjusted tolerance in order to provide a second estimate of the median droplet volume diameter (Djwr (2)) and using (Djwr (2!) And p (1) to provide a second estimate of the droplet size distribution number 25 (D).
    [0002]
    2. Method, according to claim 1, characterized by the fact that it also comprises the provision of a second scattering curve calculated from n (2) D using the direct backscattering model and the advanced scattering model and comparing the second spreading curve calculated with the measured spreading curve in order to determine whether the second spreading curve follows the measured spreading curve within the adjusted tolerance.
    [0003]
    3. Method, according to claim 2, characterized by the fact that it also includes the change in the value of D «/ D! 2Í in response to the second calculated spreading curve that does not follow the spreading curve measured within the adjusted tolerance for provide a third estimate of the median volume diameter of the droplet (Djwr (3)).
    [0004]
    4. Method, according to claim 3, characterized by the fact that it further comprises the provision of a third droplet size distribution estimate n (3) (D) using DW31 and p (1).
    [0005]
    5. Method, according to claim 4, characterized by the fact that it also comprises the provision of a third scattering curve calculated from n (3) (D) using the direct backscatter model and the advanced spreading model, and comparing the calculated spread curve with the measured spread curve to determine whether the third spread curve follows the measured spread curve within the adjusted tolerance.
    [0006]
    6. Method according to claim 5, characterized by the fact that the part of the measured spreading curve is removed in the field of viewing angles below a cutting angle.
    [0007]
    7. Method, according to claim 6, characterized by the fact that the cutting angle is the angle of divergence of the electromagnetic radiation beam.
    [0008]
    8. Method, according to claim 6, characterized by the fact that the extrapolation of the remaining measured scattering curve satisfies the conditions of meeting the remaining dispersion curve at the cut-off angle at θ = 0.
    [0009]
    9. Method according to claim 6, characterized by the fact that the part removed from the measured scattering curve comprises a signal corresponding to the direct backscattering of electromagnetic radiation [pdireta (θ)] and the remaining measured scattering curve comprises a corresponding signal advanced dispersion of electromagnetic radiation [pdisp (θ)] •
    [0010]
    10. Method according to claim 9, characterized by the fact that the estimated scattering curve provides a first estimate of the advanced dispersion of electromagnetic radiation [p (1) disP (θ)].
    [0011]
    11. Method, according to claim 10, characterized by the fact that n íl} (D) is determined according to the function:
    [0012]
    12. Method, according to claim 11, characterized by the fact that the calculated spreading curve is determined according to the function:
    [0013]
    13. Method, according to claim 11, characterized by the fact that DMB (1) is determined according to the equation:
    [0014]
    14. Method according to claim 11, characterized by the fact that p! Li is determined according to the equation:
    [0015]
    15. Method, according to claim 14, characterized by the fact that the calculated third scattering curve follows the scattering curve measured within the adjusted tolerance, and <3> (D) represents the distribution of water droplets that have a diameter beyond the maximum detectable droplet diameter.
    [0016]
    16. Method, according to claim 15, characterized by the fact that the calculated spreading curve is determined according to the function:
    [0017]
    17. Method, according to claim 16, characterized by the fact that it also comprises the determination of the liquid water content of the cloud using Dθff.
    [0018]
    18. Method according to claim 17, characterized in that it further comprises the determination of the effective droplet diameter (DθffJ using no. 3) (D).
    [0019]
    19. Method, according to claim 5, characterized by the fact that it also includes changing the value of Djwr (n) in response to a calculated umpteenth spread curve that does not follow the spread curve measured within the defined tolerance to provide an estimate n + l of the median droplet volume diameter [Dí® (n + 1!], where n is an integer greater than 3.
    [0020]
    20. Method, according to claim 19, characterized by the fact that it also comprises the provision of an estimated droplet size distribution [nín + 1) (D)] using Djwr (n + 1! And píl}.
    [0021]
    21. Method according to claim 20, characterized in that it further comprises the provision of a scattering curve calculated (n + l) from n (n + 1) (D) using the direct backscatter model and the advanced spreading, the calculated spreading curve (n + l) following the spreading curve measured within the adjusted tolerance.
    [0022]
    22. Method, according to claim 21, characterized by the fact that it comprises the determination of the effective droplet diameter βπ (Dθff) using n (n + 1) (D).
    [0023]
    23. Method according to claim 22, characterized by the fact that it further comprises the determination of the liquid water content of the cloud using Deff.
    [0024]
    24. Method according to claim 21, characterized in that the part of the measured spreading curve is removed in the field of viewing angles below a cutting angle.
    [0025]
    25. Method, according to claim 24, characterized by the fact that the cutting angle is the angle of divergence of the electromagnetic radiation beam.
    [0026]
    26. Method according to claim 25, characterized in that the part removed from the measured scattering curve comprises a signal corresponding to the direct backscattering of electromagnetic radiation [pdirect (θ)] and the remaining measured scattering curve comprises a signal corresponding to the advanced dispersion of electromagnetic radiation [pdiSp (θ)].
    [0027]
    27. Method according to claim 26, characterized by the fact that the estimated scattering curve provides a first estimate of the advanced dispersion of electromagnetic radiation [pD’disp (θ)].
    [0028]
    28. Method according to claim 27, characterized by the fact that níl! (D) is determined according to the function:
    [0029]
    29. Method, according to claim 28, characterized by the fact that the calculated spreading curve is determined according to the function:
    [0030]
    30. Method, according to claim 28, characterized by the fact that DMVD (1) is determined according to the equation:
    [0031]
    31. Method according to claim 30, characterized by the fact that p (1) is determined according to the equation: where Di is a first droplet diameter less than DW1 'and Ü2 is a second droplet diameter less than DW11.
    类似技术:
    公开号 | 公开日 | 专利标题
    BR102012019441B1|2020-10-27|methods for determining cloud water droplet size distributions
    Yan et al.2012|Improving classification accuracy of airborne LiDAR intensity data by geometric calibration and radiometric correction
    Bucher et al.1973|Experiments on light pulse communication and propagation through atmospheric clouds
    BR102012019439A2|2013-11-12|METHOD FOR DETERMINING A CLOUD LIQUID WATER CONTENT
    CN108291863A|2018-07-17|System and method for using light scattering technique to carry out individual particles dimensional measurement
    BR102015028080A2|2016-05-31|system and method
    Gayet et al.2006|Microphysical and optical properties of midlatitude cirrus clouds observed in the southern hemisphere during INCA
    WO2019101247A2|2019-05-31|Laser maritime-visibility monitoring instrument, and method of detecting sea fog
    Shi et al.2015|Measurements of near-ground aerosol backscattering coefficient profile with side-scatter technique
    Braga et al.2014|Investigating the ice water path in convective cloud life cycles to improve passive microwave rainfall retrievals
    Sprung et al.2014|Investigation of optical turbulence in the atmospheric surface layer using scintillometer measurements along a slant path and comparison to ultrasonic anemometer measurements
    Bernard et al.2014|Active and thermal imaging performance under bad weather conditions
    CN101539424B|2010-06-16|Nighttime imaging cloud-height measuring method
    Kochin et al.2021|Examination of Optical Processes in the Atmosphere during Upper-Air Soundings
    Gurvich et al.2013|Lidar sensing of the turbulence based on the backscattering enhancement effect
    Samokhvalov et al.2019|Estimation of microphysical characteristics of contrails by polarization lidar data: theory and experiment
    Desaulniers-Soucy et al.2001|The HYDROP experiment: an empirical method for the determination of the continuum limit in rain
    Bernard et al.2013|Experiments and models of active and thermal imaging under bad weather conditions
    SUN et al.2014|Modeling and simulation of space object optical scattering characteristics using TracePro
    Hu et al.2016|Development and validation of the CALIPSO ocean subsurface data
    Wang et al.2016|Cloud and Aerosol Interaction Observed in SKYNET Hefei Site in China
    Colombi et al.2014|Monte Carlo simulation of multiple scattered light in the atmosphere
    Hainosz2018|POINT CLOUD GENERATION FROM GAUSSIAN DECOMPOSITION OF THE WAVEFORM LASER SIGNAL WITH GENETIC ALGORITHMS Geração de nuvem de pontos a partir da decomposição Gaussiana do sinal LASER com Algoritmos Genéticos
    Chen et al.2019|Laser Attenuation Model in Low Visibility Fog
    Arai et al.2017|Dependence on Solar Phase Angle and Grain Size of the Spectral Reflectance of the Railroad Valley Playa for GOSAT/GOSAT-2 Vicarious Calibration
    同族专利:
    公开号 | 公开日
    BR102012019441A2|2013-11-05|
    JP2013130564A|2013-07-04|
    EP2587277B1|2016-12-07|
    CA2780525C|2020-09-22|
    AU2012203742A1|2013-05-09|
    CA2780525A1|2013-04-25|
    CN103072695B|2016-12-21|
    US8831884B2|2014-09-09|
    US20130103316A1|2013-04-25|
    JP6199542B2|2017-09-20|
    EP2587277A1|2013-05-01|
    CN103072695A|2013-05-01|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US619324A|1899-02-14|Battery-switch |
    US1001918A|1909-07-23|1911-08-29|Friedrich Ludwig Bartelt|Apparatus for aerial propulsion.|
    US4537507A|1982-10-18|1985-08-27|Spectron Development Laboratories, Inc.|Dual beam maximum intensity laser sizing system|
    US5229839A|1989-10-06|1993-07-20|National Aerospace Laboratory Of Science & Technology Agency|Method and apparatus for measuring the size of a single fine particle and the size distribution of fine particles|
    JP2827901B2|1994-05-31|1998-11-25|株式会社島津製作所|Particle size distribution measurement method|
    US5619324A|1995-12-29|1997-04-08|Insitec Measurement Systems|Method for measuring particle size in the presence of multiple scattering|
    GB9818348D0|1998-08-22|1998-10-14|Malvern Instr Ltd|Improvements relating to the measurement of particle size distribution|
    US6819265B2|2002-08-22|2004-11-16|Rosemount Aerospace Inc.|Advanced warning ice detection system for aircraft|
    DE60331231D1|2002-08-26|2010-03-25|Dalsgaard Nielsen Aps|METHOD FOR DETERMINING THE RISK OF IRON DEPOSITION DUE TO PRECIPITATION AND DEVICE FOR CARRYING OUT SAID METHOD|
    JP4185983B2|2003-03-25|2008-11-26|独立行政法人情報通信研究機構|Measuring method of backscatter coefficient depending on water droplets|
    JP2005010046A|2003-06-19|2005-01-13|National Institute Of Information & Communication Technology|Satellite observation method for scatterer|
    US8634072B2|2004-03-06|2014-01-21|Michael Trainer|Methods and apparatus for determining characteristics of particles|
    US20080208511A1|2005-03-07|2008-08-28|Michael Trainer|Methods and apparatus for determining characteristics of particles|
    US8705040B2|2004-03-06|2014-04-22|Michael Trainer|Methods and apparatus for determining particle characteristics by measuring scattered light|
    US20080221814A1|2004-04-10|2008-09-11|Michael Trainer|Methods and apparatus for determining particle characteristics by measuring scattered light|
    JP4595078B2|2005-01-28|2010-12-08|独立行政法人防災科学技術研究所|Apparatus and method for estimating three-dimensional distribution of rainfall intensity and amount of rainwater|
    ITTO20060400A1|2006-05-31|2007-12-01|Lorenzo Battisti|METHOD AND SYSTEM FOR DETECTION OF DANGER OF ICE FORMATION ON AERODYNAMIC SURFACES|
    JP2008164539A|2006-12-29|2008-07-17|Horiba Ltd|Particle size distribution measuring apparatus|
    IT1391180B1|2008-07-07|2011-11-18|Consiglio Nazionale Ricerche|PROCEDURE FOR THE CHARACTERIZATION OF THE ATMOSPHERIC PARTICULATE BY MEANS OF A LIDAR DEVICE FOR ELASTIC AND RETRO-REFLECTION REFLECTION, AND LIDAR SYSTEM FOR IMPLEMENTING THE PROCEDURE|
    US8144325B2|2009-07-23|2012-03-27|Rosemount Aerospace, Inc.|In-flight multiple field of view detector for supercooled airborne water droplets|
    CN101704410A|2009-12-03|2010-05-12|上海交通大学|Nano superhydrophobic surface used for airplane antifreezing and deicing and preparation method thereof|US9658337B2|2013-06-21|2017-05-23|Rosemount Aerospace Inc.|Large droplet detection by statistical fluctuations in lidar backscatter|
    US9041926B2|2013-09-06|2015-05-26|Rosemount Aerospace Inc.|Apparatus and method for in-flight detection of airborne volcanic ash|
    CN105992941B|2013-10-24|2019-04-26|密执安州立大学董事会|Ice and subcooled water detection system|
    WO2015060899A1|2013-10-24|2015-04-30|The Regents Of The University Of Michigan|Ice and supercooled water detection system|
    US9096323B1|2014-04-10|2015-08-04|Rosemount Aerospace Inc.|Window contamination sensor for optical detection systems|
    US9242735B1|2014-08-28|2016-01-26|The Boeing Company|Detecting inflight icing conditions on aircraft|
    US10207810B2|2016-03-21|2019-02-19|Rosemount Aerospace Inc.|Optically detecting cloud metrics using sampled analog measurements of light reflection|
    CN105865100B|2016-04-05|2018-03-16|北京航空航天大学|A kind of exemplar ejection type supercooling drop hits microcosmic observation system|
    CN105891206B|2016-04-05|2018-07-24|北京航空航天大学|A kind of controllable supercooling drop continuously hits microcosmic observation system|
    US10816661B2|2016-06-08|2020-10-27|Rosemount Aerospace Inc.|Airborne ice detector using quasi-optical radar|
    US10725173B2|2016-06-08|2020-07-28|Rosemount Aerospace Inc.|Airborne ice detector using quasi-optical radar|
    US11137519B2|2016-07-21|2021-10-05|Rosemount Aerospace Inc.|Multi-fiber optical sensor for icing|
    CN106501806A|2016-10-31|2017-03-15|北京市人工影响天气办公室|A kind of kind identification method of precipitation particles and device|
    CN106501807A|2016-10-31|2017-03-15|北京市人工影响天气办公室|A kind of hail particle identification method and device|
    US11009338B2|2017-04-04|2021-05-18|Panasonic Intellectual Property Management Co., Ltd.|Liquid droplet measurement method and liquid droplet measurement device, and method and apparatus for manufacturing device|
    US10611488B2|2017-05-05|2020-04-07|Rosemount Aerospace Inc.|Ice accretion boundary locator|
    CN112046761B|2020-08-04|2021-10-15|中国空气动力研究与发展中心计算空气动力研究所|Airplane icing on-line detection method based on statistical test and filtering|
    CN113252281B|2021-06-02|2021-09-21|中国空气动力研究与发展中心低速空气动力研究所|Method for reconstructing size distribution of icing cloud droplets|
    法律状态:
    2013-11-05| B03A| Publication of an application: publication of a patent application or of a certificate of addition of invention|
    2015-12-01| B08F| Application fees: dismissal - article 86 of industrial property law|Free format text: REFERENTE A 3A ANUIDADE. |
    2016-04-05| B08G| Application fees: restoration|
    2018-12-11| B06F| Objections, documents and/or translations needed after an examination request according art. 34 industrial property law|
    2020-05-12| B09A| Decision: intention to grant|
    2020-10-27| B16A| Patent or certificate of addition of invention granted|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 25/07/2012, OBSERVADAS AS CONDICOES LEGAIS. |
    优先权:
    申请号 | 申请日 | 专利标题
    US13/280,877|2011-10-25|
    US13/280,877|US8831884B2|2011-10-25|2011-10-25|Methods of determining water droplet size distributions of clouds|
    [返回顶部]