![]() METHOD FOR TRACING THE HOURLY CONCENTRATION PROFILE OF PARTICULATE MATERIALS IN A ZONE.
专利摘要:
A method for plotting the concentration profile of particles in an area where it is intended to define the number of particulate matter analyzers in the supervised area at 3, to form a concentration matrix (Step 3) as a function of the position of the particle analyzer instruments, to fill in the matrix data with the concentration values obtained by each of the analyzers, to use a Laplace interpolation method (Step 4) based on the concentration data from the analyzers supervising in order to generate concentration values in the matrix that are not obtained by supervising analyzers, and smooth the data (Step 6) in the concentration matrix using a bicubic interpolation, then associate each concentration value in the matrix to a corresponding color value, and plot a concentration profile of particulate matter for the area. 公开号:FR3058221A1 申请号:FR1670765 申请日:2016-12-18 公开日:2018-05-04 发明作者:Zhaogui Liu;Xudong Luan;Jianbo Peng;Suwei Zhang;Xiangfa Zhang;Jun Fang;Xiaopei Xu;Huabing Fang;Yuan Lin 申请人:Jiangsu Skyray Instrument Co Ltd; IPC主号:
专利说明:
TECHNICAL FIELD OF THE INVENTION The present invention relates to a method for plotting hourly concentration profiles of particulate matter in an area, and more specifically discusses the steps of collecting the particle concentration data in the area to form a concentration matrix, filling in the data for the concentration matrix using a Laplace interpolation method, smoothing the data from the concentration matrix using a bicubic interpolation method, and plotting the distribution profiles for the concentration of particulate matter in the area. TECHNOLOGICAL BACKGROUND The hourly particulate matter concentration profile in an area is obtained by installing a number of particulate matter analyzers in the supervised area, using the longitude and latitude coordinates to form the supervised area as a rectangular supervised area. If more precise particle concentration distribution maps are required, a sufficient number of particulate matter analyzers should be installed. Each particulate matter analyzer continuously monitors the concentration of particulate matter at a supervised point and sends the supervised particle concentration to a data processing platform every hour. As the number of particulate matter analyzers may not be regularly distributed across the supervised area, an interpolation algorithm is required to calculate the concentration of particulate matter at a location where the particulate matter analyzer is not installed at using the concentration data obtained by surrounding particulate matter analyzers. OBJECT OF THE INVENTION In order to be able to intuitively and precisely map the hourly concentration distribution of particulate matter in an area, the present invention provides a method for tracing the hourly concentration profile of particulate matter in an area. According to a general characteristic of the invention, the method comprises the following steps: 1. collect particulate matter concentration data in the area to form a concentration matrix, according to which: (1) at least three particulate matter analyzers are installed in the supervised area, and each analyzer must be installed close to the edge of the supervised area and the spacing between the analyzers must be as large as possible; and (2) each particulate matter analyzer continuously monitors the particulate matter at monitoring points, and the average value of the monitored particulate matter concentration is transmitted to a data processing platform via a wireless transmission unit every hour; and (3) the data processing platform initializes the area concentration matrix according to the hourly average of the concentrations of each particulate matter analyzer, and the data processing platform forms a matrix covering the area monitored according to the longitude and latitude coordinates of the particulate matter analyzers installed and the value of the precision of the points of the pattern, then the initial values of concentration in the matrix are fixed at 0, and according to the longitude and latitude coordinates of each analyzer particulate matter, the hourly particle concentration values selected by the data processing platform are entered into the matrix. 2. fill in the data of the concentration matrix by a Laplace interpolation method, according to which: (1) the initial value of 0 in the concentration matrix is fixed at 1 .e99; and (2) the Laplace interpolation method is used to calculate the value of the point which has the value 1 .e99. 3. smooth the data of the concentration matrix by a bicubic interpolation method, according to which the values lying in the matrix from the third row to the penultimate row and from the second column to in the antepenultimate column are recalculated by a bicubic interpolation. 4. draw the concentration distribution profiles of the area comprising the following steps: ίο (1) associate a displayed color according to the concentration interval; (2) create a new image, and define the height and width of the image as the number of rows and the number of columns of the matrix; (3) depending on the concentration value in the concentration matrix, the pixel of the image at the corresponding position is colored, the displayed color corresponding to the concentration. For example, the particulate matter concentration data corresponds to the hourly average value of the particulate matter concentrations obtained by the particulate matter analyzers installed in the supervised area and the type of particulate matter is classified in the group PM2.5, PM10, TSP or other. This method has the advantage of reducing the number of particulate matter analyzers and of increasing the measurement area adequately. The traced distribution profile is more intuitive and precise. BRIEF DESCRIPTION OF THE FIGURES Figure 1 is a flow diagram of the present invention. Figure 2 is a diagram obtained using the present invention. DESCRIPTION OF EMBODIMENTS OF THE INVENTION In the following description, the acronyms PM2.5, PM10, TSP well known to those skilled in the art are used to designate respectively the English terms Particulate Matter 2.5, Particulate Matter 10 and Total Suspended Particulates. These English terms mean particulate matter less than 2.5 microns, particulate matter less than 10 microns, and total suspended particles, respectively. The present invention discusses a method for plotting hourly particulate matter concentration profiles in an area, the method starting with collecting the particulate matter concentration in the area to form a concentration matrix, filling in the matrix data concentration using a Laplace interpolation method, smoothing the data from the concentration matrix using a bicubic interpolation method, and plotting the concentration distribution profiles of the area. The embodiment of the present invention will be described in detail below with reference to the figures. Step 1: Install particulate matter analyzers. Four PM2.5 analyzers are installed in the supervised area, and preferably placed at the four corners of the supervised area as much as possible. Step 2: The particulate matter analyzer sends data to the data processing platform. The four particulate matter analyzers continuously monitor PM2.5 particulate matter concentrations at the supervised point, and average PM2.5 particulate matter concentrations are transmitted hourly to the data processing platform via the wireless transmission unit called also dtu acronym for data transmission unit according to a term well known to those skilled in the art meaning data transmission unit. Step 3: Form the original concentration matrix. First, we obtain the coordinates of minimum longitude and maximum longitude of the supervised area, then we obtain the coordinates of minimum latitude and maximum latitude of the supervised area. The longitude interval from minimum longitude to maximum longitude is regularly divided into 800 parts, and the latitude interval from minimum latitude to maximum latitude is regularly divided into 600 parts, so the size of the original concentration matrix is 800 x 600. And, in accordance with the latitude and longitude coordinates of the four particulate matter analyzers, the hourly average concentration values of the particulate matter analyzers are entered at their corresponding position in the matrix. Step 4: Fill in the data of the concentration matrix by a Laplace interpolation method. First, the concentration values which were not obtained by the particulate matter analyzers in the original concentration matrix are fixed at l.e99, then the concentration values of the positions whose concentration value has a value of l.e99 are recalculated by the Laplace interpolation method. Step 5: Initialize the results matrix. A matrix of real numbers having the same size as the original concentration matrix is defined, and the initial values are defined as the coordinate values corresponding to the data in the concentration matrix. Step 6: Smoothing the data of the concentration matrix using a bicubic interpolation from the third row to the penultimate row and from the second column to the antepenultimate column. The data at the position of row i and column j is obtained by following the following six steps: ® Yo = Yij © Yi = Y (i + i) j ® Υς = Y (î + i) o + i) © y 3 = Yio + D ® t = i / c, u = i / r, in which r and c are the total number of rows and columns, respectively © Y (ij ') = (1 - 0 (1 ~ u) y 0 + t (l - u) yi + tuy 2 + (1 t) uy 3 Step 7: Associate the display colors in correspondence with the concentrations. When the concentration is less than or equal to 35, the defined color is green; when the concentration is less than or equal to 75, the defined color is yellow; when the concentration is less than or equal to 115, the defined color is orange; when the concentration is less than or equal to 150, the defined color is red; when the concentration is less than or equal to 250, the defined color is purple; when the concentration is less than or equal to 500, the defined color is purple brown; when the concentration is greater than 500, the defined color is black. Step 8: Initialization to draw an image. A new io image is created having a width defined as the number of columns in the result concentration matrix and having a height defined as the number of rows in the result concentration matrix. Step 9: Color each pixel of the image. Depending on the concentration value in the concentration matrix, the pixel of the image at the corresponding position is colored, the displayed color corresponding to the concentration.
权利要求:
Claims (2) [1" id="c-fr-0001] 1. Method for drawing the hourly concentration profile of particulate matter in an area, characterized in that it comprises the following steps: 5 -install particulate matter analyzers in the area (Step 1); - sending of particulate matter concentration data in the area by the particulate matter analyzers (Step 2); -collect the particulate matter concentration data in the area to form a concentration matrix (Step 3); îo -fill the data of the concentration matrix (Step 4) with a Laplace interpolation method; - smooth the data of the concentration matrix (Step 6) by a bicubic interpolation method; and - draw the concentration distribution profiles (Steps 7, 8, 9) of the zone. 2. Method according to claim 1, in which the particulate matter concentration data correspond to the hourly average value of the particulate matter concentrations obtained by the particulate matter analyzers installed in the area. 20 supervised and the type of particulate matter is classified in group PM2.5, PM10, TSP. 3. Method according to claim 1, wherein the step of collecting the concentration data of particulate matter in the area to form the concentration matrix (Steps 2, 3) is characterized in that 25 that: (1) at least three particulate matter analyzers are installed in the supervised area, and each analyzer must be installed close to the edge of the supervised area and the spacing between the analyzers must be as large as possible; and (2) each particulate matter analyzer continuously monitors the particulate matter at monitoring points, and the average value of the monitored particulate matter concentration is transmitted to a data processing platform via a transmission unit 5 wireless every hour; and (3) the data processing platform initializes the area concentration matrix as a function of the hourly average of the concentrations of each particulate matter analyzer, and the data processing platform forms a matrix covering the area supervised as a function longitude and latitude coordinates of the particulate matter analyzers installed and the value of the precision of the points of the pattern, then the initial values of concentration in the matrix are set to 0, and according to the longitude and latitude coordinates of each analyzer of particulate matter, the values of 15 hourly concentration of particles selected by the data processing platform are introduced into the matrix. 4. Method according to claim 1, in which the step of filling in the data of the concentration matrix (Step 4) by a Laplace interpolation method is characterized in that: 20 (1) the initial value of 0 in the concentration matrix is fixed at 1 .e99; and (2) the Laplace interpolation method is used to calculate the value of the point which has the value l.e99. 5. Method according to claim 1, in which the step of smoothing the 25 data from the concentration matrix (Step 6) by a bicubic interpolation method is characterized in that the values lying in the matrix from the third row to the penultimate row and from the second column up to the antepenultimate column are recalculated by a bicubic interpolation. 6. Method according to claim 1, in which the step of tracing the concentration distribution profiles (Steps 7, 8, 9) of the zone is characterized in that it comprises the following steps: (1) associate a displayed color according to a concentration interval; [2" id="c-fr-0002] (2) create a new image, and define the height and width of the image as the number of rows and the number of columns in the 5 matrix; and (3) depending on the concentration value in the concentration matrix, the pixel of the image at the corresponding position is colored, the displayed color corresponding to the concentration. 3058; 1/2 Start X Step 1 Install particulate matter analyzers Ψ 2nd step - The particulate matter analyzer sends data to the data processing platform ψ Step 3 - Form the original concentration matrix Ψ Step 4 - Fill in the data of the concentration matrix by a Laplace interpolation method Ψ Step 5 - Initialize the results matrix i Start at row r = 3 of the data matrix Start at column c = 2 of the data matrix ψ Smoothing of concentration data by a method bicubic interpolation Ψ Column c - Column c + 1 Column c = before —-—- _ ^ on last column ____—-- YES Row r = Row r + 1 'f Step 7 Associate display colors in correspondence with concentrations Ψ Step 8 Initialization to draw an image ψ Step 9 Color each pixel of the image I- ’-1 End
类似技术:
公开号 | 公开日 | 专利标题 FR3058221A1|2018-05-04|METHOD FOR TRACING THE HOURLY CONCENTRATION PROFILE OF PARTICULATE MATERIALS IN A ZONE. CN104978748B|2018-01-12|A kind of liquid crystal display defect inspection method based on local pixel value US10599944B2|2020-03-24|Visual feedback for inspection algorithms and filters CN105260713A|2016-01-20|Method and device for detecting lane line CN103676242A|2014-03-26|Color film substrate repairing method CN103065124B|2016-04-06|A kind of cigarette detection method, device and fire detection device CN104165753B|2017-02-01|Device and method for detecting transparent display screen DE102012107287A1|2013-02-21|System and method for identifying errors in a material EP3174037A1|2017-05-31|Image display method and display device CN102765249A|2012-11-07|Machine vision detection method based on four-colour printed matter registration detection marks CN107239742A|2017-10-10|A kind of gauge pointer scale value calculating method CN109522788B|2020-11-06|City range extraction method and device based on random forest classification algorithm and electronic equipment CN109613002A|2019-04-12|A kind of glass defect detection method, apparatus and storage medium CN105259909A|2016-01-20|Vegetation data acquisition method and acquisition apparatus based on unmanned aerial vehicle CN109635629A|2019-04-16|A kind of bus platform crowd density detection method and device based on deep learning CN106503740A|2017-03-15|Picture classification method and device CN103700027A|2014-04-02|Method for achieving multi-dimensional bidirectional free-matching visual display of electric power data and graphics CN104281850A|2015-01-14|Character area identification method and device CN205121343U|2016-03-30|Vegetation data collection system and unmanned vehicles based on unmanned vehicles CN104361341A|2015-02-18|Method of analyzing crop growth image based on embedded type equipment CN109426013B|2020-06-23|Method and device for analyzing and detecting and repairing defects of color film substrate Kobayashi et al.2013|Colored mosaic matrix: Visualization technique for high-dimensional data CN110599552A|2019-12-20|pH test paper detection method based on computer vision CN104835132A|2015-08-12|Road condition image fast point inspection method and equipment thereof US6815233B1|2004-11-09|Method of simultaneous display of die and wafer characterization in integrated circuit technology development
同族专利:
公开号 | 公开日 CN106528997A|2017-03-22| CN106528997B|2020-08-14|
引用文献:
公开号 | 申请日 | 公开日 | 申请人 | 专利标题 CN102254330B|2010-07-29|2013-01-30|山东大学|Image processing-based method for visualization of air pollution data| CN101900662B|2010-08-02|2012-11-07|山东大学|Method for visualizing regional pollutant concentration based on particle system| WO2012165991A1|2011-05-31|2012-12-06|Schlumberger Holdings Limited|Method for determination of spatial distribution and concentration of contrast components in a porous and/or heterogeneous sample| CN102353622B|2011-07-01|2013-03-27|黑龙江科技学院|Monitoring and measuring method for dust concentration in working faces in underground coal mine| CN103674794B|2013-12-16|2016-06-01|中国科学院遥感与数字地球研究所|Remote sensing monitoring near surface fine particle quality concentration PM2.5Multiple regression procedure| CN104483248B|2014-12-30|2017-04-19|中科宇图天下科技有限公司|Regional particulate matter stereoscopic monitoring method| CN105678085B|2016-01-12|2019-01-01|环境保护部卫星环境应用中心|A kind of PM2.5The evaluation method and system of concentration|CN110058548A|2019-04-18|2019-07-26|深圳市赛为智能股份有限公司|Reduce the method, apparatus and computer equipment of Environments in Urban Open Spaces particle concentration| CN111125206B|2019-12-26|2020-11-17|中科三清科技有限公司|Air pollutant data processing method and device| CN111912755B|2020-08-07|2021-08-10|山东中煤工矿物资集团有限公司|Mining dust concentration sensor, sensor system and method|
法律状态:
2018-01-02| PLFP| Fee payment|Year of fee payment: 2 | 2018-12-31| PLFP| Fee payment|Year of fee payment: 3 | 2019-12-20| PLSC| Search report ready|Effective date: 20191220 | 2019-12-30| PLFP| Fee payment|Year of fee payment: 4 | 2021-03-05| RX| Complete rejection|Effective date: 20210127 |
优先权:
[返回顶部]
申请号 | 申请日 | 专利标题 CN2016109592761|2016-10-28| CN201610959276.1A|CN106528997B|2016-10-28|2016-10-28|Method for drawing regional particle hourly concentration distribution map| 相关专利
Sulfonates, polymers, resist compositions and patterning process
Washing machine
Washing machine
Device for fixture finishing and tension adjusting of membrane
Structure for Equipping Band in a Plane Cathode Ray Tube
Process for preparation of 7 alpha-carboxyl 9, 11-epoxy steroids and intermediates useful therein an
国家/地区
|