CN110889199B - A layout optimization method for an on-line detector of atmospheric particulate matter concentration in a port - Google Patents

A layout optimization method for an on-line detector of atmospheric particulate matter concentration in a port Download PDF

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CN110889199B
CN110889199B CN201911063520.6A CN201911063520A CN110889199B CN 110889199 B CN110889199 B CN 110889199B CN 201911063520 A CN201911063520 A CN 201911063520A CN 110889199 B CN110889199 B CN 110889199B
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封学军
庄凯
刁昶皓
周云鹏
张艳
沈金星
林桐
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Abstract

The invention discloses a layout optimization method of a port atmospheric particulate matter concentration online detector, which can be used for online real-time continuous detection of concentrations of PM2.5, PM10 and TSP in a port atmospheric environment. The method comprises the following steps: carrying out port plane grid division; detecting the concentration of atmospheric particulate matters in a vertical space of a port grid; constructing a worst inferior curved surface of the port space with the most serious particulate pollution; optimizing the space aggregation of the port grids; and selecting the inferior curved surface of one mesh in each determined aggregation mesh set as an optimal layout scheme of the on-line detector. According to the correlation between the particulate matter concentrations in the adjacent grid spaces, the invention carries out aggregation optimization on the grids of the port, comprehensively considers the spatial relationship of different grids on the worst-case curved surface with the most particulate matter pollution, and determines the optimal layout position of the on-line detector. The detection result effectiveness can be ensured while the distribution is reduced, and the input and output benefits of port pollution monitoring are improved.

Description

一种港口大气颗粒物浓度在线检测器的布局优化方法A layout optimization method for an online detector of atmospheric particulate matter concentration in a port

技术领域technical field

本发明涉及一种港口大气颗粒物浓度在线检测器的布局优化方法，主要考虑港口中的陆域范围，不考虑水域范围内的大气颗粒物浓度检测，属于交通环境污染与防治领域。The invention relates to a layout optimization method of an on-line detector for the concentration of atmospheric particulate matter in a port, which mainly considers the land area in the port and does not consider the detection of the concentration of atmospheric particulate matter in the water area, and belongs to the field of traffic environment pollution and prevention.

背景技术Background technique

对在线检测器的合理布设是对大气污染进行有效检测的基础，是正确反映港口大气环境状况的前提，是提升港口大气环境检测结果可靠性的重要途径。由于颗粒物来源的复杂性、港口功能区位布置的多样性、作业机械及作业工艺的特殊性等影响因素，使得港口空间内大气污染情况复杂且多变。对于在线检测器的布设来说，当点位选择不恰当时，检测数据无法充分体现港口实际的大气污染情况，甚至会影响港口粉尘污染治理方案的选择。The reasonable arrangement of online detectors is the basis for effective detection of air pollution, the premise of correctly reflecting the atmospheric environment of the port, and an important way to improve the reliability of the detection results of the port atmospheric environment. Due to the complexity of the source of particulate matter, the diversity of port functional location layout, the particularity of operating machinery and operating technology and other influencing factors, the air pollution situation in the port space is complex and changeable. For the layout of online detectors, when the point selection is not appropriate, the detection data cannot fully reflect the actual air pollution situation of the port, and even affect the selection of the port dust pollution control plan.

经过发明人长期研究发现，利用无人机检测港口三维空间内的颗粒物浓度数据，可以得到能反映港口大气环境真实污染状况的在线检测器布置点位，有效检测到港区空间内整体的污染状况，避免以往地面检测的不全面性，提高港口在线检测设备的投入产出效益。After long-term research by the inventor, it is found that the use of drones to detect the particle concentration data in the three-dimensional space of the port can obtain the location of the online detector that can reflect the real pollution status of the atmospheric environment of the port, and effectively detect the overall pollution status in the port space. , to avoid the incompleteness of previous ground detection and improve the input-output efficiency of port online detection equipment.

发明内容SUMMARY OF THE INVENTION

本发明的目的是提供一种港口环境颗粒物浓度在线检测器的布局优化方法，使检测结果能充分体现港口实际大气污染情况的在线实时连续检测港口大气环境中PM2.5、PM10以及TSP的浓度。The purpose of the present invention is to provide a layout optimization method of an on-line detector for the concentration of particulate matter in a port environment, so that the detection results can fully reflect the actual atmospheric pollution situation of the port and continuously detect the concentrations of PM2.5, PM10 and TSP in the port atmospheric environment in real time.

为解决上述技术问题，本发明采用的技术方案是：In order to solve the above-mentioned technical problems, the technical scheme adopted in the present invention is:

一种港口大气颗粒物浓度在线检测器的布局优化方法，其特征在于，步骤如下：A method for optimizing the layout of an on-line detector of atmospheric particulate matter concentration in a port, characterized in that the steps are as follows:

1)港口平面网格划分：根据港口总平面布局图，对港口平面进行网格划分；1) Port plane grid division: According to the port general plane layout, the port plane is divided into grids;

2)港口网格垂直空间大气颗粒物浓度检测：利用颗粒物浓度检测器，对每个网格中心位置由地面至垂直上方H米高度空间内的L个不同高度位置的颗粒物浓度进行检测，得到网格上方垂直空间内L个颗粒物浓度数据，L≥2；2) Detection of atmospheric particulate matter concentration in the vertical space of port grid: use the particle concentration detector to detect the concentration of particulate matter at L different height positions in the space from the ground to the vertical above H meters from the center of each grid, and obtain the grid L particle concentration data in the vertical space above, L≥2;

3)港口空间颗粒物污染最严重的劣曲面构建：确定每一个网格中颗粒物污染最严重的高度，将所有网格颗粒物污染严重度最大的平面衔接起来，形成港口空间中颗粒物污染最严重的劣曲面；3) Construction of inferior surfaces with the most serious particle pollution in the port space: determine the height of the most serious particle pollution in each grid, and connect the planes with the most serious particle pollution in all grids to form the most serious particle pollution in the port space. surface;

4)港口网格的空间聚合优化：根据港口不同网格垂直空间内检测的颗粒物浓度数据进行关联度分析，确定聚合的网格集合；4) Spatial aggregation optimization of port grids: carry out correlation analysis according to the particle concentration data detected in the vertical space of different grids in the port, and determine the aggregated grid set;

5)确定在线检测器的最优布局方案：在确定的每个聚合网格集合中，选择其中一个网格的劣曲面作为布置在线检测器的最优布局方案。5) Determine the optimal layout scheme of the online detector: in each determined aggregated grid set, select the inferior surface of one of the grids as the optimal layout scheme for arranging the online detector.

所述步骤5)中确定在线检测器最优布局方案的方法为：The method for determining the optimal layout scheme of the online detector in the step 5) is:

51)在港口空间颗粒物浓度最高的劣曲面上，确定每个聚合网格集合的中心点的坐标(Xc(On),Yc(On))，式中On为第n个聚合网格集合，n＝1,2,…,N，N为聚合网格集合总数；51) On the inferior surface with the highest particle concentration in the port space, determine the coordinates (X c (O n ), Y c (O n )) of the center point of each aggregated grid set, where O n is the nth aggregate Grid set, n=1,2,...,N, N is the total number of aggregated grid sets;

52)分别计算每个聚合网格集合On中所有个网格与聚合网格集合On中心点坐标(Xc(On),Yc(On))的距离

Figure GDA0003795687230000021
为：52) Calculate the distances of all grids in each aggregate grid set O n and the coordinates (X c (O n ), Y c (O n )) of the center point of the aggregate grid set O n respectively
Figure GDA0003795687230000021
for:

Figure GDA0003795687230000022
Figure GDA0003795687230000022

式中，an＝1,2,…,An；An为第n个聚合网格集合On包含的网格数；In the formula, an =1,2,...,An; An is the number of grids included in the nth aggregate grid set O n ;

53)确定每个聚合网格集合On中所有An个网格与网格集合On中心点坐标(Xc(On),Yc(On))的距离的最大值

Figure GDA0003795687230000023
为：53) Determine the maximum value of the distances between all A n grids in each aggregated grid set O n and the center point coordinates (X c (O n ), Y c (O n )) of the grid set O n
Figure GDA0003795687230000023
for:

Figure GDA0003795687230000024
Figure GDA0003795687230000024

54)确定每个聚合网格集合On中每一个网格an上方垂直空间中劣曲面上颗粒物污染严重度修正值

Figure GDA0003795687230000025
54) Determine the correction value of particle pollution severity on the inferior surface in the vertical space above each grid an in each aggregated grid set O n
Figure GDA0003795687230000025

55)将聚合网格集合中所有网格中颗粒物污染严重度修正值最大的网格作为在线检测器的布置点位。55) The grid with the largest particle pollution severity correction value among all grids in the aggregated grid set is used as the placement point of the online detector.

L＝H/b，其中b为高度间隔。L=H/b, where b is the height interval.

采用无人机进行步骤2)的港口网格垂直空间大气颗粒物浓度检测。UAV is used to detect the concentration of atmospheric particulate matter in the vertical space of the port grid in step 2).

无人机检测时，根据港口历史气象信息，综合考虑风速、温度和湿度指标，确定无人机的最佳检测日期。When the drone is detected, the best detection date of the drone is determined based on the historical meteorological information of the port, comprehensively considering the wind speed, temperature and humidity indicators.

所述无人机的最佳检测日期的确定方法如下：The method for determining the best detection date of the UAV is as follows:

21)获取港口的历史气象数据，计算当地过去K年中每周的平均风速、平均温度和平均湿度数据；21) Obtain the historical meteorological data of the port, and calculate the weekly average wind speed, average temperature and average humidity data in the past K years;

22)根据每周的平均风速、温度和湿度数据，构建每周的平均风速集合、平均温度集合和平均湿度集合；22) According to the weekly average wind speed, temperature and humidity data, construct the weekly average wind speed set, the average temperature set and the average humidity set;

23)测算每周的风速指数fs(i)、温度指数ft(i)和湿度指数fh(i)，23) Calculate the weekly wind speed index f s (i), temperature index f t (i) and humidity index f h (i),

Figure GDA0003795687230000031
Figure GDA0003795687230000031

其中，MinS(i)为每周的平均风速集合中风速最小的值，MaxS(i)为每周的平均风速集合中风速最大的值，MinT(i)为每周的平均温度集合中温度最小的值，MaxT(i)为每周的平均温度集合中温度最大的值，MinH(i)为每周的平均湿度集合中湿度最小的值，MaxS(i)为每周的平均湿度集合中湿度最大的值；Among them, MinS(i) is the minimum wind speed in the weekly average wind speed set, MaxS(i) is the maximum wind speed in the weekly average wind speed set, MinT(i) is the minimum temperature in the weekly average temperature set , MaxT(i) is the maximum temperature value in the weekly average temperature set, MinH(i) is the minimum humidity value in the weekly average humidity set, MaxS(i) is the weekly average humidity set humidity in the set maximum value;

24)根据风速指数、温度指数和湿度指数，确定Bt(i)对应的第i周无人机的最佳检测周，24) According to the wind speed index, temperature index and humidity index, determine the best detection week of the drone in the i-th week corresponding to B t (i),

Figure GDA0003795687230000032
Figure GDA0003795687230000032

其中，Bt(i)为综合考虑风速、温度和湿度后的最佳检测气象条件，MaxV(i)为全年52周综合考虑风速指数、温度指数和湿度指数的最大值，λ1,λ2,λ3为权重系数，且λ1+λ2+λ3＝1；Among them, B t (i) is the best detected meteorological condition after comprehensive consideration of wind speed, temperature and humidity, MaxV(i) is the maximum value of wind speed index, temperature index and humidity index comprehensively considered in 52 weeks of the year, λ 1 , λ 2 , λ 3 is the weight coefficient, and λ 1 +λ 2 +λ 3 =1;

25)在最佳检测周中选择一天作为无人机检测日期。25) Select a day in the best detection week as the drone detection date.

步骤1)中所述港口平面网格划分的方法如下：The method of port plane meshing described in step 1) is as follows:

11)获取港区的总平面布局图，确定总平面的边界点的经纬度坐标；11) Obtain the general plan layout of the port area, and determine the latitude and longitude coordinates of the boundary points of the general plan;

12)在港区总平面布局图中，以纬度最低点设置X轴，以经度最低点设置Y轴，结合港区总平面尺寸数据建立港区总平面布局图的平面直角坐标系；12) In the general plan layout of the port area, the X-axis is set with the lowest point of latitude, the Y-axis is set with the lowest point of longitude, and the plane rectangular coordinate system of the general plan layout of the port area is established in combination with the general plane size data of the port area;

13)在构建的平面直角坐标系中，分别在横坐标和纵坐标上以宽度w为间隔将港口划分为M个网格，并对港区总平面内所有的网格从最接近X轴零点的位置为编号为1，其他依次以顺时针螺旋法则进行编号，直到所有网格都有专门的编号m，m＝1,2,…,M；其中顺时针螺旋法则指，从编号1的网格开始沿Y轴方向对相邻网格进行编号直到可以编号的网格边界后，以顺时针方向转换为X轴方向对相邻网格进行编号直到可以编号的网格边界后，以顺时针方向转换为Y轴方向进行同样的编号直到遍历所有的网格均编号完成；13) In the constructed plane rectangular coordinate system, the port is divided into M grids on the abscissa and the ordinate with the width w as the interval, and all grids in the general plane of the port area are divided into M grids from the nearest zero point of the X axis. The position of the grid is numbered 1, and the others are numbered according to the clockwise spiral rule, until all grids have a special number m, m=1,2,...,M; where the clockwise spiral rule refers to the grid from the number 1. The grid starts to number adjacent grids in the Y-axis direction until the numbered grid boundary, and converts clockwise to the X-axis direction to number the adjacent grids until the numberable grid boundary, then clockwise The direction is converted to the Y-axis direction and the same number is performed until all the grids are traversed and numbered;

14)确定每个网格的中心点在直角坐标系中的位置，记为(Xc(m),Yc(m))。14) Determine the position of the center point of each grid in the Cartesian coordinate system, denoted as (X c (m), Y c (m)).

所述步骤2)中港口网格垂直空间大气颗粒物浓度检测的方法为：The method for detecting the concentration of atmospheric particulate matter in the vertical space of the port grid in the step 2) is:

21)利用搭载颗粒物浓度检测器的无人机，对每个网格中心位置由地面至垂直上方H米高度空间内每隔b米位置检测的PM2.5的浓度为PM2.5(m,l,d)，PM10的浓度为PM10(m,l,d)，TSP的浓度为TSP(m,l,d)。其中，l为由地面至垂直上方H米高度空间内的检测位置编号，本发明中H米高度范围内每次检测的高度间隔为b米，因此从地面上方b米位置开始l＝1,2,…,L；d为无人机检测次数的编号，d＝1,2,…,D，D为总检测次数；PM2.5(m,l,d)是指在网格m的中心高度编号为l位置，无人机在第d次飞行检测的动力学当量直径小于等于2.5微米的颗粒物浓度；PM10(m,l,d)是指在网格m的中心高度编号为l位置，无人机在第d次飞行检测的动力学当量直径小于等于10微米的颗粒物浓度；TSP(m,l,d)是指在网格m的中心高度编号为l位置，无人机在第d次飞行检测的动力学当量直径小于等于100微米的颗粒物浓度；21) Using an unmanned aerial vehicle equipped with a particle concentration detector, the concentration of PM2.5 detected at every b-meter position from the ground to the vertical upper H-meter height space at the center of each grid is PM2.5 (m,l, d), the concentration of PM10 is PM10 (m,l,d), and the concentration of TSP is TSP(m,l,d). Among them, l is the detection position number in the space from the ground to the vertical height of H meters. In the present invention, the height interval of each detection within the height of H meters is b meters. Therefore, starting from the position of b meters above the ground, l=1, 2 ,…,L; d is the number of the detection times of the drone, d=1,2,…,D, D is the total number of detections; PM 2.5 (m,l,d) refers to the height number at the center of the grid m is the position l, the concentration of particles with a kinetic equivalent diameter less than or equal to 2.5 microns detected by the UAV in the d-th flight; PM 10 (m,l,d) refers to the position number l at the center of the grid m, no The concentration of particles with a dynamic equivalent diameter of less than or equal to 10 microns detected by the man-machine in the d-th flight; TSP(m,l,d) refers to the position numbered at the center height of the grid m, and the drone is in the d-th flight. The concentration of particles whose kinetic equivalent diameter is less than or equal to 100 microns in flight detection;

22)根据每个网格垂直空间中利用无人机检测的颗粒物浓度数据，得到不同高度的PM2.5、PM10和TSP的平均浓度；不同高度检测的PM2.5的平均浓度为

Figure GDA0003795687230000041
PM10的平均浓度为
Figure GDA0003795687230000042
TSP的平均浓度为
Figure GDA0003795687230000043
22) According to the particle concentration data detected by drones in the vertical space of each grid, the average concentrations of PM2.5, PM10 and TSP at different heights are obtained; the average concentrations of PM2.5 detected at different heights are
Figure GDA0003795687230000041
The average concentration of PM10 is
Figure GDA0003795687230000042
The average concentration of TSP is
Figure GDA0003795687230000043

23)确定不同网格空间的颗粒物浓度数据集合，PM2.5的浓度集合为

Figure GDA0003795687230000044
PM10的浓度集合为
Figure GDA0003795687230000045
TSP的浓度集合为
Figure GDA0003795687230000046
23) Determine the particle concentration data set in different grid spaces, the concentration set of PM2.5 is
Figure GDA0003795687230000044
The concentration set of PM10 is
Figure GDA0003795687230000045
The concentration set of TSP is
Figure GDA0003795687230000046

所述步骤3)中构建颗粒物浓度最劣曲面的方法为：The method for constructing the worst surface of particle concentration in the step 3) is:

31)确定港口不同网格上方空间颗粒物浓度的最大值并构建颗粒物浓度最高的集合Z(m)：31) Determine the maximum value of the particle concentration in the space above the different grids of the port and construct the set Z(m) with the highest particle concentration:

垂直上方空间中PM2.5的浓度最高值

Figure GDA0003795687230000047
PM10的浓度最高值
Figure GDA0003795687230000048
TSP的浓度最高值TSPmax(m)＝MaxTSP(M)；The highest concentration of PM2.5 in the space above the vertical
Figure GDA0003795687230000047
The highest concentration of PM10
Figure GDA0003795687230000048
The highest concentration of TSP TSP max (m) = MaxTSP (M);

构建网格m处颗粒物浓度最高的集合

Figure GDA0003795687230000049
Build the set with the highest particle concentration at grid m
Figure GDA0003795687230000049

32)测算每个网格颗粒物浓度指数：32) Calculate the particle concentration index of each grid:

PM2.5的浓度指数fPM2.5(m,l)，PM10的浓度指数为fPM10(m,l)，TSP的浓度指数为fTSP(m,l)分别为：The concentration index of PM2.5 is f PM2.5 (m,l), the concentration index of PM10 is f PM10 (m,l), and the concentration index of TSP is f TSP (m,l), respectively:

Figure GDA0003795687230000051
Figure GDA0003795687230000051

33)确定每个网格浓度指数的最大值：33) Determine the maximum value of each grid concentration index:

PM2.5浓度指数的最大值

Figure GDA0003795687230000052
PM10浓度指数的最大值
Figure GDA0003795687230000053
TSP浓度指数的最大值
Figure GDA0003795687230000054
Maximum value of PM2.5 concentration index
Figure GDA0003795687230000052
Maximum value of PM10 concentration index
Figure GDA0003795687230000053
Maximum value of TSP concentration index
Figure GDA0003795687230000054

Figure GDA0003795687230000055
Figure GDA0003795687230000055

式中，Max[]均表示向量中的最大值；In the formula, Max[] all represent the maximum value in the vector;

34)确定每个网格颗粒物浓度指数的最大值：34) Determine the maximum value of the particle concentration index for each grid:

颗粒物浓度指数的最大值为：

Figure GDA0003795687230000056
The maximum value of the particle concentration index is:
Figure GDA0003795687230000056

35)计算每个网格颗粒物浓度系数与浓度系数最大值之间的关联系数：35) Calculate the correlation coefficient between each grid particle concentration coefficient and the maximum concentration coefficient:

PM2.5、PM10以及TSP的浓度系数与浓度系数最大值的关联系数如下：The correlation coefficient between the concentration coefficients of PM2.5, PM10 and TSP and the maximum concentration coefficients is as follows:

Figure GDA0003795687230000057
Figure GDA0003795687230000057

36)根据每个网格的颗粒物浓度数据的关联系数确定不同高度的污染严重度，并得到每个网格的颗粒物污染严重度集合：36) Determine the pollution severity at different heights according to the correlation coefficient of the particle concentration data of each grid, and obtain the particle pollution severity set of each grid:

颗粒物浓度污染严重度为P(m,l),以及网格m的颗粒物污染严重度集合P(m)分别为：The particle concentration pollution severity is P(m,l), and the particle pollution severity set P(m) of grid m are:

Figure GDA0003795687230000061
Figure GDA0003795687230000061

β1,β2,β3为权重系数，且β1+β2+β3＝1；β 1 , β 2 , and β 3 are weight coefficients, and β 1 +β 2 +β 3 =1;

37)确定每个网格上方垂直空间内污染严重度最大的值：37) Determine the maximum pollution severity value in the vertical space above each grid:

污染严重度最大的值Pmax(m)＝MaxP(m)；The maximum value of pollution severity P max (m) = MaxP (m);

38)将所有网格颗粒物污染严重度最大的平面衔接起来，形成港口空间中颗粒物污染最严重的劣曲面。38) Connect the planes with the most serious particle pollution in all grids to form the worst surface with the most serious particle pollution in the port space.

所述步骤4)中港口网格的空间聚合优化方法为：The spatial aggregation optimization method of the port grid in the step 4) is:

41)计算相邻网格之间颗粒物浓度的关联度：41) Calculate the correlation degree of particle concentration between adjacent grids:

PM2.5的关联度CoPM2.5(n,q)，PM10的关联度CoPM10(n,q)以及TSP的关联度CoTSP(n,q)为：The correlation degree Co PM2.5 (n,q) of PM2.5, the correlation degree Co PM10 (n,q) of PM10 and the correlation degree Co TSP (n,q) of TSP are:

Figure GDA0003795687230000062
Figure GDA0003795687230000062

式中，q为与网格n相邻的网格；In the formula, q is the grid adjacent to grid n;

42)计算相邻网格之间颗粒物浓度的综合关联系数：42) Calculate the comprehensive correlation coefficient of particle concentration between adjacent grids:

颗粒物浓度综合关联系数CT(n,q)：Comprehensive correlation coefficient CT(n,q) of particulate matter concentration:

Figure GDA0003795687230000063
Figure GDA0003795687230000063

其中，

Figure GDA0003795687230000064
为权重系数，且
Figure GDA0003795687230000065
in,
Figure GDA0003795687230000064
is the weight coefficient, and
Figure GDA0003795687230000065

43)若网格n与相邻网格q中颗粒物浓度综合关联系数CT(n,q)≥ε，则将相邻网格q划入到网格n的聚合子集On；其中ε为预设的关联阈值。43) If the comprehensive correlation coefficient CT(n,q)≥ε of the particle concentration in the grid n and the adjacent grid q, then the adjacent grid q is divided into the aggregated subset O n of the grid n ; where ε is Preset correlation threshold.

与现有技术相比，本发明的有益效果是：Compared with the prior art, the beneficial effects of the present invention are:

1)本发明通过将港口平面细分为不同的网格，并利用无人机对港口不同网格垂直空间内颗粒物浓度进行检测，与现有的仅通过固定在地面的在线检测器相比，能更充分地掌握港口颗粒物浓度特征。1) The present invention subdivides the port plane into different grids, and uses drones to detect the particle concentration in the vertical space of different grids of the port. Compared with the existing online detectors that are only fixed on the ground, It can more fully grasp the characteristics of the concentration of particulate matter in the port.

2)根据每个网格空间颗粒物浓度的特征，确定港口空间颗粒物污染最严重的劣曲面，而通过固定在地面的在线检测器仅能判断颗粒物污染最严重的局部平面区域，本发明能更准确地判断港口颗粒物污染严重度的变化情况。2) According to the characteristics of particle concentration in each grid space, the inferior curved surface with the most serious particle pollution in the port space is determined, and the online detector fixed on the ground can only judge the local plane area with the most serious particle pollution, and the present invention can be more accurate To judge the changes in the severity of particulate pollution in ports.

3)本发明根据相邻网格空间颗粒物浓度之间的相关性，对港口的网格进行聚合优化，并在颗粒物污染最严重的劣曲面，综合考虑不同网格的空间关系，确定在线检测器的最优布设位置。可以解决现有在线检测器布设缺乏定量判断依据的问题，根据港口颗粒物污染浓度特征有针对性地选择最优的布点位置，可以在减少布点的同时，保证了检测结果的有效性，提高港口污染监测的投入产出效益。3) The present invention aggregates and optimizes the grids of the port according to the correlation between the particle concentrations in adjacent grid spaces, and determines the online detector by comprehensively considering the spatial relationship of different grids on the inferior surface with the most serious particle pollution. optimal placement location. It can solve the problem that the existing online detectors lack quantitative judgment basis. According to the characteristics of the concentration of particulate matter in the port, the optimal distribution point can be selected in a targeted manner, which can reduce the number of points, ensure the validity of the detection results, and improve the port pollution. Monitoring input-output benefits.

附图说明Description of drawings

图1流程图；Figure 1 flow chart;

图2港口平面网格划分示意图；Figure 2 Schematic diagram of port plane grid division;

图3网格关联优化调整集合示意图；Fig. 3 Schematic diagram of grid association optimization adjustment set;

图4在线检测器最优布局方案示意图。Figure 4 is a schematic diagram of the optimal layout scheme of the online detector.

具体实施方式Detailed ways

以下结合附图，对本发明做进一步说明：Below in conjunction with accompanying drawing, the present invention is further described:

本发明一种港口大气颗粒物浓度在线检测器的布局优化方法，可以用于在线实时连续检测港口大气环境中PM2.5、PM10以及TSP的浓度，可以在节约建设成本的同时真实地掌握港口大气环境的污染状况。The present invention is a method for optimizing the layout of an on-line detector for the concentration of atmospheric particulate matter in a port, which can be used for online real-time and continuous detection of the concentrations of PM2.5, PM10 and TSP in the atmospheric environment of the port, and can truly grasp the atmospheric environment of the port while saving construction costs. pollution status.

如图1所示，本发明方法步骤如下：As shown in Figure 1, the method steps of the present invention are as follows:

首先，根据港口总平面布置图，对港口进行网格划分，并以顺时针螺旋法则进行编号；First, according to the general layout of the port, the port is divided into grids and numbered according to the clockwise spiral rule;

其次，利用搭载颗粒物浓度检测器的无人机对每个网格垂直空间内的颗粒物浓度进行检测；Secondly, use a drone equipped with a particle concentration detector to detect the particle concentration in the vertical space of each grid;

进而，根据每个网格空间颗粒物浓度的特征，确定港口空间颗粒物污染最严重的劣曲面；Furthermore, according to the characteristics of particle concentration in each grid space, the inferior surface with the most serious particle pollution in the port space is determined;

同时，根据相邻网格空间颗粒物浓度之间的相关性，对港口的网格进行聚合优化；At the same time, according to the correlation between the particle concentration in adjacent grid spaces, the grid of the port is aggregated and optimized;

最后，在颗粒物污染最严重的劣曲面，综合考虑不同网格的空间关系，确定在线检测器的最优布设位置。Finally, on the inferior surface with the most serious particle pollution, the optimal placement position of the online detector is determined by comprehensively considering the spatial relationship of different grids.

A.港口平面网格划分的方法如下：A. The method of port plane grid division is as follows:

A1)获取港区的总平面布局图，确定总平面的边界点的经纬度坐标；A1) Obtain the general plan layout of the port area, and determine the latitude and longitude coordinates of the boundary points of the general plan;

A2)如附图2所示，在港区总平面布局图中，以纬度最低点设置X轴，以经度最低点设置Y轴，结合港区总平面尺寸数据建立港区总平面布局图的平面直角坐标系；A2) As shown in accompanying drawing 2, in the general plan layout of the port area, the X-axis is set with the lowest point of latitude, the Y-axis is set with the lowest point of longitude, and the plane of the general plan layout of the port area is established in combination with the general plane size data of the port area Cartesian coordinate system;

A3)在构建的平面直角坐标系中，分别在横坐标和纵坐标上以宽度w为间隔将港口划分为M个网格，并对港区总平面内所有的网格从最接近X轴零点的位置为编号为1，其他依次以顺时针螺旋法则进行编号，直到所有网格都有专门的编号m，m＝1,2,…,M。其中顺时针螺旋法则指，从编号1的网格开始沿Y轴方向对相邻网格进行编号直到可以编号的网格边界后，以顺时针方向转换为X轴方向对相邻网格进行编号直到可以编号的网格边界后，以顺时针方向转换为Y轴方向进行同样的编号直到遍历所有的网格均编号完成。如附图2所示，当没有特殊要求时，根据发明人经验，网格划分的间隔宽度w可以取值为50米；A3) In the constructed plane Cartesian coordinate system, the port is divided into M grids on the abscissa and ordinate with the width w as the interval, and all grids in the general plane of the port are divided into M grids from the nearest zero point of the X axis. The position of the grid is numbered as 1, and the others are numbered according to the clockwise spiral rule, until all grids have a special number m, m=1,2,...,M. The clockwise spiral rule means that the adjacent grids are numbered along the Y-axis direction from the grid number 1 to the grid boundary that can be numbered, and then the adjacent grids are numbered by converting the clockwise direction to the X-axis direction. After the grid boundary that can be numbered, convert the clockwise direction to the Y-axis direction and perform the same numbering until all the grids are numbered. As shown in Figure 2, when there is no special requirement, according to the inventor's experience, the interval width w of grid division can be 50 meters;

A4)确定每个网格的中心点处在直角坐标系中的位置，记为(Xc(m),Yc(m))。A4) Determine the position of the center point of each grid in the Cartesian coordinate system, denoted as (X c (m), Y c (m)).

B.无人机检测日期确定的方法如下：B. The method of determining the date of drone inspection is as follows:

B1)获取港口的历史气象数据，计算当地过去K年中每周的平均风速、平均温度和平均湿度数据，以第k(k＝1,2,…,K)年的第i(i＝1,2,…,52)周为例，平均风速为

Figure GDA0003795687230000081
平均温度为
Figure GDA0003795687230000082
平均湿度为
Figure GDA0003795687230000083
其中s(i,j,k)为第k年第i周第j天的平均风速，t(i,j,k)为第k年第i周第j天的平均温度，h(i,j,k)为第k年第i周第j天的平均湿度。根据发明人经验，历史气象数据可以由当地气象管理部门获取，建议历史年K＝3。B1) Obtain the historical meteorological data of the port, and calculate the weekly average wind speed, average temperature and average humidity data in the past K years in the local area. ,2,…,52) weeks as an example, the average wind speed is
Figure GDA0003795687230000081
The average temperature is
Figure GDA0003795687230000082
The average humidity is
Figure GDA0003795687230000083
where s(i,j,k) is the average wind speed on the jth day of the ith week in the kth year, t(i,j,k) is the average temperature on the jth day of the ith week in the kth year, h(i,j ,k) is the average humidity on the jth day of the ith week in the kth year. According to the inventor's experience, historical meteorological data can be obtained by the local meteorological management department, and it is recommended that the historical year K=3.

B2)根据每周的平均风速、温度和湿度数据，构建每周的平均风速集合

Figure GDA0003795687230000084
平均温度集合
Figure GDA0003795687230000085
和平均湿度集合
Figure GDA0003795687230000091
B2) According to the weekly average wind speed, temperature and humidity data, construct a weekly average wind speed set
Figure GDA0003795687230000084
average temperature set
Figure GDA0003795687230000085
and the average humidity set
Figure GDA0003795687230000091

B3)测算每周的风速指数fs(i)、温度指数ft(i)和湿度指数fh(i)，B3) Calculate the weekly wind speed index f s (i), temperature index f t (i) and humidity index f h (i),

Figure GDA0003795687230000092
Figure GDA0003795687230000092

其中，MinS(i)为每周的平均风速集合中风速最小的值，MaxS(i)为每周的平均风速集合中风速最大的值，MinT(i)为每周的平均温度集合中温度最小的值，MaxT(i)为每周的平均温度集合中温度最大的值，MinH(i)为每周的平均湿度集合中湿度最小的值，MaxS(i)为每周的平均湿度集合中湿度最大的值。Among them, MinS(i) is the minimum wind speed in the weekly average wind speed set, MaxS(i) is the maximum wind speed in the weekly average wind speed set, MinT(i) is the minimum temperature in the weekly average temperature set , MaxT(i) is the maximum temperature value in the weekly average temperature set, MinH(i) is the minimum humidity value in the weekly average humidity set, MaxS(i) is the weekly average humidity set humidity in the set maximum value.

B4)根据风速指数、温度指数和湿度指数，可以确定Bt(i)对应的第i周无人机的最佳检测周，B4) According to the wind speed index, temperature index and humidity index, the best detection week of the drone in the i-th week corresponding to B t (i) can be determined,

Figure GDA0003795687230000093
Figure GDA0003795687230000093

其中，Bt(i)为综合考虑风速、温度和湿度后的最佳检测气象条件，MaxV(i)为全年52周综合考虑风速指数、温度指数和湿度指数的最大值，λ1,λ2,λ3为权重系数，且λ1+λ2+λ3＝1。Among them, B t (i) is the best detected meteorological condition after comprehensive consideration of wind speed, temperature and humidity, MaxV(i) is the maximum value of wind speed index, temperature index and humidity index comprehensively considered in 52 weeks of the year, λ 1 , λ 2 , λ 3 are weight coefficients, and λ 1 +λ 2 +λ 3 =1.

当没有特殊要求时，根据发明人经验，可设定λ1＝0.3,λ2＝0.3,λ3＝0.4。When there is no special requirement, according to the inventor's experience, λ 1 =0.3, λ 2 =0.3, λ 3 =0.4 can be set.

B5)在最佳检测周中选择一天(港口正常作业)作为无人机检测日期。B5) Select one day in the best inspection week (normal operation of the port) as the UAV inspection date.

C.港口网格垂直空间大气颗粒物浓度检测的方法为：C. The method for detecting the concentration of atmospheric particulate matter in the vertical space of the port grid is:

C1)利用搭载颗粒物浓度检测器的无人机，对每个网格中心位置由地面至垂直上方H米高度空间内每隔b米位置检测的PM2.5的浓度为PM2.5(m,l,d)，PM10的浓度为PM10(m,l,d)，TSP的浓度为TSP(m,l,d)。其中，l为由地面至垂直上方H米高度空间内的检测位置编号，本发明中H米高度范围内每次检测的高度间隔为b米，因此从地面上方b米位置开始l＝1,2,…,L；D为无人机检测的总次数，d为无人机检测的编号，d＝1,2,…,D；PM2.5(m,l,d)是指在网格m的中心高度编号为l位置，无人机在第d次飞行检测的动力学当量直径小于等于2.5微米的颗粒物浓度；PM10(m,l,d)是指在网格m的中心高度编号为l位置，无人机在第d次飞行检测的的动力学当量直径小于等于10微米的颗粒物浓度；TSP(m,l)是指在网格m的中心高度编号为l位置，无人机在第d次飞行检测的动力学当量直径小于等于100微米的颗粒物浓度。当没有特色要求时，根据发明人经验，利用无人机在港口地面上方检测的高度H最好设定在H＝120米范围内，无人机检测的高度间隔b米可以设定为b＝5米，因此，L＝H/b＝24,从地面上方5米位置开始l＝1,2,…,24。根据发明人经验，无人机检测的次数D可以设定3，可以记d＝1,2,3。C1) Using a drone equipped with a particle concentration detector, the concentration of PM2.5 detected at every b-meter position from the ground to the vertical upper H-meter height space from the center of each grid is PM2.5 (m,l, d), the concentration of PM10 is PM10 (m,l,d), and the concentration of TSP is TSP(m,l,d). Among them, l is the detection position number in the space from the ground to the vertical height of H meters. In the present invention, the height interval of each detection within the height of H meters is b meters. Therefore, starting from the position of b meters above the ground, l=1, 2 ,…,L; D is the total number of drone detections, d is the number of drone detections, d=1,2,…,D; PM 2.5 (m,l,d) refers to the number of detections in grid m The center height is numbered at position l, and the dynamic equivalent diameter detected by the UAV in the d-th flight is less than or equal to 2.5 microns. position, the particle concentration with a kinetic equivalent diameter of less than or equal to 10 microns detected by the drone in the d-th flight; TSP(m,l) refers to the position numbered l at the center of the grid m, and the drone is in the d-th flight. The particle concentration of which the kinetic equivalent diameter of d flight detection is less than or equal to 100 microns. When there are no special requirements, according to the inventor's experience, the height H detected by the drone above the port ground is preferably set within the range of H=120 meters, and the height interval b meters detected by the drone can be set as b= 5 meters, therefore, L = H/b = 24, and l = 1, 2, . . . , 24 from a position 5 meters above the ground. According to the inventor's experience, the number D of drone detection can be set to 3, and d=1, 2, 3 can be recorded.

C2)根据每个网格垂直空间中利用无人机检测的颗粒物浓度数据，可得到不同高度的PM2.5、PM10和TSP的平均浓度。以网格m为例，不同高度检测的PM2.5的平均浓度为

Figure GDA0003795687230000101
PM10的平均浓度为
Figure GDA0003795687230000102
TSP的平均浓度为
Figure GDA0003795687230000103
C2) According to the particle concentration data detected by drones in the vertical space of each grid, the average concentrations of PM2.5, PM10 and TSP at different heights can be obtained. Taking grid m as an example, the average concentration of PM2.5 detected at different heights is
Figure GDA0003795687230000101
The average concentration of PM10 is
Figure GDA0003795687230000102
The average concentration of TSP is
Figure GDA0003795687230000103

C3)确定不同网格空间的颗粒物浓度数据集合，以网格m为例，PM2.5的浓度集合为

Figure GDA0003795687230000104
PM10的浓度集合为
Figure GDA0003795687230000105
TSP的浓度集合为
Figure GDA0003795687230000106
C3) Determine the particle concentration data sets in different grid spaces. Taking grid m as an example, the concentration set of PM2.5 is
Figure GDA0003795687230000104
The concentration set of PM10 is
Figure GDA0003795687230000105
The concentration set of TSP is
Figure GDA0003795687230000106

D.构建颗粒物浓度最劣曲面的方法为：D. The method of constructing the worst surface for particle concentration is:

D1)确定港口不同网格上方空间颗粒物浓度的最大值并构建颗粒物浓度最高的集合Z(m)。以网格m处为例，垂直上方空间中PM2.5的浓度最高值

Figure GDA0003795687230000107
PM10的浓度最高值
Figure GDA0003795687230000108
TSP的浓度最高值TSPmax(m)＝MaxTSP(M)。由此，构建网格m处颗粒物浓度最高的集合
Figure GDA0003795687230000109
D1) Determine the maximum particle concentration in the space above different grids of the port and construct the set Z(m) with the highest particle concentration. Taking grid m as an example, the highest concentration of PM2.5 in the vertical upper space
Figure GDA0003795687230000107
The highest concentration of PM10
Figure GDA0003795687230000108
The highest concentration of TSP is TSP max (m)=MaxTSP (M). Thus, the set with the highest particle concentration at grid m is constructed
Figure GDA0003795687230000109

D2)测算每个网格颗粒物浓度指数，以网格m为例，PM2.5的浓度指数fPM2.5(m,l)，PM10的浓度指数为fPM10(m,l)，TSP的浓度指数为fTSP(m,l)分别为：D2) Calculate the particle concentration index of each grid. Taking grid m as an example, the concentration index of PM2.5 is f PM2.5 (m,l), the concentration index of PM10 is f PM10 (m,l), and the concentration of TSP The exponents are f TSP (m,l) are:

Figure GDA0003795687230000111
Figure GDA0003795687230000111

D3)确定每个网格浓度指数的最大值，以网格m为例，PM2.5浓度指数的最大值

Figure GDA0003795687230000112
PM10浓度指数的最大值
Figure GDA0003795687230000113
TSP浓度指数的最大值
Figure GDA0003795687230000114
Figure GDA0003795687230000115
D3) Determine the maximum value of each grid concentration index, taking grid m as an example, the maximum value of PM2.5 concentration index
Figure GDA0003795687230000112
Maximum value of PM10 concentration index
Figure GDA0003795687230000113
Maximum value of TSP concentration index
Figure GDA0003795687230000114
Figure GDA0003795687230000115

本发明中Max[]均表示向量中的最大值。In the present invention, Max[] all represent the maximum value in the vector.

D4)确定每个网格颗粒物浓度指数的最大值，以网格m为例，颗粒物浓度指数的最大值为：

Figure GDA0003795687230000116
D4) Determine the maximum value of the particle concentration index of each grid. Taking grid m as an example, the maximum value of the particle concentration index is:
Figure GDA0003795687230000116

D5)计算每个网格颗粒物浓度系数与浓度系数最大值之间的关联系数，以网格m中心垂直上方编号为l位置处检测的颗粒物浓度为例，PM2.5、PM10以及TSP的浓度系数与浓度系数最大值的关联系数如下：D5) Calculate the correlation coefficient between the particle concentration coefficient of each grid and the maximum concentration coefficient, taking the particle concentration detected at the position number l vertically above the center of grid m as an example, the concentration coefficients of PM2.5, PM10 and TSP The correlation coefficient with the maximum concentration coefficient is as follows:

Figure GDA0003795687230000117
Figure GDA0003795687230000117

D6)根据每个网格的颗粒物浓度数据的关联系数确定不同高度的污染严重度，并得到每个网格的颗粒物污染严重度集合。以网格m中心垂直上方编号为l位置处检测的颗粒物浓度为例，颗粒物浓度污染严重度为P(m,l),以及网格m的颗粒物污染严重度集合P(m)分别为：D6) Determine the pollution severity at different heights according to the correlation coefficient of the particle concentration data of each grid, and obtain a set of particle pollution severity for each grid. Taking the particle concentration detected at the position number l vertically above the center of grid m as an example, the pollution severity of particle concentration is P(m,l), and the particle pollution severity set P(m) of grid m is:

Figure GDA0003795687230000121
Figure GDA0003795687230000121

β1,β2,β3为权重系数，且β1+β2+β3＝1。根据发明人经验，当地主管部门无特殊要求时可以取值为：β1＝0.2,β2＝0.3,β3＝0.5。β 1 , β 2 , and β 3 are weight coefficients, and β 1 +β 2 +β 3 =1. According to the inventor's experience, when the local competent authority has no special requirements, the values can be as follows: β 1 =0.2, β 2 =0.3, β 3 =0.5.

D7)确定每个网格上方垂直空间内污染严重度最大的值，以网格m为例，污染严重度最大的值Pmax(m)＝MaxP(m)；D7) Determine the maximum pollution severity value in the vertical space above each grid, taking grid m as an example, the maximum pollution severity value P max (m)=MaxP (m);

D8)将所有网格颗粒物污染严重度最大的平面衔接起来，形成港口空间中颗粒物污染最严重的劣曲面。D8) Connect all the planes with the most serious particle pollution in all grids to form the worst surface with the most serious particle pollution in the port space.

E.港口网格的空间聚合优化方法为：E. The spatial aggregation optimization method of port grid is:

E1)从网格编号1开始，计算相邻网格之间颗粒物浓度的关联度。以网格m与相邻的网格q的为例，PM2.5的关联度CoPM2.5(m,q)，PM10的关联度CoPM10(m,q)以及TSP的关联度CoTSP(m,q)为：E1) Starting from grid number 1, calculate the correlation degree of particle concentration between adjacent grids. Taking the grid m and the adjacent grid q as an example, the correlation degree of PM2.5 Co PM2.5 (m, q), the correlation degree of PM10 Co PM10 (m, q) and the correlation degree of TSP Co TSP ( m,q) is:

Figure GDA0003795687230000122
Figure GDA0003795687230000122

E2)计算相邻网格之间颗粒物浓度的综合关联系数，以网格m与相邻网格q为例，颗粒物浓度综合关联系数CT(m,q)；E2) Calculate the comprehensive correlation coefficient of particle concentration between adjacent grids, taking grid m and adjacent grid q as an example, the comprehensive correlation coefficient of particle concentration CT(m, q);

Figure GDA0003795687230000123
Figure GDA0003795687230000123

其中，

Figure GDA0003795687230000124
为权重系数，且
Figure GDA0003795687230000125
当无特殊要求时，根据发明人经验可设定
Figure GDA0003795687230000126
in,
Figure GDA0003795687230000124
is the weight coefficient, and
Figure GDA0003795687230000125
When there are no special requirements, it can be set according to the inventor's experience
Figure GDA0003795687230000126

E3)若网格m与相邻网格q中颗粒物浓度综合关联系数CT(m,q)≥ε，则将相邻网格q划入到网格m的聚合子集Om。其中ε为预设的关联阈值，根据发明人经验可以设ε＝0.85。如附图3所示，新的聚合子集Om共有7个不同的网格集合，包含了港口所有73个网格。每个网格的编号包含了此网格的原始编号以及所属的聚合子集编号两种，如网格编号3(60)表示原来附图1中划分的编号为60的网格属于O3子集。E3) If the comprehensive correlation coefficient CT(m,q) ≥ ε of the particle concentration in the grid m and the adjacent grid q, the adjacent grid q is divided into the aggregated subset O m of the grid m . Among them, ε is a preset association threshold, which can be set as ε=0.85 according to the inventor's experience. As shown in Fig. 3, the new aggregated subset O m has a total of 7 different grid sets, including all 73 grids of the port. The number of each grid includes the original number of the grid and the number of the aggregated subset to which it belongs. For example, grid number 3 (60) indicates that the grid numbered 60 in the original Figure 1 belongs to the O 3 sub-set. set.

E4)以此类推，直到将港口所有网格聚合优化为不同的关联网格集合，如附图3所示；E4) And so on, until the aggregation of all grids in the port is optimized into different associated grid sets, as shown in Figure 3;

F.确定在线检测器最优布局方案的方法为：F. The method to determine the optimal layout scheme of the online detector is:

F1)在港口空间颗粒物浓度最高的劣曲面上，确定所有关联网格集合的中心点的坐标，以聚合子集Om为例，此聚合子集中所有网格形成的图形的中心点坐标为(Xc(Om),Yc(Om))。以Om中第6个子集中所有网格形成的图形为例，中心点坐标如附图4所示。F1) On the inferior surface with the highest particle concentration in the port space, determine the coordinates of the center points of all the associated grid sets, taking the aggregate subset O m as an example, the coordinates of the center points of the graphs formed by all grids in this aggregate subset are ( X c (O m ), Y c (O m )). Taking the graph formed by all the grids in the sixth subset in O m as an example, the coordinates of the center point are shown in Figure 4.

F2)分别计算聚合子集Om中所有A个网格与聚合子集Om中心点坐标(Xc(Om),Yc(Om))的距离，以聚合子集Om中网格a(a＝1,2,…,A)为例，其与聚合子集中心坐标的距离

Figure GDA0003795687230000131
为：F2) Calculate the distances of all A grids in the aggregation subset O m and the coordinates (X c (O m ), Y c (O m )) of the center point of the aggregation subset O m respectively, so as to aggregate the meshes in the aggregation subset O m Take lattice a (a=1,2,...,A) as an example, its distance from the center coordinates of the aggregated subset
Figure GDA0003795687230000131
for:

Figure GDA0003795687230000132
Figure GDA0003795687230000132

F3)确定聚合子集Om中所有A个网格与聚合子集Om中心点坐标(Xc(Om),Yc(Om))的距离的最大值

Figure GDA0003795687230000133
为
Figure GDA0003795687230000134
F3) Determine the maximum distance between all A grids in the aggregate subset O m and the center point coordinates (X c (O m ), Y c (O m )) of the aggregate subset O m
Figure GDA0003795687230000133
for
Figure GDA0003795687230000134

F4)综合考虑聚合子集中所有网格空间中颗粒物浓度最高的劣曲面中颗粒物污染严重度的修正值，以聚合子集Om为例，网格a上方垂直空间中劣曲面上颗粒物污染严重度修正值

Figure GDA0003795687230000135
F4) Comprehensively consider the correction value of the particle pollution severity in the inferior surface with the highest particle concentration in all grid spaces in the aggregation subset, taking the aggregation subset O m as an example, the particle pollution severity on the inferior surface in the vertical space above the grid a Correction value
Figure GDA0003795687230000135

F5)将聚合子集中所有网格中颗粒物污染严重度修正值最大的网格作为在线检测器的布置点位。F5) The grid with the largest particle pollution severity correction value among all grids in the aggregated subset is used as the placement point of the online detector.

F6)对每一个聚合子集重复上述步骤，得到港口空间中所有在线检测器的最优布置，如附图4所示。F6) Repeat the above steps for each aggregated subset to obtain the optimal arrangement of all online detectors in the port space, as shown in FIG. 4 .

Claims (9)

1.一种港口大气颗粒物浓度在线检测器的布局优化方法，其特征在于，步骤如下：1. a layout optimization method of a port atmospheric particle concentration on-line detector, is characterized in that, step is as follows: 1)港口平面网格划分：根据港口总平面布局图，对港口平面进行网格划分；1) Port plane grid division: According to the port general plane layout, the port plane is divided into grids; 2)港口网格垂直空间大气颗粒物浓度检测：利用颗粒物浓度检测器，对每个网格中心位置由地面至垂直上方H米高度空间内的L个不同高度位置的颗粒物浓度进行检测，得到网格上方垂直空间内L个颗粒物浓度数据，L≥2；2) Detection of atmospheric particulate matter concentration in the vertical space of port grid: use the particle concentration detector to detect the concentration of particulate matter at L different height positions in the space from the ground to the vertical above H meters from the center of each grid, and obtain the grid L particle concentration data in the vertical space above, L≥2; 3)港口空间颗粒物污染最严重的劣曲面构建：确定每一个网格中颗粒物污染最严重的高度，将所有网格颗粒物污染严重度最大的平面衔接起来，形成港口空间中颗粒物污染最严重的劣曲面；3) Construction of inferior surfaces with the most serious particle pollution in the port space: determine the height of the most serious particle pollution in each grid, and connect the planes with the most serious particle pollution in all grids to form the most serious particle pollution in the port space. surface; 4)港口网格的空间聚合优化：根据港口不同网格垂直空间内检测的颗粒物浓度数据进行关联度分析，确定聚合的网格集合；4) Spatial aggregation optimization of port grids: carry out correlation analysis according to the particle concentration data detected in the vertical space of different grids in the port, and determine the aggregated grid set; 5)确定在线检测器的最优布局方案：在确定的每个聚合网格集合中，选择其中一个网格的劣曲面作为布置在线检测器的最优布局方案；5) Determine the optimal layout scheme of the online detector: in each of the determined aggregated grid sets, select the inferior surface of one of the grids as the optimal layout scheme for arranging the online detector; 步骤5)中确定在线检测器最优布局方案的方法为：The method for determining the optimal layout scheme of the online detector in step 5) is: 51)在港口空间颗粒物浓度最高的劣曲面上，确定每个聚合网格集合的中心点的坐标(Xc(On),Yc(On))，式中On为第n个聚合网格集合，n＝1,2,…,N，N为聚合网格集合总数；51) On the inferior surface with the highest particle concentration in the port space, determine the coordinates (X c (O n ), Y c (O n )) of the center point of each aggregated grid set, where O n is the nth aggregate Grid set, n=1,2,...,N, N is the total number of aggregated grid sets; 52)分别计算每个聚合网格集合On中所有个网格与聚合网格集合On中心点坐标(Xc(On),Yc(On))的距离
Figure FDA0003765616940000011
为：52) Calculate the distances of all grids in each aggregate grid set O n and the coordinates (X c (O n ), Y c (O n )) of the center point of the aggregate grid set O n respectively
Figure FDA0003765616940000011
for:
Figure FDA0003765616940000012
Figure FDA0003765616940000012
 式中，an＝1,2,…,An；An为第n个聚合网格集合On包含的网格数；In the formula, an =1,2,...,An; An is the number of grids included in the nth aggregate grid set O n ; 53)确定每个聚合网格集合On中所有An个网格与网格集合On中心点坐标(Xc(On),Yc(On))的距离的最大值
Figure FDA0003765616940000013
为：53) Determine the maximum value of the distances between all A n grids in each aggregated grid set O n and the center point coordinates (X c (O n ), Y c (O n )) of the grid set O n
Figure FDA0003765616940000013
for:
Figure FDA0003765616940000014
Figure FDA0003765616940000014
 54)确定每个聚合网格集合On中每一个网格an上方垂直空间中劣曲面上颗粒物污染严重度修正值
Figure FDA0003765616940000015
54) Determine the correction value of particle pollution severity on the inferior surface in the vertical space above each grid an in each aggregated grid set O n
Figure FDA0003765616940000015
 式中，Pmax(an)为网格an的颗粒物污染严重度最大的值；In the formula, P max (an ) is the maximum value of the particle pollution severity of grid an; 55)将聚合网格集合中所有网格中颗粒物污染严重度修正值最大的网格作为在线检测器的布置点位。55) The grid with the largest particle pollution severity correction value among all grids in the aggregated grid set is used as the placement point of the online detector. 2.根据权利要求1所述的布局优化方法，其特征在于，L＝H/b，其中b为高度间隔。2 . The layout optimization method according to claim 1 , wherein L=H/b, wherein b is a height interval. 3 . 3.根据权利要求1所述的布局优化方法，其特征在于，采用无人机进行步骤2)的港口网格垂直空间大气颗粒物浓度检测。3 . The layout optimization method according to claim 1 , wherein the detection of atmospheric particulate matter concentration in the vertical space of the port grid in step 2) is carried out by using an unmanned aerial vehicle. 4 . 4.根据权利要求3所述的布局优化方法，其特征在于，无人机检测时，根据港口历史气象信息，综合考虑风速、温度和湿度指标，确定无人机的最佳检测日期。4. The layout optimization method according to claim 3, characterized in that, when the drone is detected, the best detection date of the drone is determined based on the historical meteorological information of the port, comprehensively considering wind speed, temperature and humidity indicators. 5.根据权利要求4所述的布局优化方法，其特征在于，所述无人机的最佳检测日期的确定方法如下：5. layout optimization method according to claim 4, is characterized in that, the determination method of the best detection date of described unmanned aerial vehicle is as follows: 21)获取港口的历史气象数据，计算当地过去K年中每周的平均风速、平均温度和平均湿度数据；21) Obtain the historical meteorological data of the port, and calculate the weekly average wind speed, average temperature and average humidity data in the past K years; 22)根据每周的平均风速、温度和湿度数据，构建每周的平均风速集合、平均温度集合和平均湿度集合；22) According to the weekly average wind speed, temperature and humidity data, construct the weekly average wind speed set, the average temperature set and the average humidity set; 23)测算每周的风速指数fs(i)、温度指数ft(i)和湿度指数fh(i)，23) Calculate the weekly wind speed index f s (i), temperature index f t (i) and humidity index f h (i),
Figure FDA0003765616940000021
Figure FDA0003765616940000021
 其中，MinS(i)为每周的平均风速集合中风速最小的值，MaxS(i)为每周的平均风速集合中风速最大的值，MinT(i)为每周的平均温度集合中温度最小的值，MaxT(i)为每周的平均温度集合中温度最大的值，MinH(i)为每周的平均湿度集合中湿度最小的值，MaxS(i)为每周的平均湿度集合中湿度最大的值；Among them, MinS(i) is the minimum wind speed in the weekly average wind speed set, MaxS(i) is the maximum wind speed in the weekly average wind speed set, MinT(i) is the minimum temperature in the weekly average temperature set , MaxT(i) is the maximum temperature value in the weekly average temperature set, MinH(i) is the minimum humidity value in the weekly average humidity set, MaxS(i) is the weekly average humidity set humidity in the set maximum value; 24)根据风速指数、温度指数和湿度指数，确定Bt(i)对应的第i周无人机的最佳检测周，24) According to the wind speed index, temperature index and humidity index, determine the best detection week of the drone in the i-th week corresponding to B t (i),
Figure FDA0003765616940000022
Figure FDA0003765616940000022
 其中，Bt(i)为综合考虑风速、温度和湿度后的最佳检测气象条件，MaxV(i)为全年52周综合考虑风速指数、温度指数和湿度指数的最大值，λ1,λ2,λ3为权重系数，且λ1+λ2+λ3＝1；Among them, B t (i) is the best detected meteorological condition after comprehensive consideration of wind speed, temperature and humidity, MaxV(i) is the maximum value of wind speed index, temperature index and humidity index comprehensively considered in 52 weeks of the year, λ 1 , λ 2 , λ 3 is the weight coefficient, and λ 1 +λ 2 +λ 3 =1; 25)在最佳检测周中选择一天作为无人机检测日期。25) Select a day in the best detection week as the drone detection date. 6.根据权利要求1所述的布局优化方法，其特征在于，步骤1)中所述港口平面网格划分的方法如下：6. layout optimization method according to claim 1, is characterized in that, the method for port plane grid division described in step 1) is as follows: 11)获取港区的总平面布局图，确定总平面的边界点的经纬度坐标；11) Obtain the general plan layout of the port area, and determine the latitude and longitude coordinates of the boundary points of the general plan; 12)在港区总平面布局图中，以纬度最低点设置X轴，以经度最低点设置Y轴，结合港区总平面尺寸数据建立港区总平面布局图的平面直角坐标系；12) In the general plan layout of the port area, the X-axis is set with the lowest point of latitude, the Y-axis is set with the lowest point of longitude, and the plane rectangular coordinate system of the general plan layout of the port area is established in combination with the general plane size data of the port area; 13)在构建的平面直角坐标系中，分别在横坐标和纵坐标上以宽度w为间隔将港口划分为M个网格，并对港区总平面内所有的网格从最接近X轴零点的位置为编号为1，其他依次以顺时针螺旋法则进行编号，直到所有网格都有专门的编号m，m＝1,2,…,M；其中顺时针螺旋法则指，从编号1的网格开始沿Y轴方向对相邻网格进行编号直到可以编号的网格边界后，以顺时针方向转换为X轴方向对相邻网格进行编号直到可以编号的网格边界后，以顺时针方向转换为Y轴方向进行同样的编号直到遍历所有的网格均编号完成；13) In the constructed plane rectangular coordinate system, the port is divided into M grids on the abscissa and the ordinate with the width w as the interval, and all grids in the general plane of the port area are divided into M grids from the nearest zero point of the X axis. The position of the grid is numbered 1, and the others are numbered according to the clockwise spiral rule, until all grids have a special number m, m=1,2,...,M; where the clockwise spiral rule refers to the grid from the number 1. The grid starts to number adjacent grids in the Y-axis direction until the numbered grid boundary, and converts clockwise to the X-axis direction to number the adjacent grids until the numberable grid boundary, then clockwise The direction is converted to the Y-axis direction and the same number is performed until all the grids are traversed and numbered; 14)确定每个网格的中心点在直角坐标系中的位置，记为(Xc(m),Yc(m))。14) Determine the position of the center point of each grid in the Cartesian coordinate system, denoted as (X c (m), Y c (m)). 7.根据权利要求1所述的布局优化方法，其特征在于，步骤2)中港口网格垂直空间大气颗粒物浓度检测的方法为：7. layout optimization method according to claim 1, is characterized in that, in step 2), the method for detection of atmospheric particle concentration in port grid vertical space is: 21)利用搭载颗粒物浓度检测器的无人机，对每个网格中心位置由地面至垂直上方H米高度空间内每隔b米位置检测的PM2.5的浓度为PM2.5(m,l,d)，PM10的浓度为PM10(m,l,d)，TSP的浓度为TSP(m,l,d)；其中，l为由地面至垂直上方H米高度空间内的检测位置编号，H米高度范围内每次检测的高度间隔为b米，因此从地面上方b米位置开始l＝1,2,…,L；d为无人机检测次数的编号，d＝1,2,…,D，D为总检测次数；PM2.5(m,l,d)是指在网格m的中心高度编号为l位置，无人机在第d次飞行检测的动力学当量直径小于等于2.5微米的颗粒物浓度；PM10(m,l,d)是指在网格m的中心高度编号为l位置，无人机在第d次飞行检测的动力学当量直径小于等于10微米的颗粒物浓度；TSP(m,l,d)是指在网格m的中心高度编号为l位置，无人机在第d次飞行检测的动力学当量直径小于等于100微米的颗粒物浓度；21) Using an unmanned aerial vehicle equipped with a particle concentration detector, the concentration of PM2.5 detected at every b-meter position from the ground to the vertical upper H-meter height space at the center of each grid is PM2.5 (m,l, d), the concentration of PM10 is PM 10 (m, l, d), and the concentration of TSP is TSP (m, l, d); among them, l is the detection position number in the space of H meters from the ground to the vertical above, H The height interval of each detection within the height range of meters is b meters, so starting from the position of b meters above the ground, l=1,2,…,L; d is the number of the detection times of the drone, d=1,2,…, D, D are the total number of detections; PM 2.5 (m,l,d) refers to the position where the center height of grid m is numbered l, and the dynamic equivalent diameter detected by the drone in the dth flight is less than or equal to 2.5 microns Concentration of particulate matter; PM 10 (m,l,d) refers to the concentration of particulate matter with a dynamic equivalent diameter of less than or equal to 10 microns detected by the UAV at the d-th flight at the center height of grid m, numbered l position; TSP ( m, l, d) refers to the concentration of particles with a dynamic equivalent diameter less than or equal to 100 microns detected by the UAV at the d-th flight at the position numbered at the center height of grid m; 22)根据每个网格垂直空间中利用无人机检测的颗粒物浓度数据，得到不同高度的PM2.5、PM10和TSP的平均浓度；不同高度检测的PM2.5的平均浓度为
Figure FDA0003765616940000041
PM10的平均浓度为
Figure FDA0003765616940000042
TSP的平均浓度为
Figure FDA0003765616940000043
22) According to the particle concentration data detected by drones in the vertical space of each grid, the average concentrations of PM2.5, PM10 and TSP at different heights are obtained; the average concentrations of PM2.5 detected at different heights are
Figure FDA0003765616940000041
The average concentration of PM10 is
Figure FDA0003765616940000042
The average concentration of TSP is
Figure FDA0003765616940000043
 23)确定不同网格空间的颗粒物浓度数据集合，PM2.5的浓度集合为
Figure FDA0003765616940000044
PM10的浓度集合为
Figure FDA0003765616940000045
TSP的浓度集合为
Figure FDA0003765616940000046
23) Determine the particle concentration data set in different grid spaces, the concentration set of PM2.5 is
Figure FDA0003765616940000044
The concentration set of PM10 is
Figure FDA0003765616940000045
The concentration set of TSP is
Figure FDA0003765616940000046
 8.根据权利要求7所述的布局优化方法，其特征在于，步骤3)中构建颗粒物浓度最劣曲面的方法为：8. layout optimization method according to claim 7 is characterized in that, in step 3), the method for constructing the worst surface of particle concentration is: 31)确定港口不同网格上方空间颗粒物浓度的最大值并构建颗粒物浓度最高的集合Z(m)：31) Determine the maximum value of the particle concentration in the space above the different grids of the port and construct the set Z(m) with the highest particle concentration: 垂直上方空间中PM2.5的浓度最高值
Figure FDA0003765616940000047
PM10的浓度最高值
Figure FDA0003765616940000048
TSP的浓度最高值TSPmax(m)＝MaxTSP(M)；The highest concentration of PM2.5 in the space above the vertical
Figure FDA0003765616940000047
The highest concentration of PM10
Figure FDA0003765616940000048
The highest concentration of TSP TSP max (m) = MaxTSP (M); 构建网格m处颗粒物浓度最高的集合
Figure FDA0003765616940000049
Build the set with the highest particle concentration at grid m
Figure FDA0003765616940000049
 32)测算每个网格颗粒物浓度指数：32) Calculate the particle concentration index of each grid: PM2.5的浓度指数fPM2.5(m,l)，PM10的浓度指数为fPM10(m,l)，TSP的浓度指数为fTSP(m,l)分别为：The concentration index of PM2.5 is f PM2.5 (m,l), the concentration index of PM10 is f PM10 (m,l), and the concentration index of TSP is f TSP (m,l), respectively:
Figure FDA00037656169400000410
Figure FDA00037656169400000410
 33)确定每个网格浓度指数的最大值：33) Determine the maximum value of each grid concentration index: PM2.5浓度指数的最大值
Figure FDA0003765616940000051
PM10浓度指数的最大值
Figure FDA0003765616940000052
TSP浓度指数的最大值
Figure FDA0003765616940000053
Maximum value of PM2.5 concentration index
Figure FDA0003765616940000051
Maximum value of PM10 concentration index
Figure FDA0003765616940000052
Maximum value of TSP concentration index
Figure FDA0003765616940000053
Figure FDA0003765616940000054
Figure FDA0003765616940000054
 式中，Max[]均表示向量中的最大值；In the formula, Max[] all represent the maximum value in the vector; 34)确定每个网格颗粒物浓度指数的最大值：34) Determine the maximum value of the particle concentration index for each grid: 颗粒物浓度指数的最大值为：
Figure FDA0003765616940000055
The maximum value of the particle concentration index is:
Figure FDA0003765616940000055
 35)计算每个网格颗粒物浓度系数与浓度系数最大值之间的关联系数：35) Calculate the correlation coefficient between each grid particle concentration coefficient and the maximum concentration coefficient: PM2.5、PM10以及TSP的浓度系数与浓度系数最大值的关联系数如下：The correlation coefficient between the concentration coefficients of PM2.5, PM10 and TSP and the maximum concentration coefficients is as follows:
Figure FDA0003765616940000056
Figure FDA0003765616940000056
 36)根据每个网格的颗粒物浓度数据的关联系数确定不同高度的污染严重度，并得到每个网格的颗粒物污染严重度集合：36) Determine the pollution severity at different heights according to the correlation coefficient of the particle concentration data of each grid, and obtain the particle pollution severity set of each grid: 颗粒物浓度污染严重度为P(m,l),以及网格m的颗粒物污染严重度集合P(m)分别为：The particle concentration pollution severity is P(m,l), and the particle pollution severity set P(m) of grid m are:
Figure FDA0003765616940000057
Figure FDA0003765616940000057
 β1,β2,β3为权重系数，且β1+β2+β3＝1；β 1 , β 2 , and β 3 are weight coefficients, and β 1 +β 2 +β 3 =1; 37)确定每个网格上方垂直空间内污染严重度最大的值：37) Determine the maximum pollution severity value in the vertical space above each grid: 污染严重度最大的值Pmax(m)＝MaxP(m)；The maximum pollution severity value P max (m)=MaxP (m); 38)将所有网格颗粒物污染严重度最大的平面衔接起来，形成港口空间中颗粒物污染最严重的劣曲面。38) Connect the planes with the most serious particle pollution in all grids to form the worst surface with the most serious particle pollution in the port space. 9.根据权利要求8所述的布局优化方法，其特征在于，步骤4)中港口网格的空间聚合优化方法为：9. layout optimization method according to claim 8, is characterized in that, the space aggregation optimization method of port grid in step 4) is: 41)计算相邻网格之间颗粒物浓度的关联度：41) Calculate the correlation degree of particle concentration between adjacent grids: PM2.5的关联度CoPM2.5(n,q)，PM10的关联度CoPM10(n,q)以及TSP的关联度CoTSP(n,q)为：The correlation degree Co PM2.5 (n,q) of PM2.5, the correlation degree Co PM10 (n,q) of PM10 and the correlation degree Co TSP (n,q) of TSP are:
Figure FDA0003765616940000061
Figure FDA0003765616940000061
 式中，q为与网格n相邻的网格；In the formula, q is the grid adjacent to grid n; 42)计算相邻网格之间颗粒物浓度的综合关联系数：42) Calculate the comprehensive correlation coefficient of particle concentration between adjacent grids: 颗粒物浓度综合关联系数CT(n,q)：Comprehensive correlation coefficient CT(n,q) of particulate matter concentration:
Figure FDA0003765616940000062
Figure FDA0003765616940000062
 其中，
Figure FDA0003765616940000063
为权重系数，且
Figure FDA0003765616940000064
in,
Figure FDA0003765616940000063
is the weight coefficient, and
Figure FDA0003765616940000064
 43)若网格n与相邻网格q中颗粒物浓度综合关联系数CT(n,q)≥ε，则将相邻网格q划入到网格n的聚合子集On；其中ε为预设的关联阈值。43) If the comprehensive correlation coefficient CT(n,q)≥ε of the particle concentration in the grid n and the adjacent grid q, then the adjacent grid q is divided into the aggregated subset O n of the grid n ; where ε is Preset correlation threshold.
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