CN104915551A - PM2.5 concentration estimation method based on vehicle-mounted data acquisition technology - Google Patents

Abstract

The invention relates to a PM2.5 concentration estimation method based on a vehicle-mounted data acquisition technology. Firstly, a vehicle-mounted data acquisition device is used for acquiring original PM2.5 concentration data, then, a probability transfer matrix model is built through the acquired original PM2.5 concentration data, next, the concentration of a grid data missing point is estimated through a probability transfer matrix, and finally, the PM2.5 concentration estimation result of a city area is obtained. The method is high in data coverage rate, deploy is convenient, the precision of the PM2.5 concentration estimation result obtained through the method is high, and stability is good.

Description

A kind of PM2.5 Concentration Estimation Method based on vehicular data acquisition technology

Technical field

The present invention relates to wireless sensor technology, Computer Applied Technology and Supplementing Data technology, is a kind of PM2.5 Concentration Estimation Method based on vehicular data acquisition technology.

Background technology

PM2.5 refers to that surrounding air medium power equivalent diameter is less than or equal to the particle of 2.5 microns.Its particle diameter is little, and area is large, active strong, easily attaches poisonous and harmful substance, and residence time length, long transmission distance in an atmosphere.It produces tremendous influence to health and atmosphere quality, and therefore the monitoring of PM2.5 concentration and estimation become a hot issue of society.

Current PM2.5 Concentration Estimation Method is a kind of is in region to be evaluated, arrange fixing PM2.5 monitoring point, the data recorded using monitoring point are as the PM2.5 concentration in this region, this PM2.5 Concentration Estimation Method data area coverage rate is low, and precision is low, and monitoring equipment is with high costs; Another kind portable in a certain region, gathers PM2.5 concentration, then set up PM2.5 appraising model in conjunction with extraneous factors such as precipitation, wind-force, environment and carry out estimation area PM2.5 concentration, and it is large that this method measures difficulty, and calculation of complex is not easy to operate.

Summary of the invention

The present invention is directed to the deficiency of existing PM2.5 Concentration Estimation Method, deployment convenience, data cover rate high advantage cheap in conjunction with vehicular data acquisition technology, propose a kind of PM2.5 Concentration Estimation Method based on vehicular data acquisition technology.

The present invention is formed primarily of following step: 1, utilize vehicular dust collecting device to gather original PM2.5 concentration data 2, utilize the original PM2.5 concentration data collected to set up the model 3 of probability transfer matrix, the concentration 4 utilizing probability transfer matrix estimation grid data missing point, the display of urban area PM2.5 concentration estimation result.

The concrete steps of the inventive method are:

Step (1), vehicular dust collecting device is utilized to gather original PM2.5 concentration data.Specifically by urban area gridding, path planning traveling pressed by the vehicle carrying dust collecting device, gathers urban area PM2.5 concentration data.

The original PM2.5 concentration data that step (2), utilization collect sets up the model of probability transfer matrix.This step is made up of following 3 sub-steps:

2-1. virtual space Particle diffusion feature.According to Particle diffusion principle, the PM2.5 concentration of central gridding affects by its adjacent mesh PM2.5 concentration with different probability.Therefore, for the grid of shortage of data, the PM2.5 concentration of grid around it can be utilized to estimate the PM2.5 concentration of this grid.

2-2. sets up probability transfer matrix.According to Space Particle diffusion characteristic, set up space lattice PM2.5 concentration probability transfer matrix, be shown below:

$\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{p}_{\mathrm{ij}}=1;0\≤p_{\mathrm{ij}}\≤1$

1≤i≤n，1≤j≤N，c≤N

P in above formula _ijrepresent that grid i affects probability to the PM2.5 concentration of grid j.I represents direction number from 1 to n, n, institute's directive probability and be 1.N represents the number of grid of urban area.

2-3. determines probability transfer matrix P.For the grid of PM2.5 concentration data disappearance, estimate that its PM2.5 concentration is converted into and determine its transition probability P.Utilize the original PM2.5 concentration data collected, select data-intensive region, according to minimum error principle calculating probability transition matrix P, be shown below:

$\min Q=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{(P_i{X}_i-{\mathrm{center}}_i)}^2$

s.t.P _i＝[p _i1p _i2… p _in]

X _i＝[x _i1x _i2… x _in] ^T

$\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{p}_{\mathrm{ij}}=1$

0≤p _ij≤1

0<x _ij

P in above formula _irepresent the probability that grid i spreads to all possible n direction, X _ithe PM2.5 concentration that on n the direction of expression grid i, adjacent mesh records.

Step (3), probability transfer matrix is utilized to estimate the concentration of grid data missing point.For the single-point deletion condition of close quarters, directly utilize probability transfer matrix to estimate the concentration of missing point, be shown below as the PM2.5 concentration x of grid c to be evaluated _cestimation equation, for sparse region property, first finds original alternative concentration with heuristic search, then in the iterative estimation absent region of join probability transition matrix PM2.5 concentration a little.

x _c＝([p _1c，p _2c，…，p _(n-1)c]·[x ₁，x ₂，...，x _(n-1)] ^T)/p _nc

The display of step (4), city grid PM2.5 concentration estimation result.Through above step, obtain the PM2.5 concentration of all grids in urban area.

The invention has the beneficial effects as follows:

(1), vehicular dust collecting device gathers PM2.5 concentration and is easy to dispose, simple to operate;

(2), the inventive method equipment price is cheap, and utilization factor is high;

(3), the PM2.5 concentration precision that utilizes the inventive method estimation to obtain is high, good stability.

Accompanying drawing explanation

Fig. 1 is test scene schematic diagram;

Fig. 2 is PM2.5 grid concentration raw data coverage diagram;

Fig. 3 is Space Particle diffusion characteristic figure;

Fig. 4 is urban area PM2.5 grid concentration estimation result figure.

Embodiment

Below in conjunction with accompanying drawing, the invention will be further described.

PM2.5 grid Concentration Estimation Method concrete steps based on vehicular data acquisition technology are:

Step (1), vehicular dust collecting device is utilized to gather original PM2.5 concentration data.As shown in Figure 1, by urban area gridding, the vehicle carrying dust collecting device gathers urban area PM2.5 concentration data and passes to server by GPRS network.As shown in Figure 2, have the grid of circle to represent testing vehicle and have passed through this grid, namely this grid has PM2.5 concentration data to cover, and represents this grid cover without PM2.5 concentration data without circle grid.

The original PM2.5 concentration data that step (2), utilization collect sets up the model of probability transfer matrix.This step is made up of following 3 sub-steps:

2-1. virtual space Particle diffusion feature.As shown in Figure 3, the PM2.5 of grid Center spreads to its adjacent grid (1,2,3,4) with probability (P1, P2, P3, P4) respectively, and namely the PM2.5 concentration of central gridding affects by its adjacent mesh PM2.5 concentration with different probability.Therefore, for the grid of shortage of data, the PM2.5 concentration of grid around it can be utilized to estimate the PM2.5 concentration of this grid.

2-2. sets up probability transfer matrix.According to Space Particle diffusion characteristic, set up space lattice PM2.5 concentration probability transfer matrix, be shown below:

$\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{p}_{\mathrm{ij}}=1;0\&le;p_{\mathrm{ij}}\&le;1$

1≤i≤n，1≤j≤N，c≤N

P in above formula _ijrepresent that grid i affects probability to the PM2.5 concentration of grid j.I represents direction number from 1 to n, n, institute's directive probability and be 1.N represents the number of grid of urban area.

2-3. determines probability transfer matrix P.For the grid of PM2.5 concentration data disappearance, estimate that its PM2.5 concentration is converted into and determine its transition probability P.Utilize the original PM2.5 concentration data collected, select data-intensive region, according to minimum error principle calculating probability transition matrix P, be shown below:

$\min Q=\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{(P_i{X}_i-{\mathrm{center}}_i)}^2$

s.t.P _i＝[p _i1p _i2… p _in]

X _i＝[x _i1x _i2… x _in] ^T

$\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{p}_{\mathrm{ij}}=1$

0≤p _ij≤1

0<x _ij

P in above formula _irepresent the probability that grid i spreads to all possible n direction, X _ithe PM2.5 concentration that on n the direction of expression grid i, adjacent mesh records.

Step (3), probability transfer matrix is utilized to estimate the concentration of grid data missing point.For the single-point deletion condition of close quarters, directly utilize probability transfer matrix to estimate the concentration of missing point, be shown below as the PM2.5 concentration x of grid c to be evaluated _cestimation equation, for sparse region property, first finds original alternative concentration with heuristic search, then the PM2.5 concentration of all missing data grids of the iterative estimation of join probability transition matrix.

x _c＝([p _1c，p _2c，…，p _(n-1)c]·[x ₁，x ₂，...，x _(n-1)] ^T)/p _nc

The display of step (4), city grid PM2.5 concentration estimation result.Through above step, obtain the PM2.5 concentration of all grids in urban area.As shown in Figure 4, the grid that band circle grid representation testing vehicle covers, i.e. raw data grid, band dot grid represents the grid utilizing the inventive method estimation to obtain PM2.5 concentration.

Claims (1)

1., based on a PM2.5 Concentration Estimation Method for vehicular data acquisition technology, it is characterized in that the method comprises the following steps:

Step (1), utilize vehicular dust collecting device to gather original PM2.5 concentration data, specifically: by urban area gridding, the vehicle carrying dust collecting device press path planning and is travelled, collection urban area PM2.5 concentration data;

The original PM2.5 concentration data that step (2), utilization collect sets up the model of probability transfer matrix, specifically:

2-1. virtual space Particle diffusion feature;

According to Particle diffusion principle, the PM2.5 concentration of central gridding affects by its adjacent mesh PM2.5 concentration with different probability; Therefore, for the grid of shortage of data, utilize the PM2.5 concentration of grid around it to estimate the PM2.5 concentration of this grid;

2 ?2. set up probability transfer matrix;

According to Space Particle diffusion characteristic, set up space lattice PM2.5 concentration probability transfer matrix, be shown below:

$\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{p}_{\mathrm{ij}}=1;0\&le;p_{\mathrm{ij}}\&le;1$

l≤i≤n，1≤j≤N，c≤N

P in above formula _ijrepresent that grid i affects probability to the PM2.5 concentration of grid j; I represents direction number from 1 to n, n, institute's directive probability and be 1, the N number of grid representing urban area;

2 ?3. determine probability transfer matrix P;

For the grid of PM2.5 concentration data disappearance, estimate that its PM2.5 concentration is converted into and determine its transition probability P; Utilize the original PM2.5 concentration data collected, select data-intensive region, according to minimum error principle calculating probability transition matrix P, be shown below:

$\begin{array}{cc}\min & Q=\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{(P_i{X}_i-{\mathrm{center}}_i)}^2\end{array}$

s.t.P _i＝[p _i1p _i2… p _in]

X _i＝[x _i1x _i2… x _in] ^T

$\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{p}_{\mathrm{ij}}=1$

0≤p _ij≤1

0<x _ij

P in above formula _irepresent the probability that grid i spreads to all possible n direction, X _ithe PM2.5 concentration that on n the direction of expression grid i, adjacent mesh records;

Step (3), probability transfer matrix is utilized to estimate the concentration of grid data missing point, specifically: for the single-point deletion condition of close quarters, directly utilize probability transfer matrix to estimate the concentration of missing point, be shown below as the PM2.5 concentration x of grid c to be evaluated _cestimation equation, for sparse region property, first finds original alternative concentration with heuristic search, then in the iterative estimation absent region of join probability transition matrix PM2.5 concentration a little;

x _c＝([p _1c，p _2c，…，p _(n-1)c]·[x ₁，x ₂，…，x _(n-1)] ^T)/p _nc

The display of step (4), city grid PM2.5 concentration estimation result; Through above step, obtain the PM2.5 concentration of all grids in urban area.