CN111695712B - Pollution source tracking system and method thereof - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 36
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- 238000009792 diffusion process Methods 0.000 claims description 9
- 230000005540 biological transmission Effects 0.000 claims description 7
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims description 6
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Abstract
The invention provides a pollution source tracking system and a method thereof, comprising the steps of receiving corresponding sensing data from a plurality of micro sensors in a preset range, interpolating the corresponding sensing data onto a regular grid, carrying out integral operation on the corresponding sensing data from a first time to a second time through an integral algorithm to obtain a comparison calculated value, and comparing the comparison calculated value with a second time data actual value obtained from the same grid position of the grid at the second time, wherein the grid position of the second time data actual value larger than the comparison calculated value is confirmed as a discharge area of the pollution source.
Description
Technical Field
The present invention relates to a tracking system and a method thereof, and more particularly, to a tracking system and a method thereof for tracking a position of a pollution source.
Background
In the existing pollution source tracking method, the sensor vehicle is parked, the data sensed by the sensor is recorded periodically, and the collected data is recorded to present the distribution change situation of the pollutants in the measuring environment.
However, in the existing test method, the parking position of the parked sensor car is limited, so that the target measurement area cannot be uniformly covered, and in addition, the cost for improving the measurement accuracy of the densely parked sensor car is too high.
Moreover, by recording the data sensed by the sensor, only the current pollutant distribution position can be recorded, and if a researcher wants to analyze a pollution source, the researcher needs to analyze the pollution source through an additional analysis flow, so that real-time pollution source analysis and judgment cannot be achieved.
Disclosure of Invention
In order to solve the above-mentioned problems, the present invention provides a pollution source tracking system and a method thereof.
The invention is realized by the following technical scheme:
the invention provides a pollution source tracking system, which comprises:
a plurality of microsensors, each of the microsensors producing sensing data;
and the processing unit is used for receiving the corresponding sensing data, interpolating the corresponding sensing data onto a regular grid, carrying out integral operation on the corresponding sensing data from a first time to a second time through an integral algorithm to obtain a comparison calculation value, and comparing the comparison calculation value with a second time data actual value acquired by the same grid position of the grid at the second time, wherein the grid position with the second time data actual value larger than the comparison calculation value can be confirmed as the emission area of the pollution source.
Preferably, the micro sensor further comprises at least one wind direction sensing unit.
Preferably, the micro sensor further comprises a pollution test item sensing unit, and the pollution test item sensing unit comprises a carbon dioxide sensing unit and an aerosol sensing unit.
The invention also provides a pollution source tracking method, which comprises the following steps:
receiving corresponding sensing data from a plurality of micro sensors within a preset range;
interpolating the corresponding sensory data onto a regular grid;
integrating the corresponding sensing data from the first time to the second time through an integrating algorithm to obtain a comparison calculated value; and
comparing the comparison calculated value with a second time data actual value acquired at a second time by the same grid position of the grid;
wherein the grid position where the second time data actual value is greater than the comparison calculated value may be identified as an emission area of the pollution source.
Preferably, the integration algorithm calculates the pollution test concentration by a two-dimensional horizontal power transmission diffusion mode.
Preferably, the integration algorithm comprises a computational fluid dynamics Lagrangian numerical method.
Preferably, the first time is a starting observation time.
Preferably, the sensing data comprises wind direction data and pollution test item data.
Preferably, grid positions and grid points adjacent to the windward place, where the actual value is larger than the comparison calculated value according to the second time data, are pollution source emission areas.
The invention also provides a pollution source tracking method, which comprises the following steps:
receiving corresponding sensing data from a plurality of micro sensors within a preset range, wherein the sensing data comprises wind direction data and pollution measurement data;
interpolating the corresponding sensory data onto a regular grid;
carrying out integral operation on the corresponding sensing data from the first time to the second time through an integral algorithm, wherein the integral algorithm is used for calculating the concentration of a pollution measurement item through a two-dimensional horizontal power transmission diffusion mode, and obtaining a comparison calculation value by integrating the obtained concentration of the pollution measurement item from the first time to the second time through a hydrodynamic Lagrangian numerical method; and
comparing the comparison calculated value with a second time data actual value acquired at a second time by the same grid position of the grid;
wherein the grid position where the second time data actual value is greater than the comparison calculated value may be identified as an emission area of the pollution source.
The invention has the beneficial effects that:
by the pollution source tracking system and the pollution source tracking method, a plurality of irregularly distributed sensing data can be converted into regular grid distribution, and a researcher can conveniently analyze pollution conditions in a preset range.
According to the pollution source tracking system and the pollution source tracking method provided by the invention, the emission position of the pollution source is predicted in real time through the sensing data measured by the micro sensors.
Drawings
FIG. 1 is a flowchart of a pollution source tracking method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of air quality microsensor station and wind farm station distribution drawn according to a predetermined range boundary in an embodiment of the present invention;
FIG. 3a is a graph showing the concentration of fine aerosol in a pollution test item and the distribution of wind farm at 2 hours 26 minutes according to the concentration of fine aerosol in a pollution test item and wind farm data after objective analysis of weather in an embodiment of the present invention;
FIG. 3b is a graph showing the concentration of fine aerosol in the pollution test item and the wind field distribution at 2-time 29 minutes according to the concentration of fine aerosol in the pollution test item and the wind field data after objective analysis of weather in an embodiment of the present invention;
FIG. 4 is a graph of predicted concentration of fine aerosol for pollution measurements plotted according to a schematic diagram of the concentration of fine aerosol for pollution measurements versus wind field distribution for the pollution measurements at time 26 and 29 of FIGS. 3a and 3b, respectively, according to an embodiment of the present invention;
FIG. 5 is a plot of pollution emission source location plotted according to the pollution test item fine aerosol predicted concentration plot of FIG. 4, in an embodiment of the invention.
Detailed Description
In order to more clearly and completely describe the technical scheme of the invention, the invention is further described below with reference to the accompanying drawings. This inventive concept may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.
Referring to fig. 1, which is a schematic flow chart of a pollution source tracking method according to an embodiment of the invention, the following further describes the flow charts S1 to S4 of the pollution source tracking method according to the invention:
flow S1: corresponding sensing data is received from a plurality of micro sensors within a preset range.
In some embodiments of the present invention, the micro sensors are distributed in a high-density horizontal space and have a high time resolution, for example, the micro sensors include an air box and an air quality micro sensor station, wherein the sensing space covered by each micro sensor can be between a few meters and hundreds of meters, and the time scale of transmitting sensing data of each micro sensor can reach a minute scale.
Further, in some embodiments of the present invention, the sensing data includes wind direction data and pollution measurement data.
Flow S2: corresponding sensor data is interpolated onto a regular grid.
The method comprises the steps of generating a grid wind field and a measured item concentration distribution data of each time interval, wherein the interpolation of the corresponding sensing data to the regular grid can be achieved through a weather objective analysis method, and optionally, in some embodiments of the invention, the grid wind field and the measured item concentration distribution data which are displayed by interpolating the corresponding sensing data to the regular grid at each time can be continuously displayed in real time through a display device.
Flow S3: and carrying out integral operation on the corresponding sensing data from the first time to the second time through an integral algorithm to obtain a comparison calculated value.
Wherein the corresponding sensor data is integrated from the first time to the second time by using a two-dimensional horizontal power transmission diffusion mode, and the pollution measurement item concentration is calculated by using a Lagrangian numerical method, thereby obtaining a comparison calculation value, in other words, a comparison calculation value representing a predicted pollution concentration distribution at the second time is obtained from the first time by the above method.
The first time may be preset as a start observation time or other measurement time.
Flow S4: the comparison calculation value is compared with a second time data actual value acquired at a second time at the same grid position of the grid, and a grid position at which the second time data actual value is larger than the comparison calculation value can be confirmed as an emission region of the pollution source.
In more detail, the actual value of the second time data is subtracted from the comparison calculation value representing the predicted pollution concentration distribution at the second time, and the grid position when the actual value of the second time data is larger than the comparison calculation value is the pollution source emission area.
Alternatively, in some embodiments of the present invention, grid positions where the actual value of the second time data is greater than the calculated value and grid points adjacent to the windward location may be set as the pollution source emission area.
The method for analyzing the pollution source set up in the present invention will be further described by way of an example.
FIG. 2 is a schematic diagram of the distribution of the air quality microsensor stations and the wind farm stations according to a predetermined range boundary in an embodiment of the present invention.
Wherein, as shown in fig. 2, the table boundary in the figure is the analysis range in this embodiment, the dots represent the micro sensor stations in the analysis range, the cross-shaped weathervaning represents the wind field station, and the arrow direction and length extending from the cross-shaped weathervaning represent the wind direction and wind speed.
FIG. 3a is a graph showing the concentration of fine aerosol in a pollution test item and the wind field distribution at 2 hours and 26 minutes according to the concentration of fine aerosol in a pollution test item and the wind field data after objective analysis of weather in an embodiment of the present invention.
FIG. 3b is a graph showing the concentration of fine aerosol in a pollution test item and the wind field distribution at 2 hours and 29 minutes according to the concentration of fine aerosol in a pollution test item and the wind field data after objective analysis of weather in an embodiment of the present invention.
In fig. 3a and 3b, the gray scale color at the bottom of the table represents the concentration distribution of fine suspended particles, and the corresponding color is plotted in fig. 3a and 3b, and the gray scale change in the graph represents the concentration of fine suspended particles of pollution measurement item at the time of 2 and the wind field distribution, and the concentration of fine suspended particles of pollution measurement item at the time of 29 at the time of 2.
FIG. 4 is a graph of predicted concentration of fine aerosol for pollution measurements plotted according to a schematic of the concentration of fine aerosol for pollution measurements versus wind field distribution for the pollution measurements at time 2 at 26 and at time 29 in FIGS. 3a and 3b, according to an embodiment of the present invention.
The two-dimensional horizontal power transmission and diffusion mode uses ground horizontal wind field data and known pollution source concentration distribution, and the distribution situation of the pollution source concentration in different time can be predicted when the pollution source is known along with horizontal wind field advection and diffusion by using the mode.
Further, fig. 4, which is plotted against the pollution test term fine aerosol concentration at 2 at 26 and at 29 in fig. 3a and 3b, is transformed according to the following equation:
wherein C is concentration;(u, v) is a horizontal wind field component; gamma is the turbulence diffusion coefficient, and further, the equation of gamma is: />Wherein CS is Smogorinsky constant, the value of which is an adjustable parameter from 0.1 to 10, and is the average size calculated by numerical value; />
Further, in an embodiment of the present invention, the numerical time integration method of the advection equation is a Lagrangian method.
In an embodiment of the present invention, the differential calculation method for the spatial differential is a medium differential method.
FIG. 5 is a plot of pollution emission source location plotted according to the pollution test item fine aerosol predicted concentration plot of FIG. 4, in an embodiment of the invention.
As shown in fig. 5, the time 2 is divided into a positive area of the observed concentration value minus the predicted concentration value at 29. In fig. 5, the green line is a contour line of positive 5. Dark purple is a contour of positive value 100, and the closed area of the contour lines and the area of the lattice point adjacent to the upwind are the positions of the pollution emission sources.
Further, the present invention also provides a pollution source tracking system, comprising: a plurality of microsensors, each of the microsensors producing sensing data; the processing unit receives the corresponding sensing data, the processing unit interpolates the corresponding sensing data to the regular grid, performs integral operation on the corresponding sensing data from the first time to the second time through an integral algorithm to obtain a comparison calculated value, and compares the comparison calculated value with a second time data actual value obtained from the same grid position of the grid at the second time, wherein the grid position with the second time data actual value larger than the comparison calculated value can be confirmed as an emission area of the pollution source.
In some embodiments of the present invention, the micro sensor further includes at least one wind direction sensing unit.
Alternatively, in some embodiments of the present invention, the microsensor further comprises a pollution test item sensing unit comprising a carbon dioxide sensing unit, an aerosol sensing unit, and a volatile organic sensing unit.
In addition, the present invention further provides a pollution source tracking method, which comprises: receiving corresponding sensing data from a plurality of micro sensors within a preset range, wherein the sensing data comprises wind direction data and pollution measurement item data; interpolating the corresponding sensory data onto a regular grid; carrying out integral operation on the corresponding sensing data from the first time to the second time through an integral algorithm, wherein the integral algorithm is used for calculating the concentration of a pollution measurement item through a two-dimensional horizontal power transmission diffusion mode, and obtaining a comparison calculation value by integrating the obtained concentration of the pollution measurement item from the first time to the second time through a hydrodynamic Lagrangian numerical method; comparing the comparison calculation value with a second time data actual value acquired at a second time by the same grid position of the grid; wherein the grid position where the second time data actual value is greater than the comparison calculated value confirms that the point is the emission area of the pollution source.
The pollution source tracking method and the pollution source tracking system are convenient for coupling the algorithm into the micro sensor and the processing unit connected with the micro sensor, and comprise a large number of micro sensors and the pollution source tracking system distributed in a preset range by means of customization.
In summary, by the pollution source tracking method provided by the invention, a plurality of irregularly distributed sensing data can be converted into regular grid distribution, so that a researcher can further analyze the pollution condition in a preset range, and the researcher can predict the emission position of the pollution source in real time through the sensing data measured by a plurality of micro sensors.
Of course, the present invention can be implemented in various other embodiments, and based on this embodiment, those skilled in the art can obtain other embodiments without any inventive effort, which fall within the scope of the present invention.
Claims (10)
1. A pollution source tracking system, comprising:
a plurality of microsensors, each of the microsensors producing sensing data;
the processing unit is used for receiving the corresponding sensing data, interpolating the corresponding sensing data onto a regular grid, carrying out integral operation on the corresponding sensing data from a first time to a second time through an integral algorithm to obtain a comparison calculated value, and comparing the comparison calculated value with a second time data actual value acquired by the same grid position of the grid at the second time, wherein the second time data actual value is larger than the grid position of the comparison calculated value, and determining the grid position as the emission area of the pollution source.
2. The pollution source tracking system of claim 1, wherein the microsensor further comprises at least one wind direction sensing unit.
3. The pollution source tracking system of claim 1, wherein the microsensor further comprises a pollution test item sensing unit comprising a carbon dioxide sensing unit, an aerosol sensing unit.
4. A method for tracking a source of contamination, comprising:
receiving corresponding sensing data from a plurality of micro sensors within a preset range;
interpolating the corresponding sensory data onto a regular grid;
integrating the corresponding sensing data from the first time to the second time through an integrating algorithm to obtain a comparison calculated value; and
comparing the comparison calculated value with a second time data actual value acquired at a second time by the same grid position of the grid;
wherein the grid position where the second time data actual value is greater than the comparison calculated value is identified as an emission area of the pollution source.
5. The method of claim 4, wherein the integration algorithm calculates the pollution measure concentration by a two-dimensional horizontal power transmission diffusion mode.
6. The method of claim 4, wherein the integration algorithm comprises a computational fluid dynamics Lagrangian numerical method.
7. The method of claim 4, wherein the first time is a start observation time.
8. The method of claim 4, wherein the sensor data comprises wind direction data and pollution test item data.
9. The method of claim 8, wherein grid locations and grid points at the wind up are pollution source discharge areas according to the second time data actual values being greater than the comparison calculated values.
10. A method for tracking a source of contamination, comprising:
receiving corresponding sensing data from a plurality of micro sensors within a preset range, wherein the sensing data comprises wind direction data and pollution measurement data;
interpolating the corresponding sensory data onto a regular grid;
carrying out integral operation on the corresponding sensing data from the first time to the second time through an integral algorithm, wherein the integral algorithm is used for calculating the concentration of a pollution measurement item through a two-dimensional horizontal power transmission diffusion mode, and obtaining a comparison calculation value by integrating the obtained concentration of the pollution measurement item from the first time to the second time through a hydrodynamic Lagrangian numerical method; and
comparing the comparison calculated value with a second time data actual value acquired at a second time by the same grid position of the grid;
wherein the grid position where the second time data actual value is greater than the comparison calculated value is identified as an emission area of the pollution source.
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