Method and equipment for selecting sampling points in natural pollution source area of high-salt sand and dust

Abstract

The invention provides a high-salt sand-dust natural pollution source area sampling point selection method and equipment, and relates to the technical field of insulation detection, and the method comprises the steps: determining a sampling area based on a power pollution area map, a saline-alkali soil distribution map, a power transmission corridor area diagram, a sand storm distribution map and a sand blowing channel distribution map; collecting natural pollution data in a preset sampling time period; establishing a relation model between the pollution intensity of the research area and the environmental pollution factors; based on the natural pollution data and the relation model, combining a random forest algorithm, calculating the contribution degree of the environmental pollution factors to the natural pollution data, and determining the weight distribution result of each sampling area of the research area relative to each environmental factor; according to the preset interval value of the sampling points, the sampling points are reset in the sampling area, and sampling of the natural pollution data is conducted again. By scientifically selecting sampling points, reliable data support is provided for accurately revealing the relationship between the spatial and temporal distribution of the pollution source and the natural pollution source.

Description

Technical Field

[0001] The present application relates to the field of insulation detection technology, and in particular to a method and equipment for selecting sampling points in a high-salinity dust natural pollution source area. Background Art

[0002] my country's desert areas are widely distributed and are my country's new energy base. However, most of the energy transmission lines pass through desert areas with extreme drought, frequent sandstorms and drastic temperature differences. These harsh environments pose a severe challenge to the safety of the power system. The natural pollution from the high-salt sand and dust natural pollution source area has a particularly severe impact on the external insulation of high-voltage equipment, seriously threatening the normal operation of the power system. Sandstorms bring a large amount of high-salt natural pollution, which causes pollution flashover under the conditions of climate shocks, northward movement of rain lines and artificial snowfall, directly causing line tripping and affecting energy transmission. Research on the source-pollution relationship in the high-salt sand and dust natural pollution source area can provide an important scientific basis for improving the anti-pollution ability of power facilities and extending the service life of equipment.

[0003] At present, there are few studies on the source of pollution in saline areas, and the existing sampling point determination method cannot meet the analysis needs of high-salinity sand and dust natural pollution source areas. The traditional point-by-point sampling method is difficult to accurately reveal the relationship between the spatiotemporal distribution of pollution sources and natural pollution sources, which limits the in-depth analysis of pollution source-pollution relationship. Summary of the invention

[0004] The purpose of the present invention is to provide a method and equipment for selecting sampling points in natural pollution source areas of high-salinity dust in order to solve the problem that the traditional point-by-point sampling method is difficult to accurately reveal the relationship between the temporal and spatial distribution of pollution sources and natural pollution sources, which limits the in-depth analysis of pollution source-pollution relationships.

[0005] The above-mentioned purpose of the present application is achieved through the following technical solutions: S1. Determine the sampling area based on the power pollution area map, saline-alkali land distribution map, transmission corridor area schematic diagram, sandstorm distribution map and sand-raising channel distribution map of the study area; S2. Determine the sampling period and collect natural pollution data in the sampling area; S3. Using natural pollution data, establish a relationship model between pollution intensity and environmental pollution factors in the study area; environmental pollution factors include: pollution area level, saline-alkali land level, wind speed level and sandstorm frequency; S4. Based on the natural pollution data and the relationship model, combined with the random forest algorithm, the contribution of environmental pollution factors to the natural pollution data is calculated, and the weight distribution results of each sampling area in the study area relative to each environmental factor are determined; S5. Reset the sampling points in the sampling area according to the weight distribution result and the preset interval value of the sampling points, and re-sample the natural pollution data.

[0006] Optionally, step S1 includes: S11. Obtaining a power pollution area map of the study area; the power pollution area map includes: the scope of the pollution area and the pollution level of the pollution area; S12. Obtain the local saline-alkali land distribution map of the study area, and combine the geographical characteristics of saline-alkali land to clarify the boundary between saline-alkali land and non-saline-alkali area, determine the scope of saline-alkali area and the salt content level of saline-alkali area; S13. Obtain a schematic diagram of the transmission corridor area in the study area and determine the power facility area; S14. Obtain the sandstorm distribution map and the sand-raising channel distribution map of the study area; through the sandstorm distribution map and the sand-raising channel distribution map, analyze and obtain the wind force, frequency and intensity of sandstorms in the study area.

[0007] Optionally, step S1 further includes: The analysis results are obtained by conducting overlapping comparative analysis through the scope of polluted areas, saline-alkali areas and power facility areas; The sampling area is determined by analyzing the results, taking into account the pollution level, salt level, wind speed, frequency and intensity of sandstorms.

[0008] Optionally, step S2 includes: The sampling periods include: before a sandstorm or dust weather occurs, during a sandstorm or dust weather occurs, and after a sandstorm or dust weather occurs; The natural pollution data include: first natural pollution data, second natural pollution data and third natural pollution data; S21. Collect the first natural pollution data before the sandstorm occurs in the sampling area; S22. When sandstorms or dusty weather occur, sampling is carried out to obtain the second natural pollution data; S23. After a sandstorm or dust weather occurs, sampling is carried out to obtain third-party natural pollution data.

[0009] Optionally, step S4 further includes: According to the environmental pollution factor information in the relationship model, adjusting the geographical location of the sampling area; The weight distribution result is updated based on the sampling area adjusted by the geographical location and the calculated contribution.

[0010] Optionally, step S5 includes: According to the weight distribution results, different sampling point intervals are set in each sampling area; The sampling points are arranged using a grid-based method.

[0011] An electronic device comprises a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a method for selecting sampling points in a high-salinity dust natural pollution source area.

[0012] A computer-readable storage medium stores instructions, and when the instructions are executed, a method for selecting sampling points in a high-salinity dust natural pollution source area is executed.

[0013] The beneficial effects of the technical solution provided by this application are: By collecting natural pollution data in a specific sampling period and in a rough sampling area, and analyzing it in combination with various environmental factors, a relationship model is obtained; combined with the random forest algorithm, the weight distribution results of each sampling area relative to each environmental factor are calculated to determine which sampling area needs to set more dense sampling points. In the process of collection, the location of the sampling area is dynamically updated to improve the effect of data sampling. It aims to provide reliable data support for accurately revealing the relationship between the spatiotemporal distribution of pollution sources and natural pollution sources through scientific selection of sampling points. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present application will be further described below with reference to the accompanying drawings and embodiments, in which: Figure 1 is a step diagram in an embodiment of the present application; Figure 2 is a schematic diagram of the sampling area division strategy in an embodiment of the present application; Figure 3 is a flowchart of multiple overlap analysis in an embodiment of the present application; Figure 4 It is a schematic diagram of the structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0015] In order to have a clearer understanding of the technical features, purposes and effects of the present application, the specific implementation methods of the present application are now described in detail with reference to the accompanying drawings.

[0016] An embodiment of the present application provides a method for selecting sampling points in a high-salinity dust natural pollution source area.

[0017] Please refer to Figure 1 , Figure 1 This is a step diagram of a method for selecting sampling points in a high-salinity dust natural pollution source area in an embodiment of the present application, including: S1. Determine the sampling area based on the power pollution area map, saline-alkali land distribution map, transmission corridor area schematic diagram, sandstorm distribution map and sand-raising channel distribution map of the study area; S2. Determine the sampling period and collect natural pollution data in the sampling area; S3. Using natural pollution data, establish a relationship model between pollution intensity and environmental pollution factors in the study area; environmental pollution factors include: pollution area level, saline-alkali land level, wind speed level and sandstorm frequency; As an example, the natural pollution data before, during and after dust storms are comprehensively analyzed to establish a relationship model between pollution intensity and pollution sources (such as salinity, sandstorms, wind, etc.). In particular, attention should be paid to the interaction between salinity and sandstorms, and how to aggravate or mitigate pollution under different climatic conditions and geographical features.

[0018] S4. Based on the natural pollution data and the relationship model, combined with the random forest algorithm, the contribution of environmental pollution factors to the natural pollution data is calculated, and the weight distribution results of each sampling area in the study area relative to each environmental factor are determined; S5. Reset the sampling points in the sampling area according to the weight distribution result and the preset interval value of the sampling points, and re-sample the natural pollution data.

[0019] Step S1 includes: S11. Obtaining a power pollution area map of the study area; the power pollution area map includes: the scope of the pollution area and the pollution level of the pollution area; As an example, the pollution area levels are usually divided into five levels from low to high: a, b, c, d, and e.

[0020] S12. Obtain the local saline-alkali land distribution map of the study area, and combine the geographical characteristics of saline-alkali land to clarify the boundary between saline-alkali land and non-saline-alkali area, determine the scope of saline-alkali area and the salt content level of saline-alkali area; As an example, saline-alkali land is usually divided into slightly saline-alkali land, moderately saline-alkali land, heavily saline-alkali land, and extremely heavily saline-alkali land according to the soil salt content from low to high.

[0021] S13. Obtain a schematic diagram of the transmission corridor area in the study area and determine the power facility area; S14. Obtain the sandstorm distribution map and the sand-raising channel distribution map of the study area; through the sandstorm distribution map and the sand-raising channel distribution map, analyze and obtain the wind force, frequency and intensity of sandstorms in the study area.

[0022] Step S1 also includes: The analysis results are obtained by conducting overlapping comparative analysis through the scope of polluted areas, saline-alkali areas and power facility areas; The sampling area is determined by analyzing the results, taking into account the pollution level, salt level, wind speed, frequency and intensity of sandstorms.

[0023] As an example, the distribution map of sandstorms and dust-raising channels is from the official website of the China Meteorological Administration; overlapping comparative analysis is performed based on the pollution level, soil salinity level, power facility distribution, and sandstorm / dust-raising channel area. Figure 2 , the study area was subdivided into multiple sub-areas with unique characteristics, and similar items were integrated to form sampling areas.

[0024] Step S2 includes: The sampling periods include: before a sandstorm or dust weather occurs, during a sandstorm or dust weather occurs, and after a sandstorm or dust weather occurs; The natural pollution data include: first natural pollution data, second natural pollution data and third natural pollution data; S21. Collect the first natural pollution data before the sandstorm occurs in the sampling area; As an example, by sampling the accumulation of surface pollution in saline-alkali land, desertified areas, and severely polluted areas, the pollution intensity and type of each area are recorded; S22. When sandstorms or dusty weather occur, sampling is carried out to obtain the second natural pollution data; As an example, when a sandstorm or dusty weather occurs, the immediate impact of meteorological factors such as wind speed, wind direction, and dust concentration on pollution should be monitored and compared with the pollution data before the dust.

[0025] S23. After a sandstorm or dust weather occurs, sampling is carried out to obtain third-party natural pollution data.

[0026] As an example, after a sandstorm or dust storm occurs, follow-up sampling of natural pollution is performed, especially the impact on power facilities, and the pollution deposition caused by the sandstorm and its potential damage to the equipment are recorded.

[0027] As an example, the early, middle and late stages of dust emission are divided into three dimensions: particle concentration, wind speed and visibility: Before dust emission: PM10 and PM2.5 concentrations are low and stable, wind speed is below 5-8m / s, and the possibility of dust emission is low. Visibility is high, generally above 10km.

[0028] During dust emission: PM10 concentration rises rapidly to 500 μg / m 3 Above, even up to 1000μg / m 3The PM2.5 concentration also increased significantly. The wind speed reached more than 8m / s, a large amount of dust was generated, and visibility dropped sharply to less than 5km, and in severe cases to less than 1km.

[0029] After the dust is over: the wind speed drops below 5m / s, and the PM10 and PM2.5 concentrations gradually decrease, but will not return to the pre-dust levels in the short term. The PM10 concentration drops to 300μg / m 3 Below, may drop to 100 μg / m 3 Visibility gradually recovered to more than 5 km, but it would take some time for the visibility to be completely clear.

[0030] Step S4 also includes: According to the environmental pollution factor information in the relationship model, adjusting the geographical location of the sampling area; The weight distribution result is updated based on the sampling area adjusted by the geographical location and the calculated contribution.

[0031] Step S5 includes: According to the weight distribution results, different sampling point intervals are set in each sampling area; The sampling points are arranged using a grid-based method.

[0032] As an embodiment, based on the determination of sampling time and space, the selection of sampling points gives priority to the spatial proximity to the transmission corridor. A grid-based point distribution method is adopted to finely arrange the sampling points according to the pollution level. In low-pollution areas (areas with weight distribution less than the preset threshold), the sampling point interval is set to 2 kilometers, while in high-pollution areas (areas with weight distribution greater than or equal to the preset threshold), the sampling point interval is reduced to 0.5 kilometers, ensuring comprehensive coverage of pollution sources and accurate reflection of pollution intensity.

[0033] As an example, the overlapping comparative analysis of data uses multiple overlapping analysis to subdivide each single factor layer into multiple related factors, and introduces the random forest algorithm to evaluate the relative importance of different environmental factors to pollution. In addition, dynamic adjustments are made according to different scenarios during the analysis process, which can provide a more comprehensive perspective. Figure 3 The specific steps are as follows: Data sources include: Power pollution area map (pollution level: a, b, c, d, e) Distribution map of saline-alkali land (soil salinity levels: mild saline-alkali land, moderate saline-alkali land, severe saline-alkali land, extremely severe saline-alkali land) Transmission corridor area diagram Distribution map of sandstorms and dust-raising channels (wind force, frequency and intensity of sandstorms) 1) Data overlap and segmentation Polluted area classification: The polluted area is divided into five levels: a, b, c, d, and e. Each level corresponds to a classification label (such as 0, 1, 2, 3, 4).

[0034] Classification of saline-alkali land: It is divided into different levels according to the salt content of the soil (mild, moderate, severe, extremely severe), and can also be represented by numbers such as 0, 1, 2, 3, etc.

[0035] Dust storm affected areas: divided into different categories according to the frequency and intensity of sandstorms, such as low, medium and high frequency and intensity areas.

[0036] Wind speed and direction: Wind speed can be divided into low, medium and high wind speed levels, while wind direction can be determined through directional analysis to determine its impact on pollution diffusion.

[0037] By overlapping these data layers, a multi-dimensional feature space can be generated for each region. For example, a specific area may be in a "heavy saline-alkali land", "highly polluted area" and "sandstorm channel" at the same time, resulting in it having a high pollution intensity.

[0038] 2) Data Integration Each factor (polluted area level, saline-alkali land level, sandstorm frequency, wind speed level, etc.) is converted into a characteristic variable that can be used by the model to generate a characteristic matrix. The characteristic vector of each sample is composed of a combination of these factors. Specific examples are shown in the following table:

[0039] The present application also discloses an electronic device. Figure 4 , Figure 4 The electronic device 500 may include: at least one processor 501 , at least one network interface 504 , a user interface 503 , a memory 505 , and at least one communication bus 502 .

[0040] The communication bus 502 is used to realize the connection and communication between these components.

[0041] The user interface 503 may include a display screen, and the optional user interface 503 may also include a standard wired interface or a wireless interface.

[0042] The network interface 504 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0043] The present application also discloses a computer-readable storage medium storing a plurality of instructions suitable for loading by a processor to execute the above-mentioned method for selecting sampling points in a high-salinity dust natural pollution source area.

[0044] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure.

[0045] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for selecting sampling points in a high-salinity dust natural pollution source area, characterized in that: The method comprises the following steps: S1. Determine the sampling area based on the power pollution area map, saline-alkali land distribution map, transmission corridor area schematic diagram, sandstorm distribution map and sand-raising channel distribution map of the study area; S2. Determine the sampling period and collect natural pollution data in the sampling area; S3. Using natural pollution data, establish a relationship model between pollution intensity and environmental pollution factors in the study area; Environmental pollution factors include: pollution area level, saline-alkali land level, wind speed level, and dust storm frequency; S4. Based on the natural pollution data and the relationship model, combined with the random forest algorithm, the contribution of environmental pollution factors to the natural pollution data is calculated, and the weight distribution results of each sampling area in the study area relative to each environmental factor are determined; S5. Reset the sampling points in the sampling area according to the weight distribution result and the preset interval value of the sampling points, and re-sample the natural pollution data.

2. A method for selecting sampling points in a high-salinity dust natural pollution source area as claimed in claim 1, characterized in that: Step S1 includes: S11. Obtaining a power pollution area map of the study area; the power pollution area map includes: the scope of the pollution area and the pollution level of the pollution area; S12. Obtain the local saline-alkali land distribution map of the study area, and combine the geographical characteristics of saline-alkali land to clarify the boundary between saline-alkali land and non-saline-alkali area, determine the scope of saline-alkali area and the salt content level of saline-alkali area; S13. Obtain a schematic diagram of the transmission corridor area in the study area and determine the power facility area; S14. Obtain the sandstorm distribution map and the sand-raising channel distribution map of the study area; through the sandstorm distribution map and the sand-raising channel distribution map, analyze and obtain the wind force, frequency and intensity of sandstorms in the study area.

3. A method for selecting sampling points in a high-salinity dust natural pollution source area as claimed in claim 1, characterized in that: Step S1 also includes: The analysis results are obtained by conducting overlapping comparative analysis through the scope of polluted areas, saline-alkali areas and power facility areas; The sampling area is determined by analyzing the results, taking into account the pollution level, salt level, wind speed, frequency and intensity of sandstorms.

4. A method for selecting sampling points in a high-salinity dust natural pollution source area as claimed in claim 1, characterized in that: Step S2 includes: The sampling periods include: before a sandstorm or dust weather occurs, during a sandstorm or dust weather occurs, and after a sandstorm or dust weather occurs; The natural pollution data include: first natural pollution data, second natural pollution data and third natural pollution data; S21. Collect the first natural pollution data before the sandstorm occurs in the sampling area; S22. When sandstorms or dusty weather occur, sampling is carried out to obtain the second natural pollution data; S23. After a sandstorm or dust weather occurs, sampling is carried out to obtain third-party natural pollution data.

5. A method for selecting sampling points in a high-salinity dust natural pollution source area as claimed in claim 1, characterized in that: Step S4 also includes: According to the environmental pollution factor information in the relationship model, adjusting the geographical location of the sampling area; The weight distribution result is updated based on the sampling area adjusted by the geographical location and the calculated contribution.

6. A method for selecting sampling points in a high-salinity dust natural pollution source area as claimed in claim 1, characterized in that: Step S5 includes: According to the weight distribution results, different sampling point intervals are set in each sampling area; The sampling points are arranged using a grid-based method.

7. An electronic device, characterized in that: The electronic device comprises a processor (501), a memory (505), a user interface (503) and a network interface (504), wherein the memory (505) is used to store instructions, the user interface (503) and the network interface (504) are used to communicate with other devices, and the processor (501) is used to execute the instructions stored in the memory (505) so that the electronic device executes the method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed by a computer, the method according to any one of claims 1 to 6 is executed.

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