Water pollution residue monitoring and preventing method and system based on data analysis

Abstract

The invention relates to the technical field of intelligent monitoring of water pollution, and discloses a water pollution residue monitoring, prevention and control method and system based on data analysis, and the system comprises a water pollution state analysis module, a water pollution type and prevention and control scheme analysis module, and a water pollution monitoring, prevention and control analysis result feedback module. According to the water quality characteristic concentration extreme value parameter of the water pollution sampling point, combining with an intelligent search algorithm and the space coordinate parameter of the water pollution sampling point, accurately positioning the space geographic position of the water pollutant emission source of the water pollution monitoring area; according to the water body pollution type identification parameters of the water body monitoring area, an intelligent search algorithm and scientifically stored water body water quality pollution control scheme parameters corresponding to different water body pollution types are combined to accurately analyze a polluted water body water quality control scheme of the water pollution monitoring area, so that the water pollution residue supervision efficiency and effect are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring of water pollution, and in particular to a method and system for monitoring and preventing water pollution residues based on data analysis. Background Art

[0002] Water pollution residue monitoring takes the water environment as the object, and uses physical, chemical and biological technical means to conduct qualitative, quantitative and systematic comprehensive analysis of the pollutants and their related components, in order to explore and study the changing laws of water environment quality. Water pollution residue monitoring provides reliable basic data for water environment management and provides a scientific basis for the evaluation of the effectiveness of governance measures. In order for the monitoring data to accurately reflect the current quality of the water environment and predict the development trend of water environment pollution, water pollution residue monitoring data should be representative, accurate, precise, parallel, repeatable, complete and comparable; water pollution residue monitoring has become an important means of protecting water sources. The existing water pollution residue monitoring cannot accurately identify the geographical location of water pollution emission sources, nor can it scientifically analyze water pollution types and water pollution prevention and control plans, which reduces the effectiveness and reliability of water pollution residue monitoring.

[0003] A Chinese invention patent with announcement number CN116819029B discloses a river water pollution monitoring method and system, which collects water quality sensor data, sensor node location information and combines numerical analysis to scientifically analyze the water quality deterioration parameters at the node location, and cooperates with a neural network algorithm to analyze the pollution prediction area and pollution prediction degree of the target river and provide alarm information, thereby realizing intelligent and scientific evaluation of the pollution area and pollution degree of the target river water pollution monitoring; however, the above technical solution cannot identify the source of water pollution discharge in the target river, nor can it scientifically analyze the prevention and control treatment plan of water pollution, which reduces the applicability and quality of river water pollution monitoring. Summary of the invention

[0004] 1. Technical issues to be resolved In order to solve the problem that the existing water pollution residual monitoring cannot accurately identify the geographical location of water pollution emission sources, nor can it scientifically analyze water pollution types and water pollution prevention and control plans, thereby reducing the effectiveness and reliability of water pollution residual monitoring, the above purposes are achieved by accurately collecting water quality characteristic parameters of sampling points in water pollution monitoring areas, scientifically analyzing water pollution status in water pollution monitoring areas, accurately locating the geographical location of water pollution emission sources, intelligently identifying water pollution types in water pollution monitoring areas, and accurately analyzing water pollution prevention and control plans.

[0005] (II) Technical solution The present invention is implemented by the following technical scheme: a water pollution residue monitoring and prevention method based on data analysis, the method comprising the following steps: S1. Collect water quality characteristic concentration data of water bodies at water pollution sampling points and spatial coordinate data of sampling points in water pollution monitoring areas; S2, analyzing and processing the water pollution status of the water pollution monitoring area according to the water quality characteristic concentration data of the water body at the water pollution sampling point and the water quality characteristic concentration data of the standard polluted water body, generating water pollution status analysis data of the water pollution monitoring area, and directly ending the water pollution monitoring operation when it is in a normal state; S3, when it is in a pollution state, based on the water quality characteristic concentration data of the water body at the water pollution sampling point, the water quality characteristic concentration maximum value analysis and processing of the water body at the sampling point in the water pollution monitoring area is performed to generate the water quality characteristic concentration maximum value data of the water body at the water pollution sampling point; S4, according to the water quality characteristic concentration maximum value parameters and spatial coordinate parameters of the water pollution sampling points, the spatial geographical location identification and processing of the water pollutant emission sources in the water pollution monitoring area are performed to construct the spatial coordinate data of the water pollution emission sources in the water pollution monitoring area; S5, measuring the average characteristic concentration of water quality of water bodies at the water pollution sampling points and identifying the water pollution types in the water pollution monitoring area with the water quality characteristic concentration data corresponding to different water pollution types, and generating water pollution type identification data in the water pollution monitoring area; S6, analyzing and processing the water quality prevention and control plan for the polluted water bodies in the water pollution monitoring area according to the water pollution type identification data of the water body monitoring area and the water quality prevention and control plan data corresponding to different water pollution types, and generating water quality prevention and control plan analysis data for the water pollution monitoring area; S7. Construct water pollution monitoring and prevention analysis result data and perform water pollution monitoring and prevention analysis result feedback operations.

[0006] Preferably, the operation steps of collecting water quality characteristic concentration data of water bodies at water pollution sampling points and spatial coordinate data of sampling points in water pollution monitoring areas are as follows: S11. Collect water quality characteristic concentration parameters of each water pollution sampling point randomly selected from the target water pollution monitoring area online through water body monitoring sensors, and generate a water quality characteristic concentration data set of the water pollution sampling points , ;in Indicates the collected The water quality characteristic concentration data of the water pollution sampling points corresponding to the water pollution sampling points, Indicates the maximum value of the number of water pollution sampling points, the water body monitoring sensors include pH sensors, dissolved oxygen sensors, redox potential sensors, ammonia nitrogen sensors, turbidity sensors and total organic carbon sensors; water quality characteristic concentration parameters include turbidity concentration, pH value, ammonia nitrogen concentration, chemical oxygen demand, nitrite concentration, chloride concentration, lead heavy metal concentration, chromium heavy metal concentration, organophosphorus pesticide concentration and organochlorine pesticide concentration of water quality in the target water pollution monitoring area; The spatial position coordinate parameters of each randomly selected water pollution sampling point in the target water pollution monitoring area are collected online through the position sensor, and the spatial coordinate data set of the sampling points in the water pollution monitoring area is generated. ,in Indicates the collected The spatial coordinate data of the sampling points in the water pollution monitoring area corresponding to the water pollution sampling points are obtained, and the spatial coordinate data of the sampling points in the pollution monitoring area include the longitude, latitude and altitude of the sampling points.

[0007] The present invention uses water body monitoring sensors and position sensors to accurately and dynamically collect water quality characteristic concentration parameters and spatial position parameters of water pollution sampling points, thereby providing reliable data support for scientific analysis of water pollution status and water pollution emission source locations in water pollution monitoring areas.

[0008] Preferably, the water pollution status analysis and processing of the water pollution monitoring area is performed based on the water quality characteristic concentration data of the water body at the water pollution sampling point and the water quality characteristic concentration data of the standard polluted water body, and the water pollution status analysis data of the water pollution monitoring area is generated. When it is in a normal state, the operation steps of directly ending this water pollution monitoring operation are as follows: S21. Establish a data set of water quality characteristic concentrations of standard polluted water bodies , ;in Indicates The water quality characteristic concentration data of standard polluted water bodies corresponding to the water quality characteristic types of water bodies, Indicates the maximum value of the number of water quality characteristic types of a water body; the standard polluted water quality characteristic concentration data indicates the standard concentration range of water quality characteristic parameters of a water body in a polluted state; water quality characteristic types of a water body include turbidity characteristic type, pH value characteristic type, ammonia nitrogen characteristic type, chemical oxygen demand characteristic type, nitrite characteristic type, chloride characteristic type, lead heavy metal characteristic type, chromium heavy metal characteristic type, organophosphorus pesticide characteristic type and organochlorine pesticide characteristic type; S22, the water quality characteristic concentration data set of the water pollution sampling point The water quality characteristic concentration data of the water pollution sampling points mentioned in The water quality characteristic concentration data set of the standard polluted water body is sorted according to the water pollution sampling point number and water quality characteristic type number. The water quality characteristic concentration data of the standard polluted water body described in Carry out numerical comparison of water quality characteristic concentrations, and generate water pollution status analysis data of water pollution monitoring areas based on the results of numerical comparison of water quality characteristic concentrations ; when and The water quality characteristic concentration value comparison of the water body was successful, indicating that The water bodies at the water pollution sampling points If the water quality characteristic concentration of a water body exceeds the standard, the water pollution status analysis data of the water pollution monitoring area will be output It is a polluted state; when and If the water quality characteristic concentration values ​​of the water body are not successfully compared, it means that the water quality characteristic concentrations of the water body in the target water pollution monitoring area are not exceeded, then the water pollution status analysis data of the water pollution monitoring area will be output. It is in normal state, and the water pollution monitoring operation is terminated directly at this time.

[0009] The present invention achieves the effect of autonomous and accurate assessment of the water pollution status in the water pollution monitoring area by performing intelligent analysis of the water pollution status in the water pollution monitoring area based on the characteristic concentration parameters of the water quality at the water pollution sampling point and the characteristic concentration parameters of the water quality of the standard polluted water body.

[0010] Preferably, when the pollution state occurs, the maximum value analysis and processing of the water quality characteristic concentration of the water body at the sampling point in the water pollution monitoring area is performed based on the water quality characteristic concentration data of the water body at the water pollution sampling point, and the operation steps of generating the maximum value data of the water quality characteristic concentration of the water body at the water pollution sampling point are as follows: S31, when the water pollution status analysis data of the water pollution monitoring area When the water is in a polluted state, the water quality characteristic concentration data set of the water pollution sampling point The water quality characteristic concentration data of the water pollution sampling points mentioned in Compare the water quality characteristic concentration values ​​of the water body in order according to the water pollution sampling point number, and select the water quality characteristic concentration data of the water pollution sampling point with the largest water quality characteristic concentration value , and generate the maximum value data of water quality characteristic concentration of water body at water pollution sampling point through data identification .

[0011] The present invention achieves the effect of providing real data support for accurately locating the spatial position of the source of water pollutant discharge by accurately screening out the maximum value parameters of water quality characteristic concentration of water bodies at water pollution sampling points based on numerical analysis.

[0012] Preferably, the steps of performing spatial geographic location identification processing of the water body pollutant emission source in the water pollution monitoring area according to the water quality characteristic concentration maximum value parameter and the spatial coordinate parameter of the water pollution sampling point to construct the spatial coordinate data of the water pollution emission source in the water pollution monitoring area are as follows: S41, obtaining the maximum value data of water quality characteristic concentration of the water body at the water pollution sampling point and the spatial coordinate data set of the sampling points in the water pollution monitoring area ; S42, using the KD tree nearest neighbor search algorithm based on the maximum water quality characteristic concentration data of the water body at the water pollution sampling point The corresponding water pollution sampling point number character is the spatial coordinate data set of the sampling point in the water pollution monitoring area Search for the maximum value data of water quality characteristic concentration of the water body at the water pollution sampling point Spatial coordinate data of the sampling points in the water pollution monitoring area corresponding to the water pollution sampling points , and through data identification, the spatial coordinate data of water pollution emission sources in the water pollution monitoring area is constructed The spatial coordinate data of the water pollution emission sources in the water pollution monitoring area represent the spatial position coordinate parameters of the water pollutant emission sources in the target water pollution monitoring area.

[0013] The present invention achieves the effect of efficiently and accurately locating the geographical location of water pollution emission sources in the water pollution monitoring area by accurately analyzing the spatial geographical location of water pollutant emission sources in the water pollution monitoring area according to the maximum value parameters of water quality characteristic concentration of water bodies at water pollution sampling points in combination with the KD tree nearest neighbor search algorithm and the spatial coordinate parameters of water pollution sampling points.

[0014] Preferably, the mean water quality characteristic concentration of the water body at the water pollution sampling point is measured and the water quality characteristic concentration data corresponding to different water pollution types are used to identify the water pollution type in the water pollution monitoring area, and the operation steps for generating water pollution type identification data in the water pollution monitoring area are as follows: S51, collecting water quality characteristic concentration data of the water body at the water pollution sampling point The water quality characteristic concentration data of the water pollution sampling points mentioned in According to the water pollution sampling point number and water quality characteristic keywords, the water quality characteristic concentration mean of the water body is processed in order to measure the water quality characteristic concentration mean of the water pollution sampling point. ,in ; S52. Establish a data set of water quality characteristic concentrations corresponding to different water pollution types , ;in Indicates The water quality characteristic concentration data of different water pollution types corresponding to the water pollution types are matched. Indicates the maximum value of the number of water pollution types, and the water quality characteristic concentration data corresponding to different water pollution types indicate the standard concentration range of water quality characteristic parameters corresponding to different water pollution types; water pollution types include heavy metal pollution type, inorganic pollution type, organic pollution type, chemical pollution type, and highly toxic pollution type; S53, the water quality characteristic concentration average of the water body at the water pollution sampling point A data set of water quality characteristic concentrations corresponding to the different water pollution types The water quality characteristic concentration data corresponding to the different water pollution types described in According to the water quality characteristic type character of the water body, the water quality characteristic concentration value of the water body is matched, and the average water quality characteristic concentration of the water body at the water pollution sampling point is searched out. The water quality characteristic concentration data corresponding to the different water pollution types matched Corresponding water pollution types, and construct water pollution type identification data for water pollution monitoring areas , execute to generate water pollution type identification data of the water pollution monitoring area The specific steps are as follows: S531, initialization parameters, update water pollution type search crow population, maximum number of iterations, flight distance ; S532, initializing the water pollution type to search for crow individuals in the water quality characteristic concentration data set corresponding to the different water pollution types The initial position and memory in the search space, The crows searching for water pollution types are randomly distributed in a multidimensional search space, namely The spatial dimension of the random distribution of crows searching for water pollution types is The water quality characteristic concentration data set corresponding to the different water pollution types In the search space; in the first iteration, it is assumed that the water pollution type search crow individual hides the food at the initial position; that is, in the first iteration, it is assumed that the water pollution type search crow individual hides the water quality characteristic concentration mean of the water pollution sampling point A data set of water quality characteristic concentrations corresponding to the different water pollution types The water quality characteristic concentration data corresponding to the different water pollution types at the initial position in the search space Match the water quality characteristic concentration values ​​of water bodies according to the water quality characteristic type characters; S533, calculating the individual fitness value of each water pollution type searching crow, that is, calculating the average characteristic concentration of water quality of the water body at the water pollution sampling point A data set of water quality characteristic concentrations corresponding to the different water pollution types The water quality characteristic concentration data corresponding to the different water pollution types in the search space The fitness value of S534, updating the water pollution type to search for crow individuals in the water quality characteristic concentration data set corresponding to the different water pollution types The position in the search space and the water pollution type search formula for the individual position update of the crow are as follows: ,in Indicates Iteration water pollution type search crow individual The water quality characteristic concentration data set corresponding to the different water pollution types The new position in the search space, Indicates Iteration water pollution type search crow individual The water quality characteristic concentration data set corresponding to the different water pollution types The position in the search space, represents a random number uniformly distributed between [0, 1], Indicates Iteration water pollution type search crow individual The water quality characteristic concentration data set corresponding to the different water pollution types The flight distance in the search space, Indicates Iteration water pollution type search crow individual The water quality characteristic concentration data set corresponding to the different water pollution types The food hiding location in the search space, i.e. Iteration water pollution type search crow individual The water quality characteristic concentration data set corresponding to different water pollution types Search the search space to find the mean water quality characteristic concentration of the water body at the water pollution sampling point The water quality characteristic concentration data corresponding to the different water pollution types matched location; S535, determine the feasibility of the new position, determine the feasibility of the new position of each water pollution type search crow individual; if the new position of the water pollution type search crow individual is feasible, the water pollution type search crow individual will update its position, that is, in the water quality characteristic concentration data set corresponding to the different water pollution types Search the search space to find the mean water quality characteristic concentration of the water body at the water pollution sampling point The water quality characteristic concentration data corresponding to the different water pollution types matched The water pollution type, the water pollution type search crow individual is updated to the water quality characteristic concentration data corresponding to the different water pollution types that are successfully matched Otherwise, the water pollution type searching crow individual stays at the current location and does not move to the new location; S536, evaluate the fitness value of the new position, calculate the fitness value of each water pollution type search crow's individual new position, that is, calculate the water quality characteristic concentration data set corresponding to the different water pollution types The mean concentration of water quality characteristics of the water body at the water pollution sampling point in the search space The water quality characteristic concentration data corresponding to the different water pollution types at the new location The fitness value of S537, update memory, if the fitness value of the new position of the water pollution type search crow is greater than the fitness value of the initial position in the memory, the water pollution type search crow updates its memory through the new position, otherwise it does not update its memory; that is, in the water quality characteristic concentration data set corresponding to the different water pollution types Search the search space to find the mean water quality characteristic concentration of the water body at the water pollution sampling point The water quality characteristic concentration data corresponding to the different water pollution types with the largest fitness value Types of water pollution; S538. When the maximum number of iterations is met, output the mean concentration of water quality characteristics of the water body at the water pollution sampling point. The water quality characteristic concentration data corresponding to the different water pollution types matched The water pollution type of the water body is identified and the water pollution type identification data of the water pollution monitoring area is constructed through data identification. .

[0015] The present invention achieves the effect of accurately identifying the water pollution type in the water pollution monitoring area by comprehensively and accurately analyzing the water pollution types in the water pollution monitoring area through measuring the mean water quality characteristic concentration of water bodies at water pollution sampling points based on numerical processing and combining the crow optimization algorithm with the standard preset water quality characteristic concentration parameters corresponding to different water pollution types, thereby achieving the effect of accurately identifying the water pollution type in the water pollution monitoring area.

[0016] Preferably, the steps of analyzing and processing the water quality prevention and control plan of the polluted water body in the water pollution monitoring area according to the water pollution type identification data of the water body monitoring area and the water quality prevention and control plan data corresponding to different water pollution types to generate the water quality prevention and control plan analysis data of the water body in the water pollution monitoring area are as follows: S61. Establish a data set of water pollution prevention and control plans for different water pollution types ,in Indicates water body pollution prevention and control plan data corresponding to different water body pollution types that match the water body pollution types, wherein the water body pollution prevention and control plan data corresponding to different water body pollution types represent the standard polluted water body water quality prevention and control treatment process and process equipment data used for different water body pollution types; S62, using a depth-first search algorithm to identify the water pollution type in the water pollution monitoring area Data set of water pollution prevention and control plans corresponding to different water pollution types Data on water quality pollution prevention and control plans for different water pollution types described in Perform water pollution type keyword matching to search for water pollution type identification data in the water pollution monitoring area The corresponding water pollution prevention and control plan data for the different water pollution types , and generate water quality prevention and control plan analysis data for water pollution monitoring areas through data identification .

[0017] The present invention achieves the effect of integrated management of polluted water body monitoring and prevention in the water pollution monitoring area by accurately analyzing the water quality prevention and control plan for polluted water bodies in the water pollution monitoring area based on the water pollution type identification parameters in the water body monitoring area combined with the depth-first search algorithm and the scientifically stored water quality pollution prevention and control plan parameters corresponding to different water pollution types.

[0018] Preferably, the steps of constructing the water pollution monitoring and prevention analysis result data and performing the water pollution monitoring and prevention analysis result feedback operation are as follows: S71, analyzing the water pollution status of the water pollution monitoring area , spatial coordinate data of water pollution emission sources in the water pollution monitoring area , water pollution type identification data in the water pollution monitoring area , water quality control plan analysis data of the water pollution monitoring area After data combination, water pollution monitoring and prevention analysis result data is constructed ; S72, the water pollution monitoring and prevention analysis result data Feedback is pushed to the water pollution residue monitoring platform through the Internet of Things communication network to execute the water pollution monitoring and prevention analysis results feedback task.

[0019] The present invention achieves the effect of efficient collection and accurate push of water pollution residue supervision result information by scientifically constructing water pollution monitoring and prevention analysis result information and pushing it online to the water pollution residue monitoring platform through the Internet of Things communication network.

[0020] A water pollution residue monitoring and prevention system based on data analysis, used to implement the water pollution residue monitoring and prevention method based on data analysis, the system includes a water pollution state analysis module, a water pollution type and prevention and control plan analysis module, and a water pollution monitoring and prevention analysis result feedback module; The water pollution status analysis module includes a water quality characteristic concentration acquisition unit for water pollution sampling points, a spatial coordinate acquisition unit for sampling points in water pollution monitoring areas, a standard polluted water quality characteristic concentration storage unit, and a water pollution status analysis unit for water pollution monitoring areas; The water quality characteristic concentration acquisition unit of the water body at the water pollution sampling point collects the water quality characteristic concentration data of the water body at the water pollution sampling point through the water body monitoring sensor; the spatial coordinate acquisition unit of the sampling point in the water pollution monitoring area collects the spatial coordinate data of the sampling point in the water pollution monitoring area through the position sensor; the water quality characteristic concentration storage unit of the standard polluted water body is used to store the water quality characteristic concentration data of the standard polluted water body; the water pollution status analysis unit of the water pollution monitoring area performs water pollution status analysis processing in the water pollution monitoring area according to the water quality characteristic concentration data of the water body at the water pollution sampling point and the water quality characteristic concentration data of the standard polluted water body, and generates water pollution status analysis data of the water pollution monitoring area; The water pollution type and prevention and control scheme analysis module includes a water pollution sampling point water quality characteristic concentration maximum value analysis unit, a water pollution discharge source geographical location identification unit, a water pollution sampling point water quality characteristic concentration mean value measurement unit, a water quality characteristic concentration storage unit corresponding to different water pollution types, a water pollution type identification unit in a water pollution monitoring area, a water quality prevention and control scheme storage unit corresponding to different water pollution types, and a water pollution prevention and control scheme analysis unit in a water pollution monitoring area; The water pollution sampling point water quality characteristic concentration maximum value analysis unit performs water quality characteristic concentration maximum value analysis processing of the water pollution sampling point water quality characteristic concentration data in the water pollution monitoring area based on the water pollution sampling point water quality characteristic concentration data, and generates water quality characteristic concentration maximum value data of the water pollution sampling point water quality; the water pollution emission source geographical location identification unit performs spatial geographical location identification processing of the water body pollutant emission source in the water pollution monitoring area according to the water quality characteristic concentration maximum value parameters and spatial coordinate parameters of the water pollution sampling point water quality characteristic concentration, and constructs the spatial coordinate data of the water pollution emission source in the water pollution monitoring area; the water pollution sampling point water quality characteristic concentration mean value measurement unit is used to measure the water quality characteristic concentration mean value of the water pollution sampling point water quality; the water quality characteristic concentration storage unit corresponding to different water pollution types is used to store the water quality characteristic concentration storage units corresponding to different water pollution types. Water quality characteristic concentration data; the water pollution type identification unit in the water pollution monitoring area performs water pollution type identification processing in the water pollution monitoring area according to the water quality characteristic concentration mean value of the water pollution sampling point and the water quality characteristic concentration data corresponding to different water pollution types, and generates water pollution type identification data in the water pollution monitoring area; the water quality prevention and control plan storage unit corresponding to different water pollution types is used to store water quality prevention and control plan data corresponding to different water pollution types; the water pollution prevention and control plan analysis unit in the water pollution monitoring area performs water quality prevention and control plan analysis processing in the water pollution monitoring area according to the water pollution type identification data in the water pollution monitoring area and the water quality prevention and control plan data corresponding to different water pollution types, and generates water quality prevention and control plan analysis data in the water pollution monitoring area; The water pollution monitoring and prevention analysis result feedback module includes a water pollution monitoring and prevention analysis result acquisition unit and a water pollution monitoring and prevention analysis result feedback unit; The water pollution monitoring and prevention analysis result acquisition unit is used to construct water pollution monitoring and prevention analysis result data; the water pollution monitoring and prevention analysis result feedback unit performs water pollution monitoring and prevention analysis result feedback operations based on the water pollution monitoring and prevention analysis result data.

[0021] (III) Beneficial effects The present invention provides a method and system for monitoring and preventing water pollution residues based on data analysis. It has the following beneficial effects: 1. Accurately and dynamically collect water quality characteristic concentration parameters and spatial position parameters of water pollution sampling points through water body monitoring sensors and position sensors, and provide reliable data support for scientific analysis of water pollution status and water pollution emission source locations in water pollution monitoring areas; intelligently analyze water pollution status in water pollution monitoring areas based on water quality characteristic concentration parameters of water pollution sampling points and water quality characteristic concentration parameters of standard polluted water bodies, realize autonomous and accurate assessment of water pollution status in water pollution monitoring areas, and improve the efficiency of water pollution residue monitoring.

[0022] 2. Accurately screen out the maximum value parameters of water quality characteristic concentration of water bodies at water pollution sampling points based on numerical analysis, and provide real data support for accurately locating the spatial location of the source of water pollutant emissions; accurately analyze the spatial geographical location of the source of water pollutant emissions in the water pollution monitoring area according to the maximum value parameters of water quality characteristic concentration of water bodies at water pollution sampling points combined with intelligent search algorithms and spatial coordinate parameters of water pollution sampling points, and realize efficient and accurate geographical location positioning of water pollution emission sources in the water pollution monitoring area; comprehensively and accurately analyze the water pollution types in the water pollution monitoring area based on the numerical processing and measurement of the mean value of water quality characteristic concentration of water bodies at water pollution sampling points combined with intelligent recognition algorithms and standard preset water pollution characteristic concentration parameters corresponding to different water pollution types, realize accurate identification of water pollution types in the water pollution monitoring area, and improve the quality of water pollution residue monitoring; accurately analyze the water quality prevention and control plan of polluted water bodies in the water pollution monitoring area according to the water pollution type identification parameters of the water body monitoring area combined with intelligent search algorithms and scientifically stored water pollution prevention and control plan parameters corresponding to different water pollution types, realize integrated management of polluted water monitoring and prevention in the water pollution monitoring area, and improve the efficiency and effectiveness of water pollution residue supervision.

[0023] 3. Through the combination of pollution status analysis parameters of the water pollution monitoring area, location information of water pollutant emission sources, water pollution types and water pollution prevention and control plans, combined with data processing, scientifically construct water pollution monitoring and prevention analysis result information, and improve the collection efficiency and security of water pollution residue supervision and processing information; the water pollution monitoring and prevention analysis results are pushed online through the Internet of Things communication network to the water pollution residue monitoring platform, so as to realize efficient and accurate push of water pollution residue supervision result information and improve the response efficiency of water pollution residue supervision results. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic diagram of a module of a water pollution residue monitoring and prevention system based on data analysis provided by the present invention; Figure 2 A flow chart of a water pollution residue monitoring and prevention method based on data analysis provided by the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] The embodiment of the water pollution residue monitoring and prevention method and system based on data analysis is as follows: Embodiment 1: See also Figure 1 - Figure 2 , a water pollution residue monitoring and prevention method based on data analysis, the method comprises the following steps: S1. Collect water quality characteristic concentration data of water bodies at water pollution sampling points and spatial coordinate data of sampling points in water pollution monitoring areas; S2. Analyze and process the water pollution status of the water body in the water pollution monitoring area based on the water quality characteristic concentration data of the water body at the water pollution sampling point and the water quality characteristic concentration data of the standard polluted water body, and generate water pollution status analysis data of the water pollution monitoring area. When it is in a normal state, directly end this water pollution monitoring operation; S3. When the water is in a polluted state, the water quality characteristic concentration maximum value analysis and processing of the water quality characteristic concentration of the water body at the sampling point in the water pollution monitoring area is performed based on the water quality characteristic concentration data of the water body at the water pollution sampling point to generate the maximum value data of the water quality characteristic concentration of the water body at the water pollution sampling point; S4, according to the water quality characteristic concentration maximum value parameters and spatial coordinate parameters of the water pollution sampling points, the spatial geographical location identification and processing of the water pollutant emission sources in the water pollution monitoring area are performed to construct the spatial coordinate data of the water pollution emission sources in the water pollution monitoring area; S5, measuring the average characteristic concentration of water quality of water bodies at the water pollution sampling points and identifying the water pollution types in the water pollution monitoring area with the water quality characteristic concentration data corresponding to different water pollution types, and generating water pollution type identification data in the water pollution monitoring area; S6. Analyze and process the water quality prevention and control plan for polluted water bodies in the water pollution monitoring area based on the water pollution type identification data of the water body monitoring area and the water quality prevention and control plan data corresponding to different water pollution types, and generate water quality prevention and control plan analysis data for the water body in the water pollution monitoring area; S7. Construct water pollution monitoring and prevention analysis result data and perform water pollution monitoring and prevention analysis result feedback operations.

[0027] For further information, see Figure 1 - Figure 2 The steps for collecting water quality characteristic concentration data of water pollution sampling points and spatial coordinate data of sampling points in water pollution monitoring areas are as follows: S11. Collect water quality characteristic concentration parameters of each water pollution sampling point randomly selected from the target water pollution monitoring area online through water body monitoring sensors, and generate a water quality characteristic concentration data set of the water pollution sampling points , ;in Indicates the collected The water quality characteristic concentration data of the water pollution sampling points corresponding to the water pollution sampling points, Indicates the maximum number of water pollution sampling points. Water body monitoring sensors include pH sensors, dissolved oxygen sensors, redox potential sensors, ammonia nitrogen sensors, turbidity sensors and total organic carbon sensors. Water quality characteristic concentration parameters include turbidity concentration, pH value, ammonia nitrogen concentration, chemical oxygen demand, nitrite concentration, chloride concentration, lead heavy metal concentration, chromium heavy metal concentration, organophosphorus pesticide concentration and organochlorine pesticide concentration of water quality in the target water pollution monitoring area. The spatial position coordinate parameters of each randomly selected water pollution sampling point in the target water pollution monitoring area are collected online through the position sensor, and the spatial coordinate data set of the sampling points in the water pollution monitoring area is generated. ,in Indicates the collected The spatial coordinate data of the sampling points in the water pollution monitoring area corresponding to the water pollution sampling points, the spatial coordinate data of the sampling points in the pollution monitoring area include the longitude, latitude and altitude of the sampling points.

[0028] According to the characteristic concentration data of water quality at the water pollution sampling point and the characteristic concentration data of water quality of the standard polluted water body, the water pollution status of the water pollution monitoring area is analyzed and processed to generate the water pollution status analysis data of the water pollution monitoring area. When it is in a normal state, the operation steps to directly end this water pollution monitoring operation are as follows: S21. Establish a data set of water quality characteristic concentrations of standard polluted water bodies , ;in Indicates The water quality characteristic concentration data of standard polluted water bodies corresponding to the water quality characteristic types of water bodies, Indicates the maximum value of the number of water quality characteristic types of water bodies; standard polluted water quality characteristic concentration data indicates the standard concentration range of water quality characteristic parameters of water bodies in a polluted state; water quality characteristic types of water bodies include turbidity characteristic type, pH value characteristic type, ammonia nitrogen characteristic type, chemical oxygen demand characteristic type, nitrite characteristic type, chloride characteristic type, lead heavy metal characteristic type, chromium heavy metal characteristic type, organophosphorus pesticide characteristic type and organochlorine pesticide characteristic type; S22. Collect the characteristic concentration data of water quality at the water pollution sampling point Water quality characteristic concentration data of water bodies at the sampling points for reclaimed water pollution The water quality characteristic concentration data set of polluted water bodies is ordered according to the water pollution sampling point number and water quality characteristic type number. Water quality characteristic concentration data of medium standard polluted water bodies Carry out numerical comparison of water quality characteristic concentrations, and generate water pollution status analysis data of water pollution monitoring areas based on the results of numerical comparison of water quality characteristic concentrations ; when and The water quality characteristic concentration value comparison of the water body was successful, indicating that The water bodies at the water pollution sampling points If the water quality characteristic concentration of a water body exceeds the standard, the water pollution status analysis data of the water pollution monitoring area will be output It is a polluted state; when and If the water quality characteristic concentration values ​​of the water body are not successfully compared, it means that the water quality characteristic concentrations of the water body in the target water pollution monitoring area are not exceeded, then the water pollution status analysis data of the water pollution monitoring area will be output. It is in normal state, and the water pollution monitoring operation is terminated directly at this time.

[0029] Through the cooperation of the water quality characteristic concentration collection unit at the water pollution sampling point and the spatial coordinate collection unit at the sampling point in the water pollution monitoring area, water monitoring sensors and position sensors are used to accurately and dynamically collect the water quality characteristic concentration parameters and spatial position parameters of the water pollution sampling point, so as to provide reliable data support for the scientific analysis of the water pollution status and the location of the water pollution emission source in the water pollution monitoring area; the water pollution status analysis unit in the water pollution monitoring area conducts intelligent analysis of the water pollution status in the water pollution monitoring area based on the water quality characteristic concentration parameters of the water pollution sampling point and the water quality characteristic concentration parameters of the standard polluted water body, so as to realize the autonomous and accurate assessment of the water pollution status in the water pollution monitoring area and improve the efficiency of water pollution residue monitoring.

[0030] For further information, see Figure 1 - Figure 2 When it is in a polluted state, the water quality characteristic concentration maximum value analysis and processing of the water quality characteristic concentration of the water body at the sampling point in the water pollution monitoring area is performed based on the water quality characteristic concentration data of the water body at the water pollution sampling point. The operation steps for generating the maximum value data of the water quality characteristic concentration of the water body at the water pollution sampling point are as follows: S31. Water pollution status analysis data in water pollution monitoring areas When the water is in a polluted state, the water quality characteristic concentration data set of the water pollution sampling point Water quality characteristic concentration data of water bodies at the sampling points for reclaimed water pollution Compare the water quality characteristic concentration values ​​of water bodies in order according to the water pollution sampling point numbers, and select the water quality characteristic concentration data of the water pollution sampling point with the largest water quality characteristic concentration value , and generate the maximum value data of water quality characteristic concentration of water body at water pollution sampling point through data identification .

[0031] According to the water quality characteristic concentration maximum value parameters and spatial coordinate parameters of the water pollution sampling points, the spatial geographic location identification and processing of the water pollutant emission sources in the water pollution monitoring area are carried out, and the operation steps for constructing the spatial coordinate data of the water pollution emission sources in the water pollution monitoring area are as follows: S41. Obtain the maximum value data of water quality characteristic concentration at water pollution sampling point and water pollution monitoring area sampling point spatial coordinate data set ; S42, using the KD tree nearest neighbor search algorithm based on the maximum water quality characteristic concentration data of the water pollution sampling point The corresponding water pollution sampling point number character in the water pollution monitoring area sampling point spatial coordinate data set Search for the maximum value data of water quality characteristic concentration of water body at the water pollution sampling point Spatial coordinate data of sampling points in the water pollution monitoring area corresponding to water pollution sampling points , and through data identification, the spatial coordinate data of water pollution emission sources in the water pollution monitoring area is constructed The spatial coordinate data of water pollution emission sources in the water pollution monitoring area represent the spatial position coordinate parameters of the water pollutant emission sources in the target water pollution monitoring area.

[0032] The mean water quality characteristic concentration of the water body at the water pollution sampling point is measured and the water quality characteristic concentration data corresponding to different water pollution types are used to identify the water pollution type in the water pollution monitoring area. The operating steps for generating water pollution type identification data in the water pollution monitoring area are as follows: S51. Data collection of water quality characteristic concentrations at water pollution sampling points Water quality characteristic concentration data of water bodies at the sampling points for reclaimed water pollution According to the water pollution sampling point number and water quality characteristic keywords, the water quality characteristic concentration mean of the water body is processed in order to measure the water quality characteristic concentration mean of the water pollution sampling point. ,in ; S52. Establish a data set of water quality characteristic concentrations corresponding to different water pollution types , ;in Indicates The water quality characteristic concentration data of different water pollution types corresponding to the water pollution types are matched. It indicates the maximum value of the number of water pollution types. The water quality characteristic concentration data corresponding to different water pollution types indicate the standard concentration range of water quality characteristic parameters corresponding to different water pollution types. Water pollution types include heavy metal pollution type, inorganic pollution type, organic pollution type, chemical pollution type, and highly toxic pollution type. S53, the water quality characteristic concentration average of the water body at the water pollution sampling point A data set of water quality characteristic concentrations corresponding to different types of water pollution Water quality characteristic concentration data corresponding to different water pollution types According to the water quality characteristic type character of the water body, the water quality characteristic concentration value of the water body is matched, and the average water quality characteristic concentration of the water body at the water pollution sampling point is searched out. The water quality characteristic concentration data of the water bodies corresponding to the different types of water pollution Corresponding water pollution types, and construct water pollution type identification data for water pollution monitoring areas , execute to generate water pollution type identification data in water pollution monitoring area The specific steps are as follows: S531, initialization parameters, update water pollution type search crow population, maximum number of iterations, flight distance ; S532. Initialize water pollution type and search for crow individuals in different water pollution types corresponding to water quality characteristic concentration data sets The initial position and memory in the search space, The crows searching for water pollution types are randomly distributed in a multidimensional search space, namely The spatial dimension of the random distribution of crows searching for water pollution types is The data set of water quality characteristic concentrations corresponding to different water pollution types In the search space; in the first iteration, it is assumed that the water pollution type search crow individual hides the food in the initial position; that is, in the first iteration, it is assumed that the water pollution type search crow individual hides the water quality characteristic concentration mean of the water pollution sampling point A data set of water quality characteristic concentrations corresponding to different types of water pollution The water quality characteristic concentration data corresponding to different water pollution types at the initial position of the search space Match the water quality characteristic concentration values ​​of water bodies according to the water quality characteristic type characters; S533, calculate the individual fitness value of each water pollution type search crow, that is, calculate the average concentration of water quality characteristics of the water pollution sampling point A data set of water quality characteristic concentrations corresponding to different types of water pollution Different water pollution types in the search space correspond to water quality characteristic concentration data The fitness value of S534. Update water pollution type to search for crows in different water pollution types corresponding to water quality characteristic concentration data sets The position in the search space and the water pollution type search formula for the individual position update of the crow are as follows: ,in Indicates Iteration water pollution type search crow individual A data set of water quality characteristic concentrations corresponding to different water pollution types The new position in the search space, Indicates Iteration water pollution type search crow individual A data set of water quality characteristic concentrations corresponding to different water pollution types The position in the search space, represents a random number uniformly distributed between [0, 1], Indicates Iteration water pollution type search crow individual A data set of water quality characteristic concentrations corresponding to different water pollution types The flight distance in the search space, Indicates Iteration water pollution type search crow individual A data set of water quality characteristic concentrations corresponding to different water pollution types The food hiding location in the search space, i.e. Iteration water pollution type search crow individual Data set of water quality characteristic concentrations corresponding to different water pollution types Search the search space to find the mean concentration of water quality characteristics of the water body at the water pollution sampling point The water quality characteristic concentration data of the water bodies corresponding to the different types of water pollution location; S535, determine the feasibility of the new position, determine the feasibility of the new position of each water pollution type search crow individual; if the new position of the water pollution type search crow individual is feasible, the water pollution type search crow individual will update its position, that is, the water quality characteristic concentration data set corresponding to different water pollution types Search the search space to find the mean concentration of water quality characteristics of the water body at the water pollution sampling point The water quality characteristic concentration data of the water bodies corresponding to the different types of water pollution The water pollution type, the water pollution type search crow individual is updated to the water quality characteristic concentration data corresponding to the different water pollution types that are successfully matched Otherwise, the water pollution type searching crow individual stays at the current location and does not move to the new location; S536, evaluate the fitness value of the new position, calculate the fitness value of each water pollution type search crow's individual new position, that is, calculate the water quality characteristic concentration data set corresponding to different water pollution types The mean concentration of water quality characteristics of water bodies at water pollution sampling points in the search space Water quality characteristic concentration data corresponding to different water pollution types at new locations The fitness value of S537, update memory, if the fitness value of the new position of the water pollution type search crow is greater than the fitness value of the initial position in the memory, the water pollution type search crow updates its memory through the new position, otherwise it does not update its memory; that is, in different water pollution types corresponding to the water quality characteristic concentration data set Search the search space to find the mean concentration of water quality characteristics of the water body at the water pollution sampling point The water quality characteristic concentration data corresponding to different water pollution types with the largest fitness value Types of water pollution; S538, when the maximum number of iterations is met, the output is the mean of the characteristic concentration of water quality in the water body at the water pollution sampling point The water quality characteristic concentration data of the water bodies corresponding to the different types of water pollution The water pollution type of the water body is identified and the water pollution type identification data of the water pollution monitoring area is constructed through data identification. .

[0033] According to the water pollution type identification data of the water body monitoring area and the water quality pollution prevention and control plan data corresponding to different water pollution types, the water quality prevention and control plan analysis and processing of the polluted water body in the water pollution monitoring area is carried out. The operation steps for generating the water quality prevention and control plan analysis data of the water body in the water pollution monitoring area are as follows: S61. Establish a data set of water pollution prevention and control plans for different water pollution types ,in Indicates The data of water quality pollution prevention and control plans corresponding to different water pollution types that match the water pollution types of the water body are the process and equipment data of the standard polluted water quality prevention and control treatment set for different water pollution types; S62, using the depth-first search algorithm to identify the water pollution type in the water pollution monitoring area Data set of water pollution prevention and control plans corresponding to different water pollution types Data on water quality pollution prevention and control plans for different water pollution types Perform keyword matching of water pollution types and search for water pollution type identification data in water pollution monitoring areas Corresponding water pollution prevention and control plan data for different water pollution types , and generate water quality prevention and control plan analysis data for water pollution monitoring areas through data identification .

[0034] Through the water quality characteristic concentration maximum value analysis unit of the water body at the water pollution sampling point, the maximum value parameters of the water quality characteristic concentration of the water body at the water pollution sampling point are accurately screened out based on numerical analysis, providing real data support for accurately locating the spatial location of the source of water pollutant emissions; the water pollution emission source geographical location identification unit, based on the maximum value parameters of the water quality characteristic concentration of the water body at the water pollution sampling point combined with the intelligent search algorithm and the spatial coordinate parameters of the water pollution sampling point, accurately analyzes the spatial geographical location of the source of water pollutant emissions in the water pollution monitoring area, and realizes efficient and accurate positioning of the geographical location of water pollution emission sources in the water pollution monitoring area; the water quality characteristic concentration mean measurement unit of the water pollution sampling point and the water pollution type identification unit of the water pollution monitoring area cooperate with each other based on numerical processing The mean characteristic concentration of water quality in the water bodies at the measured water pollution sampling points is combined with the intelligent recognition algorithm and the water quality characteristic concentration parameters corresponding to the different water pollution types preset in the standard to conduct a comprehensive and accurate analysis of the water pollution types in the water pollution monitoring area, so as to achieve accurate identification of water pollution types in the water pollution monitoring area and improve the quality of water pollution residue monitoring; the water pollution prevention and control plan analysis unit in the water pollution monitoring area accurately analyzes the water quality prevention and control plans of polluted water bodies in the water pollution monitoring area based on the water pollution type identification parameters in the water body monitoring area combined with the intelligent search algorithm and the scientifically stored water pollution prevention and control plan parameters corresponding to the different water pollution types, so as to achieve integrated management of polluted water monitoring and prevention in the water pollution monitoring area and improve the efficiency and effectiveness of water pollution residue supervision.

[0035] For further information, see Figure 1 - Figure 2 The steps for constructing water pollution monitoring and prevention analysis result data and performing water pollution monitoring and prevention analysis result feedback operations are as follows: S71. Analyze the water pollution status in the water pollution monitoring area , Spatial coordinate data of water pollution emission sources in water pollution monitoring areas , water pollution monitoring area water pollution type identification data , water pollution monitoring area water quality prevention and control plan analysis data After data combination, water pollution monitoring and prevention analysis result data is constructed ; S72. Data on water pollution monitoring and prevention analysis results Feedback is pushed to the water pollution residue monitoring platform through the Internet of Things communication network to execute the water pollution monitoring and prevention analysis results feedback task.

[0036] Through the water pollution monitoring and prevention analysis result acquisition unit, based on the pollution status analysis parameters of the water pollution monitoring area, the location information of the water pollutant emission sources, the water pollution type and the water pollution prevention and control plan combined with data processing, the water pollution monitoring and prevention analysis result information is scientifically constructed to improve the collection efficiency and security of water pollution residue supervision and processing information; the water pollution monitoring and prevention analysis result feedback unit pushes the water pollution monitoring and prevention analysis results online through the Internet of Things communication network to the water pollution residue monitoring platform, so as to realize the efficient and accurate push of water pollution residue supervision result information and improve the response efficiency of water pollution residue supervision results.

[0037] Embodiment 2: See also Figure 1 - Figure 2 , a water pollution residue monitoring and prevention system based on data analysis, used to implement a water pollution residue monitoring and prevention method based on data analysis, the system includes a water pollution state analysis module, a water pollution type and prevention and control plan analysis module, and a water pollution monitoring and prevention analysis result feedback module; The water pollution status analysis module includes a water quality characteristic concentration acquisition unit for water pollution sampling points, a spatial coordinate acquisition unit for sampling points in water pollution monitoring areas, a water quality characteristic concentration storage unit for standard polluted water bodies, and a water pollution status analysis unit for water pollution monitoring areas; The water quality characteristic concentration acquisition unit of the water body at the water pollution sampling point collects the water quality characteristic concentration data of the water body at the water pollution sampling point through the water body monitoring sensor; the spatial coordinate acquisition unit of the sampling point in the water pollution monitoring area collects the spatial coordinate data of the sampling point in the water pollution monitoring area through the position sensor; the water quality characteristic concentration storage unit of the standard polluted water body is used to store the water quality characteristic concentration data of the standard polluted water body; the water pollution state analysis unit of the water pollution monitoring area performs water pollution state analysis and processing in the water pollution monitoring area based on the water quality characteristic concentration data of the water body at the water pollution sampling point and the water quality characteristic concentration data of the standard polluted water body, and generates water pollution state analysis data of the water pollution monitoring area; The water pollution type and prevention and control plan analysis module includes a water pollution sampling point water quality characteristic concentration maximum value analysis unit, a water pollution emission source geographical location identification unit, a water pollution sampling point water quality characteristic concentration mean value measurement unit, a water quality characteristic concentration storage unit corresponding to different water pollution types, a water pollution type identification unit in a water pollution monitoring area, a water quality prevention and control plan storage unit corresponding to different water pollution types, and a water pollution prevention and control plan analysis unit in a water pollution monitoring area; The maximum value analysis unit of water quality characteristic concentration of water bodies at water pollution sampling points is used to analyze and process the maximum value of water quality characteristic concentration of water bodies at water pollution sampling points in the water pollution monitoring area based on the water quality characteristic concentration data of water bodies at water pollution sampling points, and generate the maximum value data of water quality characteristic concentration of water bodies at water pollution sampling points; the geographical location identification unit of water pollution emission sources is used to identify and process the spatial geographical location of the sources of water pollutant emissions in the water pollution monitoring area according to the maximum value parameters and spatial coordinate parameters of water quality characteristic concentration of water bodies at water pollution sampling points, and construct the spatial coordinate data of water pollution emission sources in the water pollution monitoring area; the mean value measurement unit of water quality characteristic concentration of water bodies at water pollution sampling points is used to measure the mean value of water quality characteristic concentration of water bodies at water pollution sampling points; the water quality characteristic concentration storage unit corresponding to different water pollution types is used to store the corresponding data of different water pollution types. Water quality characteristic concentration data; a water pollution type identification unit in a water pollution monitoring area, which performs water pollution type identification processing in a water pollution monitoring area based on the average water quality characteristic concentration of water pollution sampling points and the water quality characteristic concentration data corresponding to different water pollution types, and generates water pollution type identification data in a water pollution monitoring area; a water quality prevention and control plan storage unit corresponding to different water pollution types, which is used to store water quality prevention and control plan data corresponding to different water pollution types; a water pollution prevention and control plan analysis unit in a water pollution monitoring area, which performs water quality prevention and control plan analysis processing in a water pollution monitoring area based on water pollution type identification data in a water pollution monitoring area and water quality prevention and control plan data corresponding to different water pollution types, and generates water quality prevention and control plan analysis data in a water pollution monitoring area; The water pollution monitoring and prevention analysis result feedback module includes a water pollution monitoring and prevention analysis result acquisition unit and a water pollution monitoring and prevention analysis result feedback unit; The water pollution monitoring and prevention analysis result acquisition unit is used to construct water pollution monitoring and prevention analysis result data; the water pollution monitoring and prevention analysis result feedback unit performs water pollution monitoring and prevention analysis result feedback operations based on the water pollution monitoring and prevention analysis result data.

[0038] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A water pollution residue monitoring and prevention method based on data analysis, characterized in that: The method comprises the following steps: S1. Collect water quality characteristic concentration data of water bodies at water pollution sampling points and spatial coordinate data of sampling points in water pollution monitoring areas; S2, analyzing and processing the water pollution status of the water pollution monitoring area according to the water quality characteristic concentration data of the water body at the water pollution sampling point and the water quality characteristic concentration data of the standard polluted water body, generating water pollution status analysis data of the water pollution monitoring area, and directly ending the water pollution monitoring operation when it is in a normal state; S3, when it is in a pollution state, based on the water quality characteristic concentration data of the water body at the water pollution sampling point, the water quality characteristic concentration maximum value analysis and processing of the water body at the sampling point in the water pollution monitoring area is performed to generate the water quality characteristic concentration maximum value data of the water body at the water pollution sampling point; S4, according to the water quality characteristic concentration maximum value parameters and spatial coordinate parameters of the water pollution sampling points, the spatial geographical location identification and processing of the water pollutant emission sources in the water pollution monitoring area are performed to construct the spatial coordinate data of the water pollution emission sources in the water pollution monitoring area; S5, measuring the average characteristic concentration of water quality of water bodies at the water pollution sampling points and identifying the water pollution types in the water pollution monitoring area with the water quality characteristic concentration data corresponding to different water pollution types, and generating water pollution type identification data in the water pollution monitoring area; S6, analyzing and processing the water quality prevention and control plan for the polluted water bodies in the water pollution monitoring area according to the water pollution type identification data of the water body monitoring area and the water quality prevention and control plan data corresponding to different water pollution types, and generating water quality prevention and control plan analysis data for the water pollution monitoring area; S7. Construct water pollution monitoring and prevention analysis result data and perform water pollution monitoring and prevention analysis result feedback operations.

2. The method for monitoring and preventing water pollution residues based on data analysis according to claim 1 is characterized in that: The S1 comprises the following steps: S11. Collect water quality characteristic concentration parameters of each water pollution sampling point randomly selected from the target water pollution monitoring area online through water body monitoring sensors, and generate a water quality characteristic concentration data set of the water pollution sampling points , ;in Indicates the collected The water quality characteristic concentration data of the water pollution sampling points corresponding to the water pollution sampling points, Indicates the maximum number of water pollution sampling points; The spatial position coordinate parameters of each randomly selected water pollution sampling point in the target water pollution monitoring area are collected online through the position sensor, and the spatial coordinate data set of the sampling points in the water pollution monitoring area is generated. ,in Indicates the collected The spatial coordinate data of the sampling points in the water pollution monitoring area corresponding to the water pollution sampling points.

3. The method for monitoring and controlling water pollution residues based on data analysis according to claim 2 is characterized in that: The S2 comprises the following steps: S21. Establish a data set of water quality characteristic concentrations of standard polluted water bodies , ;in Indicates The water quality characteristic concentration data of standard polluted water bodies corresponding to the water quality characteristic types of water bodies, Indicates the maximum number of water quality characteristic types of water bodies; S22, the As stated in According to the water pollution sampling point number and water quality characteristic type number, the water pollution sampling point number and water quality characteristic type number are arranged in order. As stated in Carry out numerical comparison of water quality characteristic concentrations, and generate water pollution status analysis data of water pollution monitoring areas based on the results of numerical comparison of water quality characteristic concentrations ; when and If the water quality characteristic concentration value comparison is successful, the water pollution status analysis data of the water pollution monitoring area will be output. It is a polluted state; when and If the water quality characteristic concentration values ​​of the water body are not successfully compared, the water pollution status analysis data of the water pollution monitoring area will be output It is in normal state, and the water pollution monitoring operation is terminated directly at this time.

4. The method for monitoring and controlling water pollution residues based on data analysis according to claim 3 is characterized in that: The S3 comprises the following steps: S31, when the When the As stated in According to the water pollution sampling point number, the water quality characteristic concentration values ​​of the water body are compared in order, and the water body with the largest water quality characteristic concentration value is selected. , and generate the maximum value data of water quality characteristic concentration of water body at water pollution sampling point through data identification .

5. The method for monitoring and controlling water pollution residues based on data analysis according to claim 4 is characterized in that: The S4 comprises the following steps: S41, obtaining the and stated ; S42, using KD tree nearest neighbor search algorithm according to The corresponding water pollution sampling point number characters are described in Search for the Corresponding to the water pollution sampling points , and through data identification, the spatial coordinate data of water pollution emission sources in the water pollution monitoring area is constructed .

6. The method for monitoring and controlling water pollution residues based on data analysis according to claim 5 is characterized in that: The S5 comprises the following steps: S51, for the As stated in According to the water pollution sampling point number and water quality characteristic keywords, the water quality characteristic concentration mean of the water body is processed in order to measure the water quality characteristic concentration mean of the water pollution sampling point. ; S52. Establish a data set of water quality characteristic concentrations corresponding to different water pollution types , ;in Indicates The water quality characteristic concentration data of different water pollution types corresponding to the water pollution types are matched. Indicates the maximum value of the number of water pollution types; S53, the With the As stated in According to the water quality characteristic type character of the water body, the water quality characteristic concentration value is matched, and the water body that matches the water quality characteristic type character is searched. Matching the Corresponding water pollution types, and construct water pollution type identification data for water pollution monitoring areas , execute to generate water pollution type identification data of the water pollution monitoring area The specific steps are as follows: S531, initialization parameters, update water pollution type search crow population, maximum number of iterations, flight distance ; S532, initializing the water pollution type to search for crow individuals in the The initial position and memory in the search space, The crows searching for water pollution types are randomly distributed in a multidimensional search space, namely The spatial dimension of the random distribution of crows searching for water pollution types is of In the search space; in the first iteration, assuming that the water pollution type search crow individual hides the food in the initial position; that is, in the first iteration, assuming that the water pollution type search crow individual hides the food in the initial position With the The initial position in the search space Match the water quality characteristic concentration values ​​of water bodies according to the water quality characteristic type characters; S533, calculate the individual fitness value of each water pollution type search crow, that is, calculate the With the The search space The fitness value of S534, update the water pollution type to search for crow individuals in the Position in the search space; S535, determine the feasibility of the new position, determine the feasibility of the new position of each water pollution type search crow individual; if the new position of the water pollution type search crow individual is feasible, the water pollution type search crow individual will update its position, that is, in the Search the search space for Matching the The water pollution type, the water pollution type search crow individual is updated to the matching successful Otherwise, the water pollution type searching crow individual stays at the current location and does not move to the new location; S536, evaluate the fitness value of the new position, calculate the fitness value of each water pollution type searching crow's individual new position, that is, calculate the fitness value of the new position of the crow. Search space described With the new location The fitness value of S537, updating memory, if the fitness value of the new position of the water pollution type search crow is greater than the fitness value of the initial position in the memory, the water pollution type search crow updates its memory through the new position, otherwise it does not update its memory; that is, in the Search the search space for The one with the largest fitness value Types of water pollution; S538. When the maximum number of iterations is met, output the same as described above. Matching the The water pollution type of the water body is identified and the water pollution type identification data of the water pollution monitoring area is constructed through data identification. .

7. The method for monitoring and controlling water pollution residues based on data analysis according to claim 6 is characterized in that: The S6 comprises the following steps: S61. Establish a data set of water pollution prevention and control plans for different water pollution types ,in Indicates The data of water quality pollution prevention and control plans for different water pollution types that match the water pollution types; S62, using a depth-first search algorithm to With the As stated in Perform keyword matching of water pollution types and search for the The corresponding , and generate water quality prevention and control plan analysis data for water pollution monitoring areas through data identification .

8. The method for monitoring and controlling water pollution residues based on data analysis according to claim 7 is characterized in that: The S7 comprises the following steps: S71, the , , , After data combination, water pollution monitoring and prevention analysis result data is constructed ; S72, the Feedback is pushed to the water pollution residue monitoring platform through the Internet of Things communication network to execute the water pollution monitoring and prevention analysis results feedback task.

9. A water pollution residue monitoring and prevention system based on data analysis, used to implement a water pollution residue monitoring and prevention method based on data analysis according to any one of claims 1 to 8, characterized in that: The system includes a water pollution status analysis module, a water pollution type and prevention and control plan analysis module, and a water pollution monitoring and prevention analysis result feedback module.

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