River pollutant distribution monitoring system and method based on multi-modal data fusion

Abstract

The invention relates to the technical field of river pollutant monitoring, and discloses a river pollutant distribution monitoring system and method based on multi-modal data fusion, and the system comprises a river pollution state recognition module, a river pollutant spatial distribution monitoring module, and a river pollutant spatial distribution change monitoring module. River pollutant displacement information in prediction time is scientifically counted based on river water flow velocity information and river pollution state change prediction duration information in combination with numerical analysis; and meanwhile, the spatial distribution form scientific modeling of the river pollutants in the river within the prediction time is carried out by combining the three-dimensional change model information of the river pollutants and the spatial distribution model information of the river pollutants, so that the change of the river pollutants is monitored on the basis of multi-modal data fusion real predictability, and the applicability and intellectualization of river pollutant monitoring are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of river pollutant monitoring, in particular to a river pollutant distribution monitoring system and method based on multi-modal data fusion. BACKGROUND

[0002] Water quality monitoring is a process of monitoring and measuring the types of pollutants in water bodies, the concentrations of various pollutants, and their trends, and evaluating water quality. The monitoring range is very wide, including natural water such as rivers, lakes, seas and underground water that have not been polluted and have been polluted, and various industrial wastewater. The main monitoring items can be divided into two categories: one is the comprehensive index reflecting the water quality, such as temperature, color, turbidity, pH value, conductivity, suspended solids, dissolved oxygen, chemical oxygen demand and biochemical oxygen demand, etc.; the other is some toxic substances, such as phenol, cyanide, arsenic, lead, chromium, cadmium, mercury and organic pesticides, among which the river pollutant monitoring operation is the most widely used; the current river pollutant state monitoring at fixed positions through artificial and large models cannot truly feedback the change state of the pollutants in the river, the existing river pollutant monitoring cannot realize intelligent monitoring of the spatial distribution of river pollutants, and cannot intelligently monitor the spatial distribution change state of river pollutants based on time characteristics; the effect of river pollutant monitoring is reduced.

[0003] The Chinese invention patent application with publication number CN119291144A and publication date of January 10, 2025 discloses a river water environment pollutant real-time monitoring method and system, which obtains time series data of river water environment pollutant concentration in the monitoring area through a fixed sampling frequency, constructs a time series data sequence of the i-th type of pollutant concentration, constructs a gray prediction model using the data sequence, calculates the predicted value of the i-th type of pollutant concentration at the next sampling time through the prediction model, calculates the pollution degree evaluation value in the monitoring area at the next sampling time according to the obtained predicted value, and predicts the pollutant concentration parameter at the future time using the gray prediction model; the above technical solution cannot accurately monitor the spatial distribution form of river pollutants and the subsequent spatial distribution change form of river pollutants, and reduces the quality of river pollutant monitoring. SUMMARY

[0004] (I) Technical problems solved

[0005] To solve the above existing river pollutant monitoring cannot realize the intelligent monitoring of river pollutant spatial distribution, also cannot realize the intelligent monitoring of river pollutant spatial distribution change state based on time characteristics, reduce the effect of river pollutant monitoring, realize the above dynamic collection of river measurement point pollutant parameters, efficient analysis of river pollution state, intelligent construction of river pollutant spatial distribution model, scientific construction of river pollutant spatial distribution time sequence change model, realize the predictive monitoring of river pollutant spatial distribution, improve the precision and intelligentization of river pollutant monitoring.

[0006] (Two) Technical scheme

[0007] The application is realized by the following technical scheme: a river pollutant distribution monitoring method based on multi-modal data fusion, the method comprises the following steps:

[0008] S1, collecting river measurement point pollutant parameters;

[0009] S2, according to the river measurement point pollutant parameters and the river normal state pollutant threshold, analyzing and processing the pollution state of the river measurement point, generating river measurement point pollution state analysis information and searching and processing river pollutant type information, generating river pollutant type search information and processing river pollution state judgment, generating river pollution state judgment information, when it is normal state, directly ending the river pollutant monitoring operation;

[0010] S3, when it is a pollution state, based on the river measurement point pollution state analysis information, collecting and processing the spatial coordinate information of the river pollution measurement point, generating river pollution measurement point spatial coordinate data and processing the spatial three-dimensional model modeling of the river pollutant, generating river pollutant three-dimensional model data;

[0011] S4, collecting river three-dimensional model data and processing the spatial coordinate generation of river three-dimensional model, generating river spatial coordinate data and combining the three-dimensional model and spatial coordinate data of river with the river pollutant three-dimensional model data, generating river spatial model spatial coordinate combination data and processing the three-dimensional model construction of river pollutant spatial distribution in river with the river pollutant three-dimensional model data, generating river pollutant spatial distribution model data;

[0012] S5, collecting river water flow velocity information and river pollution state change prediction time length;

[0013] S6, based on the river pollutant species search information and different river pollutant characteristics corresponding unit time pollutant diffusion distance amount, the unit time pollutant diffusion distance amount of river pollutant is analyzed and processed, the target river unit time pollutant diffusion distance amount is generated, and the river pollution state change prediction time length is carried out statistical processing of the pollutant diffusion distance amount of the river pollutant in the prediction time, and the prediction time river pollutant diffusion distance amount is generated;

[0014] S7, based on the river pollutant three-dimensional model data, the prediction time river pollutant diffusion distance amount is carried out pollutant space three-dimensional change model modeling processing of river pollutant in prediction time, and the river pollutant three-dimensional change model data is constructed;

[0015] S8, based on the river water flow velocity information, the river pollution state change prediction time length is carried out statistical processing of the river pollutant displacement parameter in the prediction time, the prediction time river pollutant displacement data is generated, and the river pollutant three-dimensional change model data, the river pollutant space distribution model data are carried out three-dimensional model construction processing of the space distribution change of the river pollutant in the river in the prediction time, and the river pollutant space distribution time sequence change model data is generated.

[0016] Preferably, the operation steps of collecting river measurement point pollutant parameters are as follows:

[0017] S11, the pollutant species information and the pollutant concentration parameter of the water quality measurement point in the river monitoring area are collected on line by the water quality measuring instrument, and the river measurement point pollutant parameter set is generated , ; wherein represents the river measurement point pollutant parameter of the first water quality measurement point collected, represents the maximum value of the number of water quality measurement points, the pollutant species includes ammonium nitrogen, nitrite nitrogen, cyanide, phenolic compound, anionic detergent, phenol, cyanide, arsenic, lead, chromium, cadmium and mercury; the pollutant concentration unit of the water quality measurement point is milligram per meter; the water quality measuring instrument includes COD measuring instrument, BOD measuring instrument, ammonia nitrogen detector, heavy metal analyzer and nutrient salt detector.

[0018] Preferably, according to the river measurement point pollutant parameter and the river normal state pollutant threshold, the pollution state analysis information of the river measurement point is generated, the river pollutant species information search processing is carried out, the river pollution state judgment information is generated, and the river pollution state judgment processing is carried out, when it is normal state, the operation steps of directly ending the river pollutant monitoring operation are as follows:

[0019] S21. Establish a set of pollutant thresholds for normal river conditions. , ;in Indicates the first The corresponding pollutant thresholds for each type of pollutant under normal river conditions. This represents the maximum number of pollutant types. The pollutant threshold under normal river conditions represents the maximum concentration of a single pollutant under normal river conditions. The unit is milligrams per meter;

[0020] S22. Set the pollutant parameters of the river measurement points. Pollutant parameters at river measurement points described in the text The water quality measurement points are ordered according to their numbers and the pollutant threshold set under normal conditions of the river. The pollutant thresholds for normal river conditions described in the text The pollutant concentration values ​​were compared, and a pollution status analysis information set for river measurement points was generated based on the comparison results. ,in Indicates the first Pollution status analysis information of river measurement points at individual water quality measurement points;

[0021] when The concentrations of pollutants in the medium are all no greater than , indicating the first If the water quality at each water quality measurement point is unpolluted, then the pollution status analysis information for that river measurement point will be output. This is the normal state;

[0022] when There are pollutant concentrations greater than , indicating the first The water quality at the first water quality monitoring point was affected by the first If a pollutant causes pollution, the pollution status analysis information of the river measurement points will be output. The system is in a contaminated state, and the output is the first... Textual information on the types of pollutants;

[0023] S23. The Boyer-Moore search algorithm is used to analyze the pollution status information set of the river measurement points. Pollution status analysis information of river measurement points described in the document The search retrieves information on all types of pollutants polluting the water in the target river area and generates river pollutant type search information. Under normal circumstances, river water pollution exhibits regional distribution; therefore, while the types of pollutants polluting river water are the same, the concentrations of pollutants vary.

[0024] S24. Search information based on the river pollutant types. The system searches for information on river pollutant types and generates information on the river pollution status based on the search results.

[0025] when If no information on the types of river pollutants is found, it indicates that the water quality in the river monitoring area is normal. In this case, the river pollution status judgment information is output as normal, and the river pollutant monitoring operation is terminated directly.

[0026] when If the search for information on the types of pollutants in the river indicates that the water quality in the river monitoring area is polluted, then the pollution status information of the river will be output as pollution status.

[0027] Preferably, when the river is in a polluted state, the spatial coordinate information of the river pollution measurement points is collected and processed based on the pollution state analysis information of the river measurement points to generate spatial coordinate data of the river pollution measurement points and to perform spatial three-dimensional modeling of the river pollutants. The operation steps for generating three-dimensional model data of river pollutants are as follows:

[0028] S31. When the river pollution status assessment information indicates a pollution status, the pollution status analysis information of the river measurement points is collected online using location sensors. To generate a dataset of spatial coordinates of river pollution measurement points, corresponding to the water quality measurement points under pollution conditions. ,in and They represent the first and Spatial coordinate data of river pollution measurement points at various water quality measurement sites. The spatial coordinate data of the river pollution measurement points include the longitude, latitude, and altitude of the river water quality measurement points;

[0029] S32. Apply the Halcon operator to the spatial coordinate dataset of the river pollution measurement points. Spatial coordinate data of river pollution measurement points described in the document to The spatial three-dimensional morphology of water quality measurement points under pollution conditions is numerically constructed, and three-dimensional model data of river pollutants is generated. The three-dimensional model data of river pollutants includes the spatial coordinate information of water quality measurement points under pollution conditions and the spatial three-dimensional model information formed by the water quality measurement points under pollution conditions.

[0030] Preferably, the steps for collecting river 3D model data and generating spatial coordinates of the river 3D model, generating river spatial coordinate data, combining the river 3D model and spatial coordinate data with the river pollutant 3D model data, generating river spatial model spatial coordinate combination data, and then combining this data with the river pollutant 3D model data to construct a 3D model of the spatial distribution of river pollutants in the river, generating river pollutant spatial distribution model data, are as follows:

[0031] S41. Using a drone equipped with a 3D laser scanner, scan and collect the 3D physical model of the geographic terrain of the target river, and generate 3D model data of the river.

[0032] S42. Using a GIS platform, the geospatial coordinates of the river's 3D model corresponding to the river's 3D model data are generated, and a river spatial coordinate dataset is generated. , ;in Indicates the generated first River spatial coordinate data, This represents the maximum number of generated river spatial coordinates, where the river spatial coordinate data represents the longitude, latitude, and altitude of the river's geographical topography.

[0033] S43. Combine the river 3D model data with the river spatial coordinate dataset. The river spatial coordinate data described in Perform combined processing of the river's 3D model and river spatial coordinate data, and generate combined spatial coordinate data of the river spatial model;

[0034] S44. The three-dimensional model data of river pollutants and the spatial coordinate combination data of the river spatial model are combined according to the spatial coordinate parameters of the water quality measurement points under pollution status and the spatial coordinates of the river to construct a three-dimensional model of the spatial distribution of river pollutants in the river and generate the spatial distribution model data of river pollutants.

[0035] Preferably, the steps for collecting river flow velocity information and predicting the time duration of river pollution status changes are as follows:

[0036] S51. Collect the water flow velocity and flow direction information of the river monitoring area online through a flow velocity meter, and generate river water flow velocity information. The unit of water flow velocity is meters per second.

[0037] The river pollutant monitoring platform collects online information on the spatial distribution changes of river pollutants within a predicted time period through its input dialog box, and generates a predicted time length for changes in river pollution status, with the unit of the predicted time length being seconds.

[0038] Preferably, based on the river pollutant category search information and the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount, the unit time pollutant diffusion distance amount of the river pollutant is analyzed and processed, the target river unit time pollutant diffusion distance amount is generated, and the river pollutant diffusion distance amount in the prediction time is statistically processed with the river pollution state change prediction time length, and the operation steps of generating the prediction time river pollutant diffusion distance amount are as follows:

[0039] S61, a set of different river pollutant characteristic corresponding unit time pollutant diffusion distance amounts is established , ; wherein represents the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount corresponding to the th river pollutant characteristic type, represents the maximum value of the number of river pollutant characteristic types, the river pollutant characteristic type represents all pollutant category information causing water pollution in the river, and the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount represents the distance amount of the river pollutant in the river water body diffusing to the surrounding water body per unit time according to the different river pollutant characteristic type standard, The unit is meter per second;

[0040] S62, the river pollutant category search information is matched with the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount in the set of different river pollutant characteristic corresponding unit time pollutant diffusion distance amounts , the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount corresponding to the river pollutant category search information is searched out, and the target river unit time pollutant diffusion distance amount is generated through data identification, and the specific operation steps of generating the target river unit time pollutant diffusion distance amount are as follows:

[0041] S621, initialization, updating the maximum iteration number T of the algorithm and randomly initializing the position of the pollutant diffusion distance search fish eagle population in the optimization space, and the position initialization formula is , wherein represents the position of the pollutant diffusion distance search fish eagle in the search space of the set of different river pollutant characteristic corresponding unit time pollutant diffusion distance amounts with the space dimension being ​To find the optimal lower boundary, that is, the set of pollutant diffusion distances per unit time corresponding to the different river pollutant characteristics. The lower bound of the search space, To find the optimal upper boundary, that is, the set of pollutant diffusion distances per unit time corresponding to the different river pollutant characteristics. The upper bound of the search space, This represents a random number within the range [0,1].

[0042] S622. Exploration Phase: The exploration phase of pollutant dispersion distance search osprey population renewal is modeled based on the simulation of the natural behavior of this species. The pollutant dispersion distance search ospreys use the data to measure the pollutant dispersion distance per unit time corresponding to different river pollutant characteristics. Randomly search the search space for information related to the types of pollutants in the river. Matching the different river pollutant characteristics and corresponding pollutant diffusion distance per unit time The target's location is determined and attacked. Based on the simulated movement of the pollutant dispersion distance search osprey towards the target, the new position of the corresponding pollutant dispersion distance search osprey is updated. The formula for updating the pollutant dispersion distance search osprey position is as follows: ,in Indicates the distance of pollutant dispersion by the search osprey. After the update, the spatial dimension is The set of pollutant diffusion distances per unit time corresponding to the different river pollutant characteristics The position in the search space; This represents the pollutant diffusion distance measurement data per unit time for the Osprey in different rivers, corresponding to the pollutant characteristics. Search the search space for information related to the types of pollutants in the river. Matching the different river pollutant characteristics and corresponding pollutant diffusion distance per unit time The location of the target; This represents a constant that takes the value 1 or 2; if the updated position is better, the initial position of the pollutant diffusion distance search osprey is replaced according to the position replacement formula during the exploration phase. The position replacement formula during the exploration phase is: ,in Indicating the distance of pollutant dispersion during the exploration phase, the search osprey... After the update, the spatial dimension is The set of pollutant diffusion distances per unit time corresponding to the different river pollutant characteristics The optimal position in the search space; express The pollutant diffusion distance per unit time corresponding to the different river pollutant characteristics at the location. the river pollutant species search information a fitness value, denotes the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount at the location the river pollutant species search information a fitness value;

[0043] S623, the development stage, the pollutant diffusion distance search falcon hunting and eating the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount set the river pollutant species search information the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount matched the goal, the algorithm pollutant diffusion distance search falcon population update development stage is based on the simulation of the natural behavior of pollutant diffusion distance search falcon modeling, calculating the new random position as suitable for eating the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount matched the river pollutant species search information the goal of the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount matched the goal of the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount matched the formula of the goal of the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount matched wherein denotes the pollutant diffusion distance search falcon the new random position in the search space of the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount set after updating in the spatial dimension as suitable for eating the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount matched the river pollutant species search information the goal of the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount matched denotes the current algorithm iteration number; if the value of the objective function is improved at this new position, replace the initialization position of the pollutant diffusion distance search falcon before updating according to the development stage position replacement formula, the development stage position replacement formula is wherein denotes the development stage pollutant diffusion distance search falcon the optimal position in the search space of the different river pollutant characteristic corresponding unit time pollutant diffusion distance amount set after updating in the spatial dimension ; denotes The pollutant diffusion distance per unit time corresponding to the different river pollutant characteristics at the location. Fitness value relative to the search information on river pollutant types;

[0044] S624. After the algorithm reaches the maximum number of iterations, it outputs the search information related to the types of river pollutants. The most matching pollutant characteristics of the different rivers correspond to the pollutant diffusion distance per unit time. Otherwise, continue executing steps S622 to S623 until the maximum number of iterations is met;

[0045] S625. Calculate the pollutant diffusion distance per unit time corresponding to the different river pollutant characteristics output in step S624. The pollutant diffusion distance per unit time of the target river is generated by data identification, and the unit of the pollutant diffusion distance per unit time of the target river is meters per second;

[0046] S63. Multiply the predicted time length of the river pollution state change with the pollutant diffusion distance per unit time of the target river and perform statistical processing to measure the pollutant diffusion distance of the river during the predicted time. The pollutant diffusion distance of the river during the predicted time represents the distance that the pollutants in the river diffuse from the river to the surrounding water bodies within the predicted time. The unit of the pollutant diffusion distance of the river during the predicted time is meters.

[0047] Preferably, the steps for modeling and processing the three-dimensional spatial variation model of river pollutants within the predicted time period based on the three-dimensional model data of river pollutants and the predicted time river pollutant diffusion distance are as follows:

[0048] S71. Import the three-dimensional model data of the river pollutants into a three-dimensional mechanical design software, and use the thickness command in the three-dimensional mechanical design software to thicken the three-dimensional model around the three-dimensional model data of the river pollutants according to the distance value corresponding to the predicted river pollutant diffusion distance, and construct the three-dimensional change model data of the river pollutants. The three-dimensional mechanical design software can be any one of UG, CATIA, or SolidWorks.

[0049] Preferably, based on the river water flow velocity information, the river pollution state change prediction time length is used for river pollutant displacement parameter statistical processing in the prediction time, to generate prediction time river pollutant displacement data and perform prediction time river pollutant spatial distribution change three-dimensional model construction processing with the river pollutant three-dimensional change model data and the river pollutant spatial distribution model data, to generate river pollutant spatial distribution time sequence change model data. The operation steps are as follows:

[0050] S81, the river water flow velocity information is multiplied by the river pollution state change prediction time length for numerical statistical processing, and the prediction time river pollutant displacement data is calculated, the unit of the prediction time river pollutant displacement data is meter, and the prediction time river pollutant displacement data represents the displacement information of the river pollutant moving with the river water body in the prediction time; the prediction time river pollutant displacement data includes distance information and direction information of the river pollutant movement;

[0051] S82, the river pollutant three-dimensional change model data and the river pollutant spatial distribution model data are imported into a three-dimensional mechanical design software, and a simulation module of the three-dimensional mechanical design software is used to set the three-dimensional model corresponding to the river pollutant three-dimensional change model data as an initial position according to the position of the three-dimensional model corresponding to the river pollutant three-dimensional model data in the river, and control the three-dimensional model corresponding to the river pollutant three-dimensional change model data to move to a prediction position in the river based on the prediction time river pollutant displacement data, to construct river pollutant spatial distribution time sequence change model data, which represents the spatial distribution state information of the river pollutant moving with the river water body in the prediction time.

[0052] A river pollutant distribution monitoring system based on multi-modal data fusion is used to realize the river pollutant distribution monitoring method based on multi-modal data fusion. The system includes a river pollution state recognition module, a river pollutant spatial distribution monitoring module, and a river pollutant spatial distribution change monitoring module.

[0053] The river pollution state recognition module includes a river measurement point pollutant parameter acquisition unit, a river normal state pollutant threshold storage unit, a river measurement point pollution state analysis unit, a river pollutant type search unit, and a river pollution state judgment unit.

[0054] The river measurement point pollutant parameter collection unit collects river measurement point pollutant parameters through a water quality measuring instrument; the river normal state pollutant threshold storage unit is used for storing river normal state pollutant threshold values; the river measurement point pollution state analysis unit performs pollution state analysis and processing of the river measurement point according to the river measurement point pollutant parameters and the river normal state pollutant threshold values, and generates river measurement point pollution state analysis information; the river pollutant type searching unit performs river pollutant type information search processing according to the river measurement point pollution state analysis information, and generates river pollutant type search information; and the river pollution state judgment unit performs river pollution state judgment processing according to the river pollutant type search information, and generates river pollution state judgment information.

[0055] The river pollutant spatial distribution monitoring module includes a river pollution measurement point positioning unit, a river pollution three-dimensional model construction unit, a river three-dimensional model collection unit, a river three-dimensional coordinate decomposition unit, a river spatial model spatial coordinate combination information construction unit, and a river pollutant spatial distribution model construction unit.

[0056] The river pollution measurement point positioning unit performs spatial coordinate information collection and processing of the river pollution measurement point based on the river measurement point pollution state analysis information and in combination with a position sensor, and generates river pollution measurement point spatial coordinate data; the river pollution three-dimensional model construction unit performs spatial three-dimensional model modeling processing of the river pollution based on the river pollution measurement point spatial coordinate data, and generates river pollution three-dimensional model data; the river three-dimensional model collection unit collects river three-dimensional model data through a three-dimensional laser scanner carried by a drone; the river three-dimensional coordinate decomposition unit performs spatial coordinate generation processing of the river three-dimensional model based on the river three-dimensional model data and in combination with a GIS platform, and generates river spatial coordinate data; the river spatial model spatial coordinate combination information construction unit performs three-dimensional model and spatial coordinate data combination processing of the river based on the river spatial coordinate data and the river pollution three-dimensional model data, and generates river spatial model spatial coordinate combination data; and the river pollutant spatial distribution model construction unit performs spatial distribution three-dimensional model construction processing of the river pollutant in the river based on the river spatial model spatial coordinate combination data and the river pollution three-dimensional model data, and generates river pollutant spatial distribution model data.

[0057] The river pollutant spatial distribution change monitoring module comprises a river water body flow rate information acquisition unit, a river pollution state change prediction time acquisition unit, a different river pollutant characteristic corresponding unit time pollutant diffusion distance quantity storage unit, a river unit time pollutant diffusion distance quantity analysis unit, a prediction time river pollutant diffusion distance quantity statistical unit, a river pollutant three-dimensional change model construction unit, a prediction time river pollutant displacement statistical unit and a river pollutant spatial distribution time sequence change model construction unit.

[0058] The river water body flow rate information acquisition unit acquires river water body flow rate information through a flow rate measuring instrument; the river pollution state change prediction time acquisition unit acquires the length of the river pollution state change prediction time through an input dialog box of a river pollutant monitoring platform; the different river pollutant characteristic corresponding unit time pollutant diffusion distance quantity storage unit is used for storing different river pollutant characteristic corresponding unit time pollutant diffusion distance quantities; the river unit time pollutant diffusion distance quantity analysis unit performs unit time pollutant diffusion distance quantity analysis processing of river pollutants based on the river pollutant species search information and the different river pollutant characteristic corresponding unit time pollutant diffusion distance quantities, and generates target river unit time pollutant diffusion distance quantities; the prediction time river pollutant diffusion distance quantity statistical unit performs pollutant diffusion distance quantity statistical processing of river pollutants in a prediction time according to the target river unit time pollutant diffusion distance quantities and the length of the river pollution state change prediction time, and generates prediction time river pollutant diffusion distance quantities; the river pollutant three-dimensional change model construction unit performs pollutant spatial three-dimensional change model modeling processing of river pollutants in the prediction time based on the river pollutant three-dimensional model data, the prediction time river pollutant diffusion distance quantities and in combination with a three-dimensional mechanical design software, and constructs river pollutant three-dimensional change model data; the prediction time river pollutant displacement statistical unit performs displacement parameter statistical processing of river pollutants in the prediction time in a river based on the river water body flow rate information and the length of the river pollution state change prediction time, and generates prediction time river pollutant displacement data; and the river pollutant spatial distribution time sequence change model construction unit performs prediction time river pollutant spatial distribution change three-dimensional model construction processing in a river based on the prediction time river pollutant displacement data, the river pollutant three-dimensional change model data, the river pollutant spatial distribution model data and in combination with the three-dimensional mechanical design software, and generates river pollutant spatial distribution time sequence change model data.

[0059] (Three) beneficial effects

[0060] The present application provides a river pollutant distribution monitoring system and method based on multi-modal data fusion. The following beneficial effects are provided:

[0061] I. Through the water quality measuring instrument, pollutant parameters of the river measuring point are dynamically collected to realize self-determination and efficient collection of river pollutant information; according to the pollutant parameters of the river measuring point, numerical analysis and scientifically set pollutant threshold of the normal state of the river, the pollution state of the river measuring point is accurately analyzed to realize scientific monitoring of the pollution state of the river measuring point; intelligent detection of the pollution state of the river and accurate collection of the information of the type of pollutants are realized, and the river pollutant monitoring based on multi-modal data fusion is realized.

[0062] II. Through the pollution measuring point of the river based on the pollution state analysis information of the river measuring point and the position sensor, the spatial coordinate information of the river pollution measuring point is efficiently collected, and the intelligent three-dimensional model of the river pollutant is intelligently constructed by combining the intelligent modeling algorithm, so that the intelligent monitoring of the spatial form of the river pollutant is realized; the three-dimensional model of the river is efficiently collected by the unmanned aerial vehicle carrying the three-dimensional laser scanner, and the spatial coordinate of the river is digitally generated by combining the GIS platform, and the intelligent collection of the spatial form of the river is realized by cooperating with the digital modeling technology; according to the spatial coordinate combination information of the river space model and the three-dimensional model data of the river pollutant, numerical processing is carried out to digitally model the spatial distribution form of the river pollutant in the river, so that the dynamic visual monitoring of the spatial distribution state of the river pollutant is realized, and the accuracy of the river pollutant monitoring is improved.

[0063] III. Through the flow rate measuring instrument and the river pollutant monitoring platform input dialog box, the river water flow rate information and the river pollution state change prediction time length information are accurately collected to provide real data support for predictive monitoring of the river pollutant; based on the artificial intelligence algorithm, the intelligent analysis of the river pollutant diffusion distance information per unit time is carried out, and the river pollution state change prediction time length information is combined to scientifically count the diffusion distance of the river pollutant in the prediction time, and the digital technology is intelligently built to realize the intelligent prediction of the diffusion spatial form of the river pollutant based on the real scene; based on the river water flow rate information, the river pollution state change prediction time length information and numerical analysis, the river pollutant displacement information in the prediction time is scientifically counted, and the river pollutant spatial distribution form in the prediction time is scientifically modeled by combining the three-dimensional change model information of the river pollutant and the spatial distribution model information of the river pollutant, so that the real predictive monitoring of the river pollutant change based on multi-modal data fusion is realized, and the applicability and intelligence of the river pollutant monitoring are improved. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1 The module schematic diagram of the river pollutant distribution monitoring system based on multi-modal data fusion provided by the application;

[0065] Figure 2 The flow chart of the river pollutant distribution monitoring method based on multi-modal data fusion provided by the application. DETAILED DESCRIPTION

[0066] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0067] The implementation of the river pollutant distribution monitoring system and method based on multi-modal data fusion is as follows:

[0068] Embodiment 1:

[0069] Please refer to Figure 1 - Figure 2 The method for monitoring river pollutant distribution based on multi-modal data fusion includes the following steps:

[0070] S1, collecting pollutant parameters of a river measurement point;

[0071] S2, performing pollution state analysis processing on the river measurement point according to the pollutant parameters of the river measurement point and the pollutant threshold of the normal state of the river, generating river measurement point pollution state analysis information and performing river pollutant type information search processing, generating river pollutant type search information and performing river pollution state judgment processing, generating river pollution state judgment information, and when it is a normal state, directly ending the river pollutant monitoring operation;

[0072] S3, when it is a pollution state, performing spatial coordinate information collection processing on the river pollution measurement point based on the river measurement point pollution state analysis information, generating river pollution measurement point spatial coordinate data and performing spatial three-dimensional model modeling processing on the river pollutant, generating river pollutant three-dimensional model data;

[0073] S4, collecting river three-dimensional model data and performing spatial coordinate generation processing on the river three-dimensional model, generating river spatial coordinate data and performing three-dimensional model and spatial coordinate data combination processing on the river with the river pollutant three-dimensional model data, generating river spatial model spatial coordinate combination data and performing river pollutant spatial distribution three-dimensional model construction processing on the river with the river pollutant three-dimensional model data, generating river pollutant spatial distribution model data;

[0074] S5, collecting river water flow velocity information and river pollution state change prediction time length;

[0075] S6, based on the river pollutant species search information and different river pollutant characteristics corresponding to the unit time pollutant diffusion distance amount, the unit time pollutant diffusion distance amount of the river pollutant is analyzed and processed, the target river unit time pollutant diffusion distance amount is generated, and the river pollution state change prediction time length is used for statistical processing of the pollutant diffusion distance amount of the river pollutant in the prediction time, and the prediction time river pollutant diffusion distance amount is generated;

[0076] S7, based on the river pollutant three-dimensional model data and the prediction time river pollutant diffusion distance amount, the pollutant space three-dimensional change model of the river pollutant in the prediction time is modeled and processed, and the river pollutant three-dimensional change model data is constructed;

[0077] S8, based on the river water flow velocity information and the river pollution state change prediction time length, the displacement parameter of the river pollutant in the river in the prediction time is statistically processed, the prediction time river pollutant displacement data is generated, and the river pollutant three-dimensional change model data and the river pollutant spatial distribution model data are used for three-dimensional model construction processing of the spatial distribution change of the river pollutant in the river in the prediction time, and the river pollutant spatial distribution time sequence change model data is generated.

[0078] Further, please refer to Figure 1 - Figure 2 The operation steps of collecting the pollutant parameters of the river measurement point are as follows:

[0079] S11, the pollutant species information and the pollutant concentration parameters of the water quality measurement point in the river monitoring area are collected online by the water quality measuring instrument, and the river measurement point pollutant parameter set is generated , ; wherein represents the river measurement point pollutant parameter of the th water quality measurement point, represents the maximum value of the number of water quality measurement points, and the pollutant species includes ammonium nitrogen, nitrite nitrogen, cyanide, phenolic compounds, anionic detergents, phenol, cyanide, arsenic, lead, chromium, cadmium and mercury; the pollutant concentration unit of the water quality measurement point is milligrams per meter; the water quality measuring instrument includes COD measuring instrument, BOD measuring instrument, ammonia nitrogen detector, heavy metal analyzer and nutrient salt detector.

[0080] According to the river measurement point pollutant parameter and the river normal state pollutant threshold, the pollution state analysis information of the river measurement point is generated, the river pollutant species information search processing is performed, the river pollution state judgment information is generated, and the river pollution state judgment processing is performed. When it is normal, the operation steps of directly ending the river pollutant monitoring operation are as follows:

[0081] S21, establishing a set of river normal state pollutant thresholds , ; wherein represents the river normal state pollutant threshold corresponding to the th pollutant type, represents the maximum value of the number of pollutant types, and the river normal state pollutant threshold represents the maximum value of the concentration of a single pollutant when the river is in a normal state, The unit is milligrams per meter;

[0082] S22, comparing the set of river measurement point pollutant parameters with the set of river normal state pollutant thresholds according to the order of the water quality measurement point numbers to generate a set of river measurement point pollution state analysis information based on the comparison of the pollutant concentration values , wherein represents the river measurement point pollution state analysis information of the th water quality measurement point;

[0083] When all pollutant concentrations are not greater than , indicating that the water quality of the th water quality measurement point is not polluted, the river measurement point pollution state analysis information is output as a normal state;

[0084] When there is a pollutant concentration greater than , indicating that the water quality of the th water quality measurement point is polluted by the th pollutant, the river measurement point pollution state analysis information is output as a pollution state, and the th pollutant type text information is also output;

[0085] S23, searching for all pollutant type information of polluted water quality in the target river area based on the set of river measurement point pollution state analysis information using the Boyer-Moore search algorithm to generate river pollutant type search information ; under normal circumstances, river water pollution presents regional distribution, so the pollutant types of river water pollution are the same, and the pollutant concentrations are different;

[0086] S24, based on the river pollutant type search information ​​​The river pollution state judgment information is generated according to the river pollution type information search result;

[0087] When The river pollution type information is not searched in the river pollution state judgment information, indicating that the water quality of the river monitoring area is normal, and the river pollution state judgment information is output as a normal state, and the river pollution monitoring operation is directly ended at this time;

[0088] When The river pollution type information is searched in the river pollution state judgment information, indicating that the water quality of the river monitoring area is polluted, and the river pollution state judgment information is output as a pollution state.

[0089] The river pollution type search unit and the river pollution state judgment unit are mutually matched, the river pollution state intelligent detection and the pollution type information accurate collection are realized, and the river pollution monitoring based on multi-modal data fusion is realized.

[0090] Further, please refer to Figure 1 - Figure 2 When it is a pollution state, the spatial coordinate information of the water quality measurement point corresponding to the pollution state is collected and processed based on the river pollution measurement point state analysis information, the river pollution measurement point spatial coordinate data is generated, and the spatial three-dimensional model modeling processing of the river pollution is performed. The operation steps of generating river pollution three-dimensional model data are as follows:

[0091] S31, when the river pollution state judgment information is a pollution state, the river pollution measurement point state analysis information is collected online through the position sensor The spatial coordinate information of the water quality measurement point corresponding to the pollution state is generated, and the river pollution measurement point spatial coordinate data set is generated , wherein and respectively represent the river pollution measurement point spatial coordinate data of the first and water quality measurement point, The river pollution measurement point spatial coordinate data includes the longitude, latitude and altitude of the river water quality measurement point;

[0092] S32, the Halcon operator is used to process the river pollution measurement point spatial coordinate data set The river pollution measurement point spatial coordinate data to The spatial three-dimensional morphology of water quality measurement points under pollution conditions is numerically constructed, and three-dimensional model data of river pollutants is generated. The three-dimensional model data of river pollutants includes the spatial coordinate information of water quality measurement points under pollution conditions and the spatial three-dimensional model information formed by the water quality measurement points under pollution conditions.

[0093] The steps for collecting 3D river model data and generating spatial coordinates from the river model are as follows: This process involves combining the river's 3D model data with 3D pollutant model data to generate combined spatial coordinate data. This combined spatial coordinate data is then used to construct a 3D model of the spatial distribution of pollutants in the river.

[0094] S41. Using a drone equipped with a 3D laser scanner, scan and collect the 3D physical model of the geographic terrain of the target river, and generate 3D model data of the river.

[0095] S42. Use a GIS platform to generate the geospatial coordinates of the river's 3D model corresponding to the river's 3D model data, and generate a river spatial coordinate dataset. , ;in Indicates the generated first River spatial coordinate data, This represents the maximum number of generated river spatial coordinates, which indicate the longitude, latitude, and altitude of the river's geographical topography.

[0096] S43. Combine the river 3D model data with the river spatial coordinate dataset. Zhonghe River Spatial Coordinate Data Perform combined processing of the river's 3D model and river spatial coordinate data, and generate combined spatial coordinate data of the river spatial model;

[0097] S44. Combine the three-dimensional model data of river pollutants with the spatial coordinates of the river spatial model, and perform coordinate numerical matching between the spatial coordinate parameters of the water quality measurement points under pollution status and the river spatial coordinates to construct a three-dimensional model of the spatial distribution of river pollutants in the river, and generate the spatial distribution model data of river pollutants.

[0098] The river pollution measuring point positioning unit and the river pollution three-dimensional model construction unit cooperate with each other, based on the river measuring point pollution state analysis information and combined with the position sensor, the spatial coordinate information of the river pollution measuring point is efficiently collected, and the river pollution three-dimensional model is intelligently constructed combined with the intelligent modeling algorithm, so that the intelligent monitoring of the spatial form of the river pollution is realized; the river three-dimensional model acquisition unit, the river three-dimensional coordinate decomposition unit and the river space model spatial coordinate combination information construction unit cooperate with each other, the three-dimensional laser scanner is carried by the unmanned aerial vehicle to efficiently collect the river three-dimensional model, and the digitalization of the river spatial coordinates is generated combined with the GIS platform, and the intelligent collection of the spatial form of the river is carried out combined with the digital modeling technology; the river pollution spatial distribution model construction unit, according to the river space model spatial coordinate combination information and the river pollution three-dimensional model data and combined with the numerical processing, the digital modeling of the spatial distribution form of the river pollution in the river is carried out, the dynamic visual monitoring of the spatial distribution state of the river pollution is realized, and the accuracy of the river pollution monitoring is improved.

[0099] Further, please refer to Figure 1 Figure 2 The operation steps of collecting the river water flow velocity information and the river pollution state change prediction time length are as follows:

[0100] S51, the flow velocity measuring instrument is used to collect the water flow velocity information and the flow direction information of the river monitoring area online, and the river water flow velocity information is generated, the unit of the water flow velocity is meter per second;

[0101] The input dialog box of the river pollution monitoring platform is used to collect the prediction time length information corresponding to the spatial distribution state change of the river pollution in the river in the prediction time online, and the river pollution state change prediction time length is generated, the unit of the prediction time length is second.

[0102] Based on the river pollution species search information and the different river pollution characteristic corresponding unit time pollution diffusion distance amount, the unit time pollution diffusion distance amount of the river pollution is analyzed and processed, the target river unit time pollution diffusion distance amount is generated, and the river pollution diffusion distance amount in the prediction time is statistically processed combined with the river pollution state change prediction time length, and the operation steps of generating the prediction time river pollution diffusion distance amount are as follows:

[0103] S61, a set of different river pollution characteristic corresponding unit time pollution diffusion distance amounts corresponding to different river pollution characteristic types is established ; wherein represents the different river pollution characteristic corresponding unit time pollution diffusion distance amount corresponding to the th river pollution characteristic type, ​​This represents the maximum number of river pollutant characteristic types, which indicate all types of pollutants causing water pollution in the river. The corresponding pollutant diffusion distance per unit time for different river pollutant characteristics represents the distance that river pollutants diffuse from the river to surrounding water bodies per unit time, according to standards set for different river pollutant characteristic types. The unit is meters per second;

[0104] S62. Search information on river pollutant types Set of pollutant diffusion distances per unit time corresponding to different river pollutant characteristics Corresponding pollutant diffusion distance per unit time for different river pollutant characteristics By matching keywords related to pollutant types, search information on river pollutant types can be retrieved. Corresponding pollutant characteristics of different rivers and corresponding pollutant diffusion distance per unit time The data is then used to generate the pollutant diffusion distance per unit time in the target river. The specific steps for generating the pollutant diffusion distance per unit time in the target river are as follows:

[0105] S621. Initialize and update the maximum number of iterations T of the algorithm, and randomly initialize the pollutant diffusion distance search for the osprey population location in the optimization space. The location initialization formula is as follows: ,in Indicates the distance of pollutant dispersion by the search osprey. In spatial dimension Different river pollutant characteristics correspond to pollutant diffusion distance per unit time. The location in the search space, To find the optimal lower boundary, that is, the set of pollutant diffusion distances per unit time corresponding to different river pollutant characteristics. The lower bound of the search space, To find the optimal upper boundary, that is, the set of pollutant diffusion distances per unit time corresponding to different river pollutant characteristics. The upper bound of the search space, This represents a random number within the range [0,1].

[0106] S622. Exploration Phase: The exploration phase of pollutant dispersion distance search osprey population renewal is modeled based on the simulation of the natural behavior of this species. The pollutant dispersion distance search osprey population is calculated based on the pollutant dispersion distance measurements per unit time corresponding to different river pollutant characteristics. Randomly search for information related to river pollutant types within the search space. Matching different river pollutant characteristics and corresponding pollutant diffusion distance per unit time The target's location is determined and attacked. Based on the simulated movement of the pollutant dispersion distance search osprey towards the target, the new position of the corresponding pollutant dispersion distance search osprey is updated. The formula for updating the pollutant dispersion distance search osprey position is as follows: ,in Indicates the distance of pollutant dispersion by the search osprey. After the update, the spatial dimension is Different river pollutant characteristics correspond to pollutant diffusion distance per unit time. The position in the search space; This represents the pollutant diffusion distance measurement set per unit time corresponding to pollutant characteristics in different rivers, obtained by searching the Osprey. Searching the search space for information related to river pollutant types Matching different river pollutant characteristics and corresponding pollutant diffusion distance per unit time The location of the target; This represents a constant that takes the value 1 or 2; if the updated position is better, the initial position of the pollutant diffusion distance search osprey is replaced according to the position replacement formula during the exploration phase. The position replacement formula during the exploration phase is: ,in Indicating the distance of pollutant dispersion during the exploration phase, the search osprey... After the update, the spatial dimension is Different river pollutant characteristics correspond to pollutant diffusion distance per unit time. The optimal position in the search space; express Different river pollutant characteristics at different locations correspond to pollutant diffusion distance per unit time Search information on river pollutant types fitness value, express Different river pollutant characteristics at different locations correspond to pollutant diffusion distance per unit time Search information on river pollutant types fitness value;

[0107] S623. Development Phase: Pollutant Dispersion Distance Search - Osprey Pollutant Dispersion Distance per Unit Time Corresponding to Pollutant Characteristics in Different Rivers Search information on hunting and consuming river pollutants in the search space Matching different river pollutant characteristics and corresponding pollutant diffusion distance per unit time The goal of this algorithm for updating the osprey population through pollutant dispersion distance search is to model the natural behavior of ospreys in this field by simulating their behavior. The algorithm calculates new random locations as suitable locations for searching for river pollutant species and their potential for consumption. the different river pollutant characteristic corresponding pollutant diffusion distance amount per unit time the position of the target, calculate the new suitable food and river pollutant species search information the different river pollutant characteristic corresponding pollutant diffusion distance amount per unit time the position of the target wherein denotes the pollutant diffusion distance search falcon the updated set of different river pollutant characteristic corresponding pollutant diffusion distance amount per unit time in the spatial dimension of the new random position in the search space suitable food and river pollutant species search information the different river pollutant characteristic corresponding pollutant diffusion distance amount per unit time the position of the target denotes the current iteration number of the algorithm; if the value of the objective function is improved at this new position, replace the initialization position of the pollutant diffusion distance search falcon before updating according to the development stage position replacement formula, the development stage position replacement formula is wherein denotes the development stage pollutant diffusion distance search falcon the updated set of different river pollutant characteristic corresponding pollutant diffusion distance amount per unit time in the spatial dimension of the optimal position in the search space ; denotes the different river pollutant characteristic corresponding pollutant diffusion distance amount per unit time at the position the fitness value of the river pollutant species search information

[0108] S624, output the river pollutant species search information when the algorithm meets the maximum iteration number the most matched different river pollutant characteristic corresponding pollutant diffusion distance amount per unit time , otherwise continue to execute steps S622 to S623 until the maximum iteration number is met

[0109] S625, output the different river pollutant characteristic corresponding pollutant diffusion distance amount per unit time in step S624 generate the target river pollutant diffusion distance amount per unit time through data identification, the unit of the target river pollutant diffusion distance amount per unit time is meter per second

[0110] S63, the river pollution state change prediction time length and the target river unit time pollutant diffusion distance amount are multiplied and statistically processed, and the prediction time river pollutant diffusion distance amount is calculated. The prediction time river pollutant diffusion distance amount represents the distance amount of the river pollutant diffusion in the water body to the surrounding water body in the prediction time. The unit of the prediction time river pollutant diffusion distance amount is meter.

[0111] Based on the river pollutant three-dimensional model data and the prediction time river pollutant diffusion distance amount, the river pollutant spatial three-dimensional change model in the prediction time is modeled and processed, and the operation steps of constructing the river pollutant three-dimensional change model data are as follows:

[0112] S71, the river pollutant three-dimensional model data is imported into the three-dimensional mechanical design software, and the thickness instruction in the three-dimensional mechanical design software is used to thicken the corresponding three-dimensional model around the river pollutant three-dimensional model data according to the distance value corresponding to the prediction time river pollutant diffusion distance amount, and the river pollutant three-dimensional change model data is constructed. Any one of UG, CATIA and SolidWorks in three-dimensional mechanical design software.

[0113] Based on the river water flow velocity information and the river pollution state change prediction time length, the river pollutant displacement parameter in the river in the prediction time is statistically processed, the prediction time river pollutant displacement data is generated, and the prediction time river pollutant spatial distribution change three-dimensional model is constructed with the river pollutant three-dimensional change model data and the river pollutant spatial distribution model data, and the operation steps of generating the river pollutant spatial distribution time sequence change model data are as follows:

[0114] S81, the river water flow velocity information and the river pollution state change prediction time length are multiplied and statistically processed, and the prediction time river pollutant displacement data is calculated. The unit of the prediction time river pollutant displacement data is meter. The prediction time river pollutant displacement data represents the displacement information of the river pollutant with the theoretical movement of the river water body in the prediction time. The prediction time river pollutant displacement data includes the distance information and the direction information of the river pollutant movement;

[0115] S82, import the river pollutant three-dimensional change model data and the river pollutant spatial distribution model data into the three-dimensional mechanical design software, and use the simulation module of the three-dimensional mechanical design software to set the three-dimensional model corresponding to the river pollutant three-dimensional change model data as the initial position according to the position of the three-dimensional model corresponding to the river pollutant three-dimensional change model data in the river, control the three-dimensional model corresponding to the river pollutant three-dimensional change model data to move to the predicted position in the river based on the river pollutant displacement data at the predicted time, and construct the river pollutant spatial distribution time sequence change model data, which represents the spatial distribution state information of the river pollutant in the river water body after the river pollutant theoretically moves with the river water body in the predicted time.

[0116] Through the cooperation between the river water body flow velocity information acquisition unit and the river pollution state change prediction time acquisition unit, the river water body flow velocity information and the river pollution state change prediction time information are accurately collected through the flow velocity measuring instrument and the river pollution monitoring platform input dialog box, which provides real data support for predictive monitoring of river pollutants; the river pollutant diffusion distance amount analysis unit, the predicted time river pollutant diffusion distance amount statistical unit and the river pollutant three-dimensional change model construction unit cooperate with each other, intelligently analyze the river pollutant diffusion distance amount information based on the artificial intelligence algorithm, and combine the river pollution state change prediction time information to scientifically count the predicted time river pollutant diffusion distance amount, and intelligently build the river pollutant spatial form at the predicted time based on the digital technology, realize intelligent prediction of the river pollutant diffusion spatial form change based on the real scene; the predicted time river pollutant displacement statistical unit and the river pollutant spatial distribution time sequence change model construction unit cooperate with each other, scientifically count the predicted time river pollutant displacement information based on the river water body flow velocity information, the river pollution state change prediction time information and numerical analysis, and scientifically model the spatial distribution form of the river pollutant in the river at the predicted time based on the river pollutant three-dimensional change model information and the river pollutant spatial distribution model information, realize real predictive monitoring of the river pollutant change based on multi-modal data fusion, and improve the applicability and intelligence of the river pollutant monitoring.

[0117] Embodiment 2:

[0118] Please refer to Figure 1 - Figure 2 , the river pollutant distribution monitoring system based on multi-modal data fusion, for realizing the river pollutant distribution monitoring method based on multi-modal data fusion, the system comprising a river pollution state recognition module, a river pollutant spatial distribution monitoring module, and a river pollutant spatial distribution change monitoring module.

[0119] The river pollution state identification module comprises a river measurement point pollutant parameter acquisition unit, a river normal state pollutant threshold storage unit, a river measurement point pollution state analysis unit, a river pollutant type search unit, and a river pollution state judgment unit.

[0120] The river measurement point pollutant parameter acquisition unit acquires the pollutant parameters of the river measurement point through a water quality measuring instrument; the river normal state pollutant threshold storage unit is configured to store the pollutant threshold of the normal state of the river; the river measurement point pollution state analysis unit analyzes and processes the pollution state of the river measurement point according to the pollutant parameters of the river measurement point and the pollutant threshold of the normal state of the river, and generates river measurement point pollution state analysis information; the river pollutant type search unit searches and processes the river pollutant type information according to the river measurement point pollution state analysis information, and generates river pollutant type search information; and the river pollution state judgment unit judges the pollution state of the river according to the river pollutant type search information, and generates river pollution state judgment information.

[0121] The river pollutant spatial distribution monitoring module comprises a river pollution measurement point positioning unit, a river pollutant three-dimensional model construction unit, a river three-dimensional model acquisition unit, a river three-dimensional coordinate decomposition unit, a river spatial model spatial coordinate combination information construction unit, and a river pollutant spatial distribution model construction unit.

[0122] The river pollution measurement point positioning unit acquires and processes the spatial coordinate information of the river pollution measurement point based on the river measurement point pollution state analysis information and in combination with a position sensor, and generates river pollution measurement point spatial coordinate data; the river pollutant three-dimensional model construction unit models the spatial three-dimensional model of the river pollutant according to the river pollution measurement point spatial coordinate data, and generates river pollutant three-dimensional model data; the river three-dimensional model acquisition unit acquires the river three-dimensional model data by means of a three-dimensional laser scanner carried by a drone; the river three-dimensional coordinate decomposition unit generates the spatial coordinate of the river three-dimensional model according to the river three-dimensional model data and in combination with a GIS platform, and generates river spatial coordinate data; the river spatial model spatial coordinate combination information construction unit combines the three-dimensional model and the spatial coordinate data of the river according to the river spatial coordinate data and the river pollutant three-dimensional model data, and generates river spatial model spatial coordinate combination data; and the river pollutant spatial distribution model construction unit constructs the spatial distribution three-dimensional model of the river pollutant in the river according to the river spatial model spatial coordinate combination data and the river pollutant three-dimensional model data, and generates river pollutant spatial distribution model data.

[0123] The river pollutant spatial distribution change monitoring module comprises a river water body flow velocity information acquisition unit, a river pollution state change prediction time acquisition unit, a different river pollutant characteristic corresponding unit time pollutant diffusion distance quantity storage unit, a river unit time pollutant diffusion distance quantity analysis unit, a prediction time river pollutant diffusion distance quantity statistical unit, a river pollutant three-dimensional change model construction unit, a prediction time river pollutant displacement statistical unit and a river pollutant spatial distribution time sequence change model construction unit.

[0124] The river water body flow velocity information acquisition unit acquires river water body flow velocity information through a flow velocity measuring instrument; the river pollution state change prediction time acquisition unit acquires the river pollution state change prediction time length through an input dialog box of the river pollutant monitoring platform; the different river pollutant characteristic corresponding unit time pollutant diffusion distance quantity storage unit is used for storing different river pollutant characteristic corresponding unit time pollutant diffusion distance quantities; the river unit time pollutant diffusion distance quantity analysis unit performs unit time pollutant diffusion distance quantity analysis processing of river pollutants based on river pollutant species search information and different river pollutant characteristic corresponding unit time pollutant diffusion distance quantities, and generates target river unit time pollutant diffusion distance quantities; the prediction time river pollutant diffusion distance quantity statistical unit performs pollutant diffusion distance quantity statistical processing of river pollutants in a prediction time according to the target river unit time pollutant diffusion distance quantities and the river pollution state change prediction time length, and generates prediction time river pollutant diffusion distance quantities; the river pollutant three-dimensional change model construction unit performs pollutant spatial three-dimensional change model modeling processing of river pollutants in the prediction time based on river pollutant three-dimensional model data, the prediction time river pollutant diffusion distance quantities and in combination with a three-dimensional mechanical design software, and constructs river pollutant three-dimensional change model data; the prediction time river pollutant displacement statistical unit performs displacement parameter statistical processing of river pollutants in the prediction time in a river based on the river water body flow velocity information and the river pollution state change prediction time length, and generates prediction time river pollutant displacement data; and the river pollutant spatial distribution time sequence change model construction unit performs prediction time river pollutant spatial distribution change three-dimensional model construction processing in a river based on the prediction time river pollutant displacement data, the river pollutant three-dimensional change model data, river pollutant spatial distribution model data and in combination with the three-dimensional mechanical design software, and generates river pollutant spatial distribution time sequence change model data.

[0125] Although the embodiments of the present application have been shown and described, it is to be understood that various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for monitoring river pollutant distribution based on multimodal data fusion, characterized in that, The method includes the following steps: S1. Collect pollutant parameters at river measurement points; S2. Perform pollution status analysis and processing of river measurement points, generate pollution status analysis information of river measurement points, perform river pollutant type information search and processing, generate river pollutant type search information, perform river pollution status judgment processing, generate river pollution status judgment information, and directly end the river pollutant monitoring operation when it is in a normal state. S3. When the river is in a polluted state, the spatial coordinate information of the river pollution measurement points is collected and processed to generate the spatial coordinate data of the river pollution measurement points. The spatial three-dimensional model of the river pollutants is then processed to generate the three-dimensional model data of the river pollutants. S4. Collect river 3D model data and process the spatial coordinate generation of the river 3D model to generate river spatial coordinate data. Combine the river 3D model and spatial coordinate data with the river pollutant 3D model data to generate river spatial model spatial coordinate combination data. Combine the river spatial model and spatial coordinate combination data with the river pollutant 3D model data to construct a 3D model of the spatial distribution of river pollutants in the river to generate river pollutant spatial distribution model data. S5. Collect information on river flow velocity and predict the time frame for changes in river pollution status; S6. Perform analysis and processing of the pollutant diffusion distance per unit time in the river, generate the pollutant diffusion distance per unit time in the target river, and perform statistical processing of the pollutant diffusion distance in the river within the predicted time period with the predicted time length of the river pollution state change, to generate the pollutant diffusion distance in the river at the predicted time. S7. Model and process the three-dimensional spatial variation model of river pollutants within the predicted time period to construct the three-dimensional variation model data of river pollutants. S8. Perform statistical processing of the displacement parameters of river pollutants in the river within the predicted time, generate river pollutant displacement data for the predicted time, and perform three-dimensional model construction processing on the river pollutant spatial distribution change in the river within the predicted time with the river pollutant three-dimensional change model data and the river pollutant spatial distribution model data to generate river pollutant spatial distribution temporal change model data.

2. The method for monitoring river pollutant distribution based on multimodal data fusion according to claim 1, characterized in that: S1 includes the following steps: S11. Collect pollutant type information and pollutant concentration parameters at water quality measurement points in the river monitoring area online using a water quality measuring instrument, and generate a pollutant parameter set for the river measurement points. , ;in Indicates the number of collections Pollutant parameters at river monitoring points at various water quality measurement sites. This represents the maximum number of water quality measurement points.

3. The method for monitoring river pollutant distribution based on multimodal data fusion according to claim 2, characterized in that: S2 includes the following steps: S21. Establish a set of pollutant thresholds for normal river conditions. The include ;in Indicates the first Pollutant thresholds for each type of pollutant under normal river conditions; S22, the above The above According to the water quality measurement point numbering, and in order with the above The above The pollutant concentration values ​​were compared, and a pollution status analysis information set for river measurement points was generated based on the comparison results. The include ;in Indicates the first Pollution status analysis information of river measurement points at individual water quality measurement points; when The concentrations of pollutants in the medium are all no greater than Then output the above. This is the normal state; when There are pollutant concentrations greater than Then output the above. The system is in a contaminated state, and the output is the first... Textual information on the types of pollutants; S23, Using the Boyer-Moore search algorithm based on the above The above The search retrieves information on all types of pollutants polluting the water in the target river area and generates river pollutant type search information. ; S24, based on the above The system searches for information on river pollutant types and generates information on the river pollution status based on the search results. when If no information on the types of river pollutants is found, the river pollution status judgment information is output as normal, and the river pollutant monitoring operation is terminated directly. when If the search engine finds information on the types of pollutants in the river, it will output the river pollution status information as the pollution status.

4. The method for monitoring river pollutant distribution based on multimodal data fusion according to claim 3, characterized in that: S3 includes the following steps: S31. When the river pollution status assessment information indicates a pollution status, the data is collected online via a location sensor. To generate a dataset of spatial coordinates of river pollution measurement points, corresponding to the water quality measurement points under pollution conditions. The include and ;in and They represent the first and Spatial coordinate data of river pollution measurement points at various water quality measurement sites. ; S32. Apply the Halcon operator to the... The above to The spatial three-dimensional morphology of water quality measurement points under pollution conditions is numerically constructed, and three-dimensional model data of river pollutants are generated.

5. The method for monitoring river pollutant distribution based on multimodal data fusion according to claim 4, characterized in that... S4 includes the following steps: S41. Using a drone equipped with a 3D laser scanner, scan and collect the 3D physical model of the geographic terrain of the target river, and generate 3D model data of the river. S42. Using a GIS platform, the geospatial coordinates of the river's 3D model corresponding to the river's 3D model data are generated, and a river spatial coordinate dataset is generated. The include ;in Indicates the generated first Spatial coordinate data of one river; S43, Combine the river 3D model data with the... The above Perform combined processing of the river's 3D model and river spatial coordinate data, and generate combined spatial coordinate data of the river spatial model; S44. The three-dimensional model data of river pollutants and the spatial coordinate combination data of the river spatial model are combined according to the spatial coordinate parameters of the water quality measurement points under pollution status and the spatial coordinates of the river to construct a three-dimensional model of the spatial distribution of river pollutants in the river and generate the spatial distribution model data of river pollutants.

6. The method for monitoring river pollutant distribution based on multimodal data fusion according to claim 5, characterized in that: S5 includes the following steps: S51. Collect the water flow velocity and flow direction information of the river monitoring area online through a flow velocity meter, and generate river water flow velocity information. The unit of water flow velocity is meters per second. The river pollutant monitoring platform collects online information on the spatial distribution changes of river pollutants within the predicted time frame through its input dialog box, and generates the predicted time frame for changes in river pollution status.

7. The method for monitoring river pollutant distribution based on multimodal data fusion according to claim 6, characterized in that: S6 includes the following steps: S61. Establish a set of pollutant diffusion distances per unit time corresponding to different river pollutant characteristics. The include ;in Indicates the first The pollutant diffusion distance per unit time corresponding to different river pollutant characteristics; S62, the above With the The above Perform keyword matching for pollutant types to search for the aforementioned The corresponding The specific steps for generating the target river's pollutant diffusion distance per unit time are as follows: The data is then labeled to generate the target river's pollutant diffusion distance per unit time. S621. Initialize and update the maximum number of iterations T of the algorithm and randomly initialize the pollutant diffusion distance in the optimization space to search for the location of the osprey population. S622, Exploration Phase: The exploration phase of pollutant dispersion distance search osprey population renewal is modeled based on the simulation of the natural behavior of this species. The pollutant dispersion distance search osprey is described in... Randomly search the search space for the match with the The matching The target location is determined and attacked. Based on the simulated pollutant diffusion distance search osprey moving towards the target, the new position of the corresponding pollutant diffusion distance search osprey is updated. If the updated new position is better, the initial position of the pollutant diffusion distance search osprey is replaced according to the position replacement formula in the exploration phase. S623, Development Phase, Pollutant Dispersion Distance Search Osprey in the... Hunting and eating in the search space of the described The matching The goal of the algorithm for updating the pollutant dispersion distance search osprey population is to model the natural behavior of ospreys in this field by simulating their behavior, and to calculate new random locations as suitable feeding grounds for the ospreys. The matching If the value of the objective function improves at this new location, the initial position of the pollutant diffusion distance search osprey is replaced with the position replacement formula during the development phase. S624. When the algorithm satisfies the maximum number of iterations, the output is the same as described above. The most matching Otherwise, continue executing steps S622 to S623 until the maximum number of iterations is met; S625, The output in step S624 The data identification process generates the pollutant diffusion distance per unit time in the target river. S63. Multiply the predicted time length of the river pollution state change with the pollutant diffusion distance per unit time of the target river and perform statistical processing to measure the pollutant diffusion distance of the river during the predicted time. The pollutant diffusion distance of the river during the predicted time represents the distance that the pollutants of the river diffuse from the river water to the surrounding water bodies within the predicted time.

8. The method for monitoring river pollutant distribution based on multimodal data fusion according to claim 7, characterized in that: S7 includes the following steps: S71. Import the three-dimensional model data of the river pollutants into the three-dimensional mechanical design software, and use the thickness command in the three-dimensional mechanical design software to thicken the three-dimensional model around the three-dimensional model data of the river pollutants according to the distance value corresponding to the predicted river pollutant diffusion distance, and construct the three-dimensional change model data of the river pollutants.

9. The method for monitoring river pollutant distribution based on multimodal data fusion according to claim 8, characterized in that: S8 includes the following steps: S81. Multiply the river water flow velocity information with the predicted time length of the river pollution state change and perform statistical processing to measure the displacement data of river pollutants over the predicted time. S82. Import the three-dimensional variation model data of river pollutants and the spatial distribution model data of river pollutants into the three-dimensional mechanical design software. Using the simulation module of the three-dimensional mechanical design software, the three-dimensional model corresponding to the three-dimensional variation model data of river pollutants is initially positioned in the river according to the position of the three-dimensional model corresponding to the three-dimensional variation model data of river pollutants in the river. Based on the predicted time river pollutant displacement data, the three-dimensional model corresponding to the three-dimensional variation model data of river pollutants is controlled to move directionally to the predicted position in the river, and the temporal variation model data of spatial distribution of river pollutants is constructed.

10. A river pollutant distribution monitoring system based on multimodal data fusion, used to implement the river pollutant distribution monitoring method based on multimodal data fusion as described in any one of claims 1-9, characterized in that: The system includes a river pollution status identification module, a river pollutant spatial distribution monitoring module, and a river pollutant spatial distribution change monitoring module.

Images