A water quality sampling and monitoring method and system for a smart water station based on ultraviolet spectroscopy

Abstract

The present application relates to the technical field of water quality detection, and discloses a water quality sampling and monitoring method and system for a smart water station based on ultraviolet spectra, including: dividing the area of the smart water station to obtain multiple water areas; performing water quality analysis based on the ultraviolet spectral data of the water samples at the central sampling points of each water area to obtain normal water areas and abnormal water areas; performing water quality analysis on the water samples at all sampling points within the abnormal water areas to obtain pollution source sampling points; by performing regional processing on the smart water station, the present application reduces the number of water samples collected and accelerates the water quality detection process; different water quality analysis methods are adopted in different water quality analysis stages to achieve dynamic adjustment of the analysis process, determine the sampling point closest to the pollution source, and facilitate the treatment of the water quality of the water station; the model parameters of the water quality detection model are optimized by using a multi-objective optimization method, effectively avoiding falling into local optimality when dealing with multi-output objective problems and improving the accuracy of water quality detection results.

Claims

1. A water quality sampling and monitoring method for a smart water station based on ultraviolet spectroscopy, characterized in that: include: The smart water station is divided into regions to obtain multiple water areas; According to the ultraviolet spectrum data of water samples from the central sampling point of each water area, water quality analysis is carried out to obtain normal water areas and abnormal water areas; By analyzing the environmental information of the abnormal water area, the water area boundary is optimized to obtain an updated abnormal water area range, wherein the optimization process includes translation processing and stretching processing; Perform water quality analysis on water samples from all sampling points within the updated abnormal water area to obtain the pollution source sampling points so as to monitor the water quality of the smart water station in real time; The method of analyzing the environmental information of the abnormal water area and optimizing the water area boundary to obtain an updated abnormal water area range includes: According to the preset pressure sensor, the flow direction of the water flow is determined in the abnormal water area in combination with the water flow pressure data, and the boundary of the abnormal water area is translated to obtain a moving boundary; Determine the maximum diffusion distance of pollutants according to a preset pollution diffusion model, stretch the moving boundary to obtain an optimized boundary; According to the optimized boundary, an updated abnormal water area range is obtained; The water quality analysis of all the water samples at the sampling points within the updated abnormal water area is performed to obtain the pollution source sampling points so as to monitor the water quality of the smart water station in real time, including: Obtain water samples from all sampling points within the updated abnormal water area; In the preset sliding window, the spectrum data of the water sample at each sampling point is collected respectively to obtain the ultraviolet spectrum data of the water samples at multiple sampling points; Through the preset water quality detection model, the ultraviolet spectrum data of the water sample at each sampling point is analyzed to obtain water quality parameter information; Performing an abnormal analysis on the water quality parameter information to obtain normal sampling points and abnormal sampling points; Among the abnormal sampling points, the sampling points with the highest abnormality in water quality parameters are selected as the pollution source sampling points.

2. The water quality sampling and monitoring method of a smart water station based on ultraviolet spectroscopy according to claim 1 is characterized in that: The water quality analysis is performed based on the ultraviolet spectrum data of the water samples at the central sampling point of each water area to obtain normal water areas and abnormal water areas, including: In the preset sliding window, UV spectrum data of water samples at the central sampling point of each water area is collected to obtain multiple sets of UV spectrum data; By analyzing the absorbance values ​​of the multiple groups of ultraviolet spectral data, corresponding feature vectors are constructed, and the water quality of the water samples at the central sampling point of each water area is analyzed to obtain normal water areas and abnormal water areas.

3. The water quality sampling and monitoring method of a smart water station based on ultraviolet spectroscopy according to claim 2 is characterized in that: In the preset sliding window, ultraviolet spectrum data is collected for water samples at the central sampling point of each water area, and multiple sets of ultraviolet spectrum data are obtained, including: According to the historical UV spectrum data, the sliding window and sliding step size are obtained through the preset window optimization model; According to the sliding step length, ultraviolet spectral data of water samples at each central sampling point of the water area are collected in the sliding window respectively, and the sliding window is filled with ultraviolet spectral data to obtain multiple groups of ultraviolet spectral data.

4. The water quality sampling and monitoring method of a smart water station based on ultraviolet spectroscopy according to claim 2 is characterized in that: By analyzing the absorbance values ​​of the multiple sets of ultraviolet spectral data, corresponding feature vectors are constructed, and the water quality of the water samples at the central sampling point of each water area is analyzed to obtain normal water areas and abnormal water areas, including: Based on historical UV spectrum data and corresponding water quality data, multiple specific wavelengths related to water quality are obtained; At each of the specific wavelengths, the absorbance value of each set of ultraviolet spectrum data is extracted to obtain a plurality of absorbance values; Combine multiple absorbance values ​​of each group to obtain a characteristic vector of each group of ultraviolet spectrum data; The feature vector is input into a pre-trained water quality classification model, and the water quality of the water sample at the central sampling point of each water area is analyzed to obtain normal water areas and abnormal water areas.

5. The water quality sampling and monitoring method of a smart water station based on ultraviolet spectroscopy according to claim 1 is characterized in that: The preset water quality detection model is used to analyze the ultraviolet spectrum data of the water sample at each sampling point to obtain water quality parameter information, including: Based on the historical water quality data of water samples at the sampling points, a pre-trained water quality detection model is obtained in combination with the multi-objective particle swarm optimization method; The ultraviolet spectrum data of the water sample at each sampling point is input into the pre-trained water quality detection model to obtain the water quality parameter information.

6. The water quality sampling and monitoring method of a smart water station based on ultraviolet spectroscopy according to claim 5 is characterized in that: The pre-trained water quality detection model is obtained based on the historical water quality data of the water samples at the sampling points and combined with the multi-objective particle swarm optimization method, including: Construct an initial neural network model according to the preset model parameters; Initializing a particle swarm according to the initial neural network model and preset particle swarm algorithm parameters to obtain an initial particle swarm, wherein particles in the initial particle swarm represent weights and bias values ​​of the initial neural network model; According to a preset optimization goal, the initial particle swarm is updated until a preset maximum number of iterations is reached to obtain an optimal solution set; Substituting the optimal solution set into the initial neural network model to obtain a water quality detection model; The water quality detection model is trained using historical ultraviolet spectrum data of water samples at sampling points and corresponding historical water quality data to obtain a pre-trained water quality detection model.

7. The water quality sampling and monitoring method of a smart water station based on ultraviolet spectroscopy according to claim 6 is characterized in that: The initial particle swarm is updated according to a preset optimization target until a preset maximum number of iterations is reached to obtain an optimal solution set, including: Analyze the solutions corresponding to the particles according to the preset optimization objectives and obtain multiple non-inferior solutions; storing the plurality of non-inferior releases into a pre-created external archive; Updating the non-inferior solutions in the external file by using the Euclidean distance between the non-inferior solutions and a preset critical distance; The particles in the initial particle swarm are updated until the preset maximum number of iterations is reached and the non-inferior solution meets the preset external file size, and an updated non-inferior solution is obtained; According to the updated non-inferior solutions in the external archive, an optimal solution set is obtained.

8. A water quality sampling and monitoring system for a smart water station based on ultraviolet spectroscopy, characterized in that: A method for sampling and monitoring water quality of a smart water station based on ultraviolet spectroscopy according to any one of claims 1 to 7, comprising: The water area division module divides the smart water station into regions and obtains multiple water areas; The abnormal water area detection module analyzes water quality based on the ultraviolet spectrum data of water samples at the central sampling point of each water area to obtain normal water areas and abnormal water areas; The pollution source sampling point detection module optimizes the water area boundary by analyzing the environmental information of the abnormal water area to obtain an updated abnormal water area range, wherein the optimization processing includes translation processing and stretching processing. Water quality analysis is performed on water samples from all sampling points within the updated abnormal water area to obtain the pollution source sampling points, so as to monitor the water quality of the smart water station in real time.

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