Method and system for determining water quality risk value of industrial sewage

Abstract

The invention provides a method and system for determining a water quality risk value of industrial sewage, and the method comprises the steps: obtaining water quality monitoring data of different monitoring points, obtaining a physical index parameter, a chemical index parameter and a biological index parameter, and constructing a water quality parameter of a target water area; the method comprises the following steps: training historical physical index parameters, historical chemical index parameters and historical biological index parameters of historical water quality monitoring data to obtain a water quality monitoring deduction model, and deducing water quality parameters of a target water area through the water quality monitoring deduction model to obtain an initial water quality risk value; the corresponding actual index parameters are obtained by updating the water quality monitoring data of different monitoring points in real time, the parameters of the water quality monitoring deduction model are optimized, and the optimized water quality risk value is obtained through deduction again. The industrial sewage is subjected to multi-index analysis, the water quality risk trend is predicted, and the water quality monitoring accuracy of the industrial sewage is improved.

Description

Technical Field

[0001] The present invention relates to the field of sewage quality monitoring, and in particular to a method and system for determining water quality risk values ​​of industrial sewage. Background Art

[0002] Industrial wastewater usually contains a variety of complex components, and the accumulation of pollutants can lead to environmental pollution events such as water quality degradation and eutrophication. Therefore, it is necessary to effectively monitor industrial wastewater and determine its risk value; At present, the existing technology mainly analyzes single indicators of industrial wastewater. The monitoring of industrial wastewater with complex components cannot comprehensively assess water quality risks, and the accuracy of water quality risk value monitoring is poor. Furthermore, the existing technology lacks prediction of future water quality risks and cannot respond to potential risks in a timely manner, resulting in poor accuracy in water quality monitoring of industrial wastewater. Summary of the invention

[0003] In order to solve the above problems, the present invention proposes a method and system for determining the water quality risk value of industrial wastewater, which realizes multi-layer indicator analysis of industrial wastewater and prediction of water quality risk trends, thereby improving the accuracy of water quality monitoring of industrial wastewater.

[0004] To achieve the above object, an embodiment of the present invention provides a method for determining a water quality risk value of industrial wastewater, comprising: Acquire water quality monitoring data from different monitoring points, select representative characteristic indicators of the water quality monitoring data from different monitoring points by comparing the neighborhood radius of characteristic indicators, obtain physical indicator parameters, chemical indicator parameters and biological indicator parameters, and construct water quality parameters of the target water area; Taking historical physical indicator parameters of historical water quality monitoring data as auxiliary points, a number of physical-chemical indicator change curves are obtained by fitting the historical chemical indicator parameters of historical monitoring data corresponding to each auxiliary point, and taking the historical biological indicator parameters of historical monitoring data corresponding to each auxiliary point as smoothing factors, a number of comprehensive indicator change curves are obtained by moving average of the several physical-chemical indicator change curves, and a preset deduction model parameter library is updated based on the several comprehensive indicator change curves to obtain a water quality monitoring deduction model; The water quality parameters of the target water area are input into the water quality monitoring deduction model, and the auxiliary point that meets the preset deviation requirements is used as the deduction starting point for deduction and the deduction value of each indicator parameter is recorded. Through different preset red line thresholds and time intervals of the preset prediction time interval, the number of time intervals in which the deduced value of each indicator exceeds the standard is obtained, and the initial water quality risk value is calculated; Update the water quality monitoring data of different monitoring points in real time to obtain the corresponding actual indicator parameters, calculate the difference between the actual indicator parameters and the deduced values ​​of each indicator parameter, update the parameter library of the water quality monitoring deduction model according to the difference calculation results, and re-deduct through the updated water quality monitoring deduction model to obtain the optimized water quality risk value.

[0005] The embodiment of the present invention proposes a method for determining the water quality risk value of industrial wastewater. By performing physical, biological and chemical multi-level indicator analysis on water quality monitoring data from different monitoring points, the water quality status of the target water area can be analyzed more objectively and comprehensively. The accuracy of determining the water quality risk value can be further improved through multi-indicator analysis. Furthermore, the historical water quality monitoring data is also divided into three levels of physical, chemical and biological indicators. The physical indicator parameters are used as auxiliary points, and several physical-chemical indicator change curves are fitted in combination with the chemical indicator parameters. Then, the biological indicator parameters are combined for smoothing optimization to obtain several comprehensive indicator change curves. The water quality monitoring deduction model is obtained by training. The multi-indicator joint training improves the robustness of the water quality monitoring deduction model, thereby improving the accuracy of determining the water quality risk value. Degree, by selecting the deduction starting point for deduction and recording the deduced values ​​of various indicator parameters, using fixed-point deduction to reflect the changes in indicator parameters is helpful to improve the accuracy of water quality monitoring, and then the initial water quality risk value is calculated through different preset red line thresholds and preset prediction time intervals. Time intervals, early warning of future indicator change trends, to ensure the reliability of water quality monitoring, and also through real-time updating of water quality monitoring data at different monitoring points, and feedback to optimize the water quality monitoring deduction model, to achieve continuous optimization and updating of the model, so as to obtain more reliable water quality risk values. Therefore, through multi-level analysis of numerical monitoring data, the water quality monitoring deduction model is continuously optimized and updated, so as to obtain more reliable and accurate water quality risk values, thereby improving the accuracy of water quality monitoring of industrial wastewater.

[0006] Furthermore, the water quality monitoring data of different monitoring points are obtained, and representative characteristic indicators of the water quality monitoring data of different monitoring points are selected by comparing the neighborhood radius of characteristic indicators, and physical indicator parameters, chemical indicator parameters and biological indicator parameters are obtained to construct the water quality parameters of the target water area, including: Respectively calculating the physical characteristic neighborhood radius, chemical characteristic neighborhood radius and biological characteristic neighborhood radius of the water quality monitoring data of the different monitoring points; Compare the physical characteristic neighborhood radius, chemical characteristic neighborhood radius and biological characteristic neighborhood radius of the water quality monitoring data of the different monitoring points one by one, take the physical characteristic, chemical characteristic and biological characteristic with the largest corresponding neighborhood radius as the representative characteristic index, and obtain the physical characteristic index value, chemical characteristic index value and biological characteristic index value corresponding to the water quality monitoring data of the different monitoring points; The physical characteristic index values, chemical characteristic index values ​​and biological characteristic index values ​​corresponding to the water quality monitoring data at different monitoring points are respectively divided by the preset alignment factors and the absolute values ​​are respectively calculated to obtain the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data at different monitoring points; The physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points are aligned in time domain, and the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points with the same time domain are integrated into the water quality parameters of the target water area.

[0007] The embodiment of the present invention proposes a method for determining the water quality risk value of industrial wastewater. By performing neighborhood radius analysis on the water quality monitoring data of different monitoring points at multiple levels of physics, chemistry and biology, representative characteristic indicators are selected, which can reduce data redundancy, and multi-factor analysis can improve the accuracy of subsequent model deduction. At the same time, the parameters at multiple levels of physics, chemistry and biology are unified through alignment factors, so that the efficiency of model deduction does not need to be affected by different data types during data processing.

[0008] Furthermore, the physical index parameters, chemical index parameters and biological index parameters are calculated as follows:

[0009] In the formula, , and They represent physical index parameters, chemical index parameters and biological index parameters respectively; , and They are physical characteristic index value, chemical characteristic index value and biological characteristic index value respectively; is the preset alignment factor.

[0010] Furthermore, the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points are aligned in the time domain, and the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points with the same time domain are integrated into the water quality parameters of the target water area, including: Adding preset time scales to the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points, aligning the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points with the same preset time scales into indicator parameters of the same time domain, and obtaining time domain physical indicator parameters, time domain chemical indicator parameters and time domain biological indicator parameters; The time-domain physical index parameters, time-domain chemical index parameters and time-domain biological index parameters are weightedly calculated to obtain the water quality parameters of the target water area.

[0011] The embodiment of the present invention proposes a method for determining the water quality risk value of industrial wastewater, which adds time scales to physical indicator parameters, chemical indicator parameters and biological indicator parameters, and can align the parameters in time to ensure that the data of each deduction is at the same time node, thereby reducing the problem of reduced accuracy of model deduction due to redundant data.

[0012] Furthermore, the historical physical indicator parameters of the historical water quality monitoring data are used as auxiliary points, and several physical-chemical indicator change curves are obtained by fitting the historical chemical indicator parameters of the historical monitoring data corresponding to each auxiliary point, and the historical biological indicator parameters of the historical monitoring data corresponding to each auxiliary point are used as smoothing factors, and several comprehensive indicator change curves are obtained by moving average of the several physical-chemical indicator change curves. The preset deduction model parameter library is updated based on the several comprehensive indicator change curves to obtain the water quality monitoring deduction model, including: The historical physical index parameter of each historical monitoring data is set as the auxiliary point corresponding to the historical monitoring data, and the historical chemical index parameter and the historical biological index parameter of the historical monitoring data corresponding to the auxiliary point are read by sliding to the auxiliary point with a preset sliding distance; The historical chemical index parameters of the historical monitoring data corresponding to the several auxiliary points are divided into several data sets with equal data intervals, and the historical chemical index parameters of the corresponding historical monitoring data and the auxiliary points of each data set are fitted into several physical-chemical index change curves; Using the historical biological indicator parameters of the historical monitoring data corresponding to the auxiliary point as smoothing factors, traversing the plurality of physical-chemical indicator change curves through a preset smoothing window for moving average, and obtaining a plurality of comprehensive indicator change curves; Based on the several comprehensive indicator change curves, several comprehensive indicator analysis results are obtained, and the parameter library of the preset deduction model is updated until the several comprehensive indicator analysis results are all updated to obtain a water quality monitoring deduction model.

[0013] The embodiment of the present invention proposes a method for determining the water quality risk value of industrial wastewater. The historical monitoring data corresponding to the auxiliary point is read by sliding distance, which ensures the continuity and integrity of the data and avoids the deviation of the monitoring results caused by missing or incorrect data. The historical physical indicator parameters are then used as auxiliary points, and combined with their corresponding chemical and biological indicator parameters to achieve comprehensive integration of water quality data into a comprehensive indicator change curve, which helps to train the water quality monitoring deduction model to capture the subtle trends of water quality changes and improve the accuracy of water quality monitoring of industrial wastewater.

[0014] Further, based on the multiple comprehensive indicator change curves, multiple comprehensive indicator analysis results are obtained, and the parameter library of the preset deduction model is updated until the multiple comprehensive indicator analysis results are updated, thereby obtaining a water quality monitoring deduction model, including: Extracting data features of the plurality of comprehensive indicator change curves as a plurality of comprehensive indicator analysis results, inputting the plurality of comprehensive indicator analysis results into a preset deduction model in sequence, and querying whether a parameter library of the preset deduction model contains corresponding comprehensive indicator analysis results; If the comprehensive index analysis result does not exist, inserting the comprehensive index analysis result into the parameter library of the preset deduction model to update the database; When the analysis results of several comprehensive indicators have been queried and updated, the preset deduction model after the parameter library is updated is used as the water quality monitoring deduction model.

[0015] An embodiment of the present invention proposes a method for determining the water quality risk value of industrial wastewater. The parameter library of a preset deduction model is updated through the analysis results of several comprehensive indicators, and the non-existent results are inserted into the database to enrich the database data volume, so that the water quality monitoring deduction model can learn more complex water quality change relationships during the training process, thereby further improving the performance of the model.

[0016] Furthermore, the water quality parameters of the target water area are input into the water quality monitoring deduction model, and the auxiliary point that meets the preset deviation requirements is used as the deduction starting point for deduction and the deduction value of each indicator parameter is recorded. Through different preset red line thresholds and time intervals of the preset prediction time interval, the number of time intervals in which the deduction value of each indicator exceeds the standard is obtained, and the initial water quality risk value is calculated, including: Based on the water quality monitoring deduction model, matching a number of auxiliary points in the water quality monitoring deduction model parameter library whose physical index parameters of the target water area water quality parameters meet a preset first deviation value; Compare the historical chemical index parameters corresponding to each auxiliary point with the chemical index parameters of the target water area water quality parameters one by one to see whether they meet the preset second deviation value, and compare the historical biological index parameters corresponding to each auxiliary point with the biological index parameters of the target water area water quality parameters one by one to see whether they meet the preset third deviation value; Taking the auxiliary point that meets the preset second deviation value and the preset third deviation value as the deduction starting point, recording the change values ​​of each indicator parameter of the deduction starting point on the plurality of comprehensive indicator change curves, and obtaining the deduced value of the physical indicator, the deduced value of the chemical indicator, and the deduced value of the biological indicator; Based on the time interval of the preset prediction time interval, determine whether the physical indicator deduced value, chemical indicator deduced value and biological indicator deduced value exceed the corresponding different preset red line thresholds, obtain the number of time intervals when the physical indicator deduced value exceeds the standard, the number of time intervals when the chemical indicator deduced value exceeds the standard and the number of time intervals when the biological indicator deduced value exceeds the standard, and calculate the initial water quality risk value.

[0017] Furthermore, the calculation formula of the initial water quality risk value is:

[0018] Where P is the initial water quality risk value, , and They are the number of time intervals when the deduced values ​​of physical indicators exceed the standard, the number of time intervals when the deduced values ​​of chemical indicators exceed the standard, and the number of time intervals when the deduced values ​​of biological indicators exceed the standard. The total number of time intervals for the forecast time interval.

[0019] Furthermore, the water quality monitoring data of different monitoring points are updated in real time to obtain corresponding actual indicator parameters, the difference between each actual indicator parameter and the deduced value of each indicator parameter is calculated, and the parameter library of the water quality monitoring deduction model is updated according to the difference calculation result, and the deduction is re-performed through the updated water quality monitoring deduction model to obtain the optimized water quality risk value, including: Obtain the actual physical index parameters, actual chemical index parameters and actual biological index parameters of water quality monitoring data of different monitoring points updated in real time; Respectively subtracting the actual physical indicator parameter from the physical indicator deduced value, the actual chemical indicator parameter from the chemical indicator deduced value, and the actual biological indicator parameter from the biological indicator deduced value to obtain a physical indicator deduced difference value, a chemical indicator deduced difference value, and a biological indicator deduced difference value; Iterate the deduced values ​​of various indicators that do not meet the preset deduced error range among the deduced difference values ​​of physical indicators, the deduced difference values ​​of chemical indicators and the deduced difference values ​​of biological indicators into corresponding actual indicator parameters, and update the actual indicator parameters to the water quality monitoring deduction model parameter library; Based on the water quality monitoring deduction model after the parameter library is updated, the number of time intervals when the deduced values ​​of physical indicators exceed the standard, the number of time intervals when the deduced values ​​of chemical indicators exceed the standard, and the number of time intervals when the deduced values ​​of biological indicators exceed the standard are re-obtained and the optimized water quality risk value is calculated.

[0020] The embodiment of the present invention proposes a method for determining the water quality risk value of industrial wastewater. By obtaining actual indicator parameters by updating water quality monitoring data in real time, it can ensure that the model can capture the latest dynamics of water quality changes. By comparing the difference between the actual indicator parameters and the indicator deduced values, the prediction error of the model under the current water quality conditions is reflected. Based on the prediction error, dynamic adjustment and optimization of the water quality monitoring deduction model is achieved, thereby improving the accuracy of sewage monitoring.

[0021] The embodiment of the present invention also provides a water quality risk value determination system for industrial wastewater, including: an indicator acquisition module, a deduction model construction module, a water quality risk value calculation module and a water quality risk value optimization module; The indicator acquisition module is used to obtain water quality monitoring data from different monitoring points, select representative characteristic indicators of the water quality monitoring data from different monitoring points by comparing the neighborhood radius of characteristic indicators, obtain physical indicator parameters, chemical indicator parameters and biological indicator parameters, and construct water quality parameters of the target water area; The deduction model construction module is used to use the historical physical indicator parameters of the historical water quality monitoring data as auxiliary points, obtain a number of physical-chemical indicator change curves by fitting the historical chemical indicator parameters of the historical monitoring data corresponding to each auxiliary point, and use the historical biological indicator parameters of the historical monitoring data corresponding to each auxiliary point as a smoothing factor, obtain a number of comprehensive indicator change curves by moving average of the several physical-chemical indicator change curves, and update the preset deduction model parameter library based on the several comprehensive indicator change curves to obtain a water quality monitoring deduction model; The water quality risk value calculation module is used to input the water quality parameters of the target water area into the water quality monitoring deduction model, use the auxiliary point that meets the preset deviation requirements as the deduction starting point to deduce and record the deduced values ​​of each indicator parameter, obtain the number of time intervals in which the deduced values ​​of each indicator exceed the standard through different preset red line thresholds and preset prediction time intervals, and calculate the initial water quality risk value; The water quality risk value optimization module is used to update the water quality monitoring data of different monitoring points in real time to obtain the corresponding actual indicator parameters, calculate the difference between each actual indicator parameter and the deduced value of each indicator parameter, update the parameter library of the water quality monitoring deduction model according to the difference calculation results, and re-deduce through the updated water quality monitoring deduction model to obtain the optimized water quality risk value.

[0022] The embodiment of the present invention proposes a water quality risk value determination system for industrial sewage. The indicator acquisition module performs physical, biological and chemical multi-level indicator analysis on the water quality monitoring data of different monitoring points, which can more objectively and comprehensively analyze the water quality status of the target water area. The multi-indicator analysis can further improve the accuracy of determining the water quality risk value. In addition, the deduction model construction module also splits the historical water quality monitoring data into three-level indicators: physical, chemical and biological. The physical indicator parameters are used as auxiliary points, and the chemical indicator parameters are combined to fit a number of physical-chemical indicator change curves. Then, the biological indicator parameters are combined to perform smooth optimization to obtain a number of comprehensive indicator change curves. The water quality monitoring deduction model is trained in this way. The multi-indicator joint training improves the robustness of the water quality monitoring deduction model, thereby improving the accuracy of determining the water quality risk value. The water quality risk value calculation module selects the deduction starting point to deduce and record the deduced values ​​of various indicator parameters. The fixed-point deduction to reflect the changes in indicator parameters helps to improve the accuracy of water quality monitoring. The initial water quality risk value is calculated through different preset red line thresholds and preset prediction time intervals. Time intervals, early warning of future indicator change trends, to ensure the reliability of water quality monitoring, and the water quality risk value optimization module is used to update the water quality monitoring data of different monitoring points in real time, and feedback is used to optimize the water quality monitoring deduction model to achieve continuous optimization and updating of the model to obtain more reliable water quality risk values. Therefore, by analyzing the numerical monitoring data at multiple levels and continuously optimizing and updating the water quality monitoring deduction model, more reliable and accurate water quality risk values ​​can be obtained, which improves the accuracy of water quality monitoring of industrial wastewater.

[0023] Beneficial effects: (1) The embodiment of the present invention proposes a method and system for determining the water quality risk value of industrial wastewater. By performing physical, biological and chemical multi-level indicator analysis on the water quality monitoring data of different monitoring points, the water quality status of the target water area can be analyzed more objectively and comprehensively. The multi-indicator analysis can further improve the accuracy of determining the water quality risk value. Furthermore, the historical water quality monitoring data is also divided into three levels of physical, chemical and biological indicators. The physical indicator parameters are used as auxiliary points, and the chemical indicator parameters are combined to fit a number of physical-chemical indicator change curves. Then, the biological indicator parameters are combined to perform smoothing optimization to obtain a number of comprehensive indicator change curves. The water quality monitoring deduction model is obtained by training. The multi-indicator joint training improves the robustness of the water quality monitoring deduction model, thereby improving the water quality risk value determination. In order to improve the accuracy of water quality monitoring, the deduction value of each indicator parameter is recorded by selecting the deduction starting point. The fixed-point deduction reflects the change of indicator parameters, which helps to improve the accuracy of water quality monitoring. Then, the initial water quality risk value is calculated through different preset red line thresholds and preset prediction time intervals. Early warning is given for future indicator change trends to ensure the reliability of water quality monitoring. The water quality monitoring data of different monitoring points are updated in real time, and the water quality monitoring deduction model is optimized through feedback, so as to realize continuous optimization and updating of the model and obtain more reliable water quality risk values. Therefore, by analyzing the numerical monitoring data at multiple levels and continuously optimizing and updating the water quality monitoring deduction model, more reliable and accurate water quality risk values ​​can be obtained, thereby improving the accuracy of water quality monitoring of industrial wastewater. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic flow chart of the steps of a method for determining a water quality risk value of industrial wastewater provided in one embodiment of the present invention; Figure 2 A schematic diagram of a data processing structure of a method for determining a water quality risk value of industrial wastewater provided by a certain embodiment of the present invention; Figure 3 A schematic diagram of the module structure of a system for determining water quality risk values ​​of industrial wastewater provided in one embodiment of the present invention. DETAILED DESCRIPTION

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

[0026] Example 1 See also Figure 1 , Figure 1A schematic flow chart of the steps of a method for determining the water quality risk value of industrial wastewater provided in one embodiment of the present invention. Figure 1 As shown, the embodiment of the present invention provides a method for determining the water quality risk value of industrial wastewater, including steps 101 to 104, each of which is specifically as follows: Step 101, obtaining water quality monitoring data from different monitoring points, selecting representative characteristic indicators of the water quality monitoring data from different monitoring points by comparing the neighborhood radius of characteristic indicators, obtaining physical indicator parameters, chemical indicator parameters and biological indicator parameters and constructing water quality parameters of the target water area; As an example of this embodiment, the physical characteristic neighborhood radius, chemical characteristic neighborhood radius and biological characteristic neighborhood radius of the water quality monitoring data of the different monitoring points are calculated respectively; the physical characteristic neighborhood radius, chemical characteristic neighborhood radius and biological characteristic neighborhood radius of the water quality monitoring data of the different monitoring points are compared one by one, and the physical characteristic, chemical characteristic and biological characteristic with the largest corresponding neighborhood radius are used as representative characteristic indicators to obtain the physical characteristic indicator value, chemical characteristic indicator value and biological characteristic indicator value corresponding to the water quality monitoring data of the different monitoring points; the physical characteristic indicator value, chemical characteristic indicator value and biological characteristic indicator value corresponding to the water quality monitoring data of the different monitoring points are respectively divided by the preset alignment factor and the absolute value is calculated respectively to obtain the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points; the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points are aligned in time domain, and the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points with the same time domain are integrated into the water quality parameters of the target water area. Specifically, a preset time scale is added to the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points, and the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points with the same preset time scale are aligned as indicator parameters of the same time domain to obtain time domain physical indicator parameters, time domain chemical indicator parameters and time domain biological indicator parameters; weighted calculation is performed on the time domain physical indicator parameters, time domain chemical indicator parameters and time domain biological indicator parameters to obtain water quality parameters of the target water area.

[0027] The existing technology usually only analyzes a single indicator of sewage, but sewage usually has a complex composition. If only a single indicator is analyzed, risks are easily missed during sewage risk monitoring. In order to solve this problem, an embodiment of the present invention proposes a method for determining the water quality risk value of industrial sewage. By performing a local range analysis of the water quality monitoring data of each monitoring station in three dimensions of physical, chemical and biological, and then selecting representative characteristic indicators in each dimension, it not only reduces data redundancy but also provides a reliable data basis for subsequent model deduction. When constructing the water quality parameters of the target water area, by adding a time stamp, the parameters are time-aligned to ensure that the data of each deduction is at the same time node, reducing the problem of reduced accuracy of model deduction due to data redundancy. A specific implementation method , to obtain water quality monitoring data from different monitoring points, the neighborhood radius iterative classification method and principal component analysis method can be used to analyze the physical characteristics, chemical characteristics and biological characteristics of each data respectively, and obtain the physical indicator parameters, chemical indicator parameters and biological indicator parameters of each water quality monitoring data, among which the physical characteristics include: chromaticity, transparency, conductivity and redox potential, etc.; chemical characteristics include: pH value, dissolved oxygen (DO), ammonia nitrogen (NH3-N), total phosphorus (TP) and heavy metals, etc.; biological characteristics include: total bacteria count, coliform count, plankton species and plankton count, etc.; taking the neighborhood radius iterative classification method to analyze the physical characteristics of water quality monitoring data as an example, specifically, obtain the j physical characteristics of the i-th water quality monitoring data, and calculate the average value of the j-th physical characteristics of all monitoring points , the calculation formula is as follows:

[0028] In the formula, is the average value of the jth physical characteristic of all monitoring points, n is the total number of monitoring points, is the jth physical feature of the i-th water quality monitoring data; where i=1, 2, ..., n; j=1, 2, ..., m; m is the total number of physical features of water quality monitoring data; The average value calculated based on Calculate the neighborhood radius of the jth physical feature of the i-th monitoring point , the calculation formula is as follows:

[0029] In the formula, is the neighborhood radius of the jth physical feature of the ith monitoring point; Select the physical feature with the largest domain radius as the representative feature, and use the corresponding monitoring value of the physical feature as the physical feature index value , which means that in one monitoring of the target water area, the physical feature has the most direct and obvious impact on water quality monitoring. If multiple physical features have the same neighborhood radius, then all physical feature combinations with the same neighborhood radius are taken as representative features, and the combination of the corresponding monitoring values ​​of these physical features is taken as the physical feature index value, which means that in one monitoring of the target water area, these physical features have the most direct, obvious and equally important impact on water quality monitoring. Therefore, analyzing the physical features can help analyze the water quality of the target water area more objectively and comprehensively. Similarly, analyzing the chemical features and biometrics Perform the same process to obtain the chemical characteristic index value and biometric indicator values ; It is worth mentioning that the physical characteristic index value , Chemical characteristic index value and biometric indicator values It can be a single data or a data set; Getting the physical characteristic index value , Chemical characteristic index value and biometric indicator values Then, by setting the alignment factor, the physical characteristic index value , Chemical characteristic index value and biometric indicator values To perform alignment, a specific implementation method may be to divide each characteristic index value by a preset alignment factor (which may be set as a constant) and calculate the absolute value. The specific calculation formula is as follows:

[0030] In the formula, , and They represent physical index parameters, chemical index parameters and biological index parameters respectively; , and They are physical characteristic index value, chemical characteristic index value and biological characteristic index value respectively; is the preset alignment factor. Thus, we convert the physical characteristic index value, chemical characteristic index value and biological characteristic index value into physical indicator parameters, chemical indicator parameters and biological indicator parameters; Since a multi-index analysis method is adopted, in order to prevent subsequent data analysis from being affected by the amount of data, a time stamp is set for each physical indicator parameter, chemical indicator parameter and biological indicator parameter, and each physical indicator parameter, chemical indicator parameter and biological indicator parameter are processed in their respective corresponding time domains. Each time the data is used, only the data in the same domain is acquired and then the subsequent deduction and analysis are performed, ensuring that the data for each deduction is at the same time node, thereby reducing the problem of reduced accuracy of model deduction due to data redundancy. The specific implementation method is as follows: adding a preset time stamp to each physical indicator parameter, chemical indicator parameter and biological indicator parameter. The time stamp has a variety of setting methods. For example, the corresponding timestamp can be inserted into each physical indicator parameter, chemical indicator parameter and biological indicator parameter as a time stamp, and a time stamp can also be added when the water quality monitoring data is collected. Add a timestamp so that the physical characteristics, chemical characteristics, biological characteristics, physical characteristic index values, chemical characteristic index values ​​and biological characteristic index values ​​used for subsequent processing all have the timestamp, so that the timestamp of the corresponding time already exists when the subsequent calculation obtains each physical indicator parameter, chemical indicator parameter and biological indicator parameter. Many existing mature methods can also be used, which will not be elaborated here; after adding a preset time stamp to each physical indicator parameter, chemical indicator parameter and biological indicator parameter, align several data to their corresponding time domain through the timestamp carried by each data, and obtain the time domain physical indicator parameters, time domain chemical indicator parameters and time domain biological indicator parameters. Finally, set the corresponding weights according to the actual application for weighted calculation, and integrate each time domain physical indicator parameter, time domain chemical indicator parameter and time domain biological indicator parameter into the water quality parameters of the target water area.

[0031] Step 102, using historical physical indicator parameters of historical water quality monitoring data as auxiliary points, obtaining a plurality of physical-chemical indicator change curves by fitting the historical chemical indicator parameters of the historical monitoring data corresponding to each auxiliary point, and using the historical biological indicator parameters of the historical monitoring data corresponding to each auxiliary point as smoothing factors, obtaining a plurality of comprehensive indicator change curves by moving average of the plurality of physical-chemical indicator change curves, and updating a preset deduction model parameter library based on the plurality of comprehensive indicator change curves to obtain a water quality monitoring deduction model; As an example of this embodiment, the historical physical indicator parameter of each historical monitoring data is set as an auxiliary point corresponding to the historical monitoring data, and the preset sliding distance is slid to the auxiliary point to read the historical chemical indicator parameter and the historical biological indicator parameter of the historical monitoring data corresponding to the auxiliary point; the historical chemical indicator parameters of the historical monitoring data corresponding to several auxiliary points are divided into several data sets with equal data intervals, and the auxiliary points of each data set and the historical chemical indicator parameters of the corresponding historical monitoring data are fitted into several physical-chemical indicator change curves; the historical biological indicator parameters of the historical monitoring data corresponding to the auxiliary point are used as smoothing factors, and the several physical-chemical indicator change curves are traversed through a preset smoothing window for moving average to obtain several comprehensive indicator change curves; based on the several comprehensive indicator change curves, several comprehensive indicator analysis results are obtained, and the parameter library of the preset deduction model is updated until the several comprehensive indicator analysis results are all updated, so as to obtain a water quality monitoring deduction model. Specifically, the data features of the several comprehensive indicator change curves are extracted as several comprehensive indicator analysis results, the several comprehensive indicator analysis results are input into the preset deduction model in sequence and the parameter library of the preset deduction model is queried whether there is a corresponding comprehensive indicator analysis result; if the comprehensive indicator analysis result does not exist, the comprehensive indicator analysis result is inserted into the parameter library of the preset deduction model to update the database; when the query and update of several comprehensive indicator analysis results are completed, the preset deduction model after the parameter library is updated is used as the water quality monitoring deduction model.

[0032] Before training the deduction model, in order to make the obtained training data set coherent, the sliding distance method is used to slide and read the data between the auxiliary points, and then the curve fitting method is used through the auxiliary points and their corresponding indicator parameters to achieve a comprehensive integrated analysis of the water quality data. The change of the curve can also capture the subtle trend of water quality changes and improve the accuracy of water quality monitoring. The specific implementation method is as follows, see Figure 2 , Figure 2 A schematic diagram of a data processing structure of a method for determining a water quality risk value of industrial wastewater provided by a certain embodiment of the present invention; Figure 2 As shown, in one example, Figure 2Where Tphd is the historical physical indicator parameter of the historical monitoring data; Tchd is the historical chemical indicator parameter of the historical monitoring data; Tbhd is the historical biological indicator parameter of the historical monitoring data; wherein d=1, 2, 3, ..., d, t is the preset sliding distance, t' is the preset data interval, and w is the preset smoothing window; each historical water quality monitoring data J is composed of historical physical indicator parameters, historical chemical indicator parameters and historical biological indicator parameters, and its representation is J={Tphd, Tchd, Tbhd}; it is worth mentioning that d represents points in different time domains, that is, the historical water quality monitoring data J is composed of water quality monitoring data at different time nodes, and in order to make the subsequent data fitting more accurate, the preset data interval t' can be set to a larger interval, which is conducive to the subsequent fitting curve analysis. However, in this embodiment, for the convenience of explanation, the preset data interval t' is set to 3 data points; the specific data processing steps are as follows: First, the historical physical indicator parameters of each historical monitoring data are set to the auxiliary points corresponding to the historical monitoring data , auxiliary point The historical physical index parameter Tphd is stored in the disk. The corresponding auxiliary point is read by preset sliding distance t. The corresponding historical chemical indicator parameters Tchd and historical biological indicator parameters Tbhd are then divided into several data sets {Tch1, Tch2, Tch3}, {Tch4, Tch5, Tch6}, ..., {Tch (d-2), Tch (d-1), Tchd} by the preset data interval t'; according to each data set, the historical physical indicator parameters Tphd stored by the auxiliary point are fitted with the historical chemical indicator parameters Tchd in the data set to obtain several physical-chemical indicator change curves; then the historical biological indicator parameter Tbhd is traversed over the entire physical-chemical indicator change curve with a preset smoothing window w. Generally, the preset smoothing window w can be set to have the same length as the preset data interval t'. At each window position, the moving average of the data points in the window is calculated, and the comprehensive indicator change curve is constructed by the moving average. A specific explanation is that in the setting of the above example scheme, the first slide to the auxiliary point When auxiliary point The data point stored in is Tph1. The historical chemical index parameter Tchd is divided into data sets {Tch1, Tch2, Tch3} by the preset data interval t'. Tph1 is fitted with Tch1, Tch2 and Tch3 respectively to obtain the first physical-chemical index fitting value, and then slide to the next auxiliary point , due to the auxiliary point The corresponding historical chemical indicator parameter is Tch2, which is still in the data set {Tch1, Tch2, Tch3}. Therefore, the data set does not change. Tph2 is fitted with Tch1, Tch2 and Tch3 respectively to obtain the second physical-chemical indicator fitting value, until the auxiliary points corresponding to the historical chemical indicator parameters in the data set are fitted, all the physical-chemical indicator fitting values ​​are obtained and the physical-chemical indicator change curve is constructed. The historical biological indicator parameters {Tbh1, Tbh2, Tbh3} in the sliding window are used to calculate the moving average value of all the physical-chemical indicator fitting values ​​of the physical-chemical indicator change curve one by one to smooth the curve, and a comprehensive indicator change curve is constructed based on all the calculated moving average values; the method of constructing the data points into a curve in the above scheme can adopt the existing conventional manual segment; after processing the data, a comprehensive indicator change curve is obtained, and a suitable preset deduction model is selected. Generally, the deduction model can adopt a time series model, a machine learning model (such as a neural network or a random forest, etc.), etc., and the characteristics of each data point of the comprehensive indicator change curve are extracted as the comprehensive indicator analysis result, which is input into the preset deduction model for training, and the parameter library of the preset deduction model is iteratively updated to determine whether the above comprehensive indicator analysis result already exists in the parameter library of the preset deduction model. If the comprehensive indicator analysis result does not exist, the comprehensive indicator analysis result is inserted into the parameter library of the preset deduction model to update the database. If it already exists, the update of the comprehensive indicator analysis result is ignored. When several comprehensive indicator analysis results have completed the query update, it means that the preset deduction model has completed the database update, and a water quality monitoring deduction model is obtained.

[0033] Step 103, input the water quality parameters of the target water area into the water quality monitoring deduction model, use the auxiliary point that meets the preset deviation requirements as the deduction starting point to perform deduction and record the deduced values ​​of each indicator parameter, obtain the number of time intervals in which the deduced values ​​of each indicator exceed the standard through different preset red line thresholds and preset prediction time intervals, and calculate the initial water quality risk value; As an example of this embodiment, based on the water quality monitoring deduction model, several auxiliary points in the parameter library of the water quality monitoring deduction model that meet the preset first deviation value with the physical indicator parameters of the water quality parameters of the target water area are matched; the historical chemical indicator parameters corresponding to each auxiliary point are compared one by one with the chemical indicator parameters of the water quality parameters of the target water area to see whether they meet the preset second deviation value, and the historical biological indicator parameters corresponding to each auxiliary point are compared one by one with the biological indicator parameters of the water quality parameters of the target water area to see whether they meet the preset third deviation value; the auxiliary point that meets the preset second deviation value and the preset third deviation value is used as the deduction starting point, and the change values ​​of each indicator parameter at the deduction starting point on the several comprehensive indicator change curves are recorded to obtain the physical indicator deduction value, the chemical indicator deduction value and the biological indicator deduction value; based on the time interval of the preset prediction time interval, it is judged whether the physical indicator deduction value, the chemical indicator deduction value and the biological indicator deduction value exceed the corresponding different preset red line thresholds, the number of time intervals in which the physical indicator deduction value exceeds the standard, the number of time intervals in which the chemical indicator deduction value exceeds the standard and the number of time intervals in which the biological indicator deduction value exceeds the standard are obtained, and the initial water quality risk value is calculated.

[0034] When analyzing the water quality parameters of the target water area, the water quality monitoring deduction model obtained by training through the above steps is deduced, and then the changing trend of the water quality of the target water area in the future period of time is deduced, and the risk of water quality change can be predicted to improve the accuracy of sewage monitoring. A specific implementation method is to obtain the physical indicator parameters, chemical indicator parameters and biological indicator parameters of the water quality parameters of the target water area, and input the water quality parameters of the target water area into the water quality monitoring deduction model. First, the auxiliary points similar to the physical indicator parameters of the water quality parameters of the target water area are matched in the water quality monitoring deduction model parameter library. The auxiliary points that meet the deviation requirements (equivalent to the preset first deviation value) can be screened out by calculating the deviation values ​​of the physical indicator parameters of the water quality parameters of the target water area and the historical physical indicator parameters corresponding to each auxiliary point, and then the deviation values ​​of the chemical indicator parameters of the water quality parameters of the target water area and the historical chemical indicator parameters of each selected auxiliary point are calculated one by one, and the biological indicator parameters of the water quality parameters of the target water area and the historical biological indicator parameters of each selected auxiliary point are calculated one by one. Deviation value, filter out auxiliary points that meet the corresponding deviation requirements (equivalent to the preset second deviation value and third deviation value), the screened auxiliary points can be multiple, it is worth mentioning that the deviation value can be adjusted according to the actual situation; take each screened auxiliary point as the deduction starting point, and use the change characteristics of the auxiliary point on the comprehensive indicator change curve as the change trend of each indicator, and output it as the physical indicator deduction value, chemical indicator deduction value and biological indicator deduction value. If there are multiple starting points, the corresponding indicator change trends can be obtained respectively, and then the multiple deduction values ​​can be integrated into one deduction value according to the weight calculation, and the multiple change trends can be integrated into a more reliable change trend; after obtaining the physical indicator deduction value, chemical indicator deduction value and biological indicator deduction value, set the time interval to be predicted, and set the red line threshold for the physical indicator, chemical indicator and biological indicator, obtain the number of time intervals exceeding the red line threshold in the physical indicator deduction value, chemical indicator deduction value and biological indicator deduction value, and calculate the initial water quality risk value. The calculation formula is as follows:

[0035] Where P is the initial water quality risk value, , and They are the number of time intervals when the deduced values ​​of physical indicators exceed the standard, the number of time intervals when the deduced values ​​of chemical indicators exceed the standard, and the number of time intervals when the deduced values ​​of biological indicators exceed the standard. The total number of time intervals for the forecast time interval.

[0036] Step 104, update the water quality monitoring data of different monitoring points in real time to obtain the corresponding actual indicator parameters, calculate the difference between each actual indicator parameter and the deduced value of each indicator parameter, update the parameter library of the water quality monitoring deduction model according to the difference calculation result, and re-deduct through the updated water quality monitoring deduction model to obtain the optimized water quality risk value.

[0037] As an example of this embodiment, actual physical indicator parameters, actual chemical indicator parameters and actual biological indicator parameters of water quality monitoring data of different monitoring points are obtained, which are updated in real time; the actual physical indicator parameters are subtracted from the physical indicator deduced values, the actual chemical indicator parameters are subtracted from the chemical indicator deduced values, and the actual biological indicator parameters are subtracted from the biological indicator deduced values ​​to obtain physical indicator deduced difference values, chemical indicator deduced difference values ​​and biological indicator deduced difference values; the deduced values ​​of each indicator that do not meet the preset deduction error range among the physical indicator deduced difference values, chemical indicator deduced difference values ​​and biological indicator deduced difference values ​​are iterated into corresponding actual indicator parameters, and the actual indicator parameters are updated to the water quality monitoring deduction model parameter library; based on the water quality monitoring deduction model updated by the parameter library, the number of time intervals in which the physical indicator deduced values ​​exceed the standard, the number of time intervals in which the chemical indicator deduced values ​​exceed the standard and the number of time intervals in which the biological indicator deduced values ​​exceed the standard are re-obtained and the optimized water quality risk value is calculated.

[0038] In order to make the deduction results of the water quality monitoring deduction model more accurate, the water quality monitoring data of different monitoring points are updated in real time, and deduction is performed based on the updated data, and then the deviation of the predicted value is calculated, the accuracy of the predicted value is evaluated, and the unreliable data is iteratively updated to retain the reliable data. Therefore, continuous feedback and updating of the parameter library of the water quality monitoring deduction model can make the performance of the water quality monitoring deduction model at a higher level and improve the accuracy of sewage monitoring. A specific implementation method is to update the water quality monitoring data of different monitoring points in real time, obtain the latest actual physical indicator parameters, actual chemical indicator parameters and actual biological indicator parameters of the water quality monitoring data, and the latest water quality monitoring data will be input into the water quality monitoring deduction model. The deduction is performed in the same way as the above deduction steps to obtain the actual physical indicator deduction values, actual chemical indicator deduction values ​​and actual biological indicator deduction values, and the actual physical indicator deduction values, actual chemical indicator deduction values ​​and actual biological indicator deduction values ​​are subtracted from the predicted physical indicator deduction values, chemical indicator deduction values ​​and biological indicator deduction values, and the difference values ​​corresponding to each indicator are evaluated. If the difference value is greater than the preset error range, the indicator parameters that do not meet the requirements are iteratively updated to the corresponding actual indicator parameters, and the indicator parameters that do not meet the requirements are deleted, so as to realize the iterative update of the water quality monitoring deduction model, and the water quality parameters of the target water area are re-deduced through the updated water quality monitoring deduction model, and the water quality risk value is recalculated.

[0039] The embodiment of the present invention proposes a method for determining the water quality risk value of industrial wastewater. By performing physical, biological and chemical multi-level indicator analysis on water quality monitoring data from different monitoring points, the water quality status of the target water area can be analyzed more objectively and comprehensively. The accuracy of determining the water quality risk value can be further improved through multi-indicator analysis. Furthermore, the historical water quality monitoring data is also divided into three levels of physical, chemical and biological indicators. The physical indicator parameters are used as auxiliary points, and several physical-chemical indicator change curves are fitted in combination with the chemical indicator parameters. Then, the biological indicator parameters are combined for smoothing optimization to obtain several comprehensive indicator change curves. The water quality monitoring deduction model is obtained by training. The multi-indicator joint training improves the robustness of the water quality monitoring deduction model, thereby improving the accuracy of determining the water quality risk value. Degree, by selecting the deduction starting point for deduction and recording the deduced values ​​of various indicator parameters, using fixed-point deduction to reflect the changes in indicator parameters is helpful to improve the accuracy of water quality monitoring, and then the initial water quality risk value is calculated through different preset red line thresholds and preset prediction time intervals. Time intervals, early warning of future indicator change trends, to ensure the reliability of water quality monitoring, and also through real-time updating of water quality monitoring data at different monitoring points, and feedback to optimize the water quality monitoring deduction model, to achieve continuous optimization and updating of the model, so as to obtain more reliable water quality risk values. Therefore, through multi-level analysis of numerical monitoring data, the water quality monitoring deduction model is continuously optimized and updated, so as to obtain more reliable and accurate water quality risk values, thereby improving the accuracy of water quality monitoring of industrial wastewater.

[0040] Example 2 See also Figure 3 , Figure 3 A schematic diagram of the module structure of a system for determining the water quality risk value of industrial wastewater provided by a certain embodiment of the present invention. Figure 3 As shown, the embodiment of the present invention proposes a water quality risk value determination system for industrial wastewater, including: an indicator acquisition module 201, a deduction model construction module 202, a water quality risk value calculation module 203 and a water quality risk value optimization module 204; The indicator acquisition module 201 is used to obtain water quality monitoring data from different monitoring points, select representative characteristic indicators of the water quality monitoring data from different monitoring points by comparing the neighborhood radius of characteristic indicators, obtain physical indicator parameters, chemical indicator parameters and biological indicator parameters, and construct water quality parameters of the target water area; The deduction model construction module 202 is used to use the historical physical indicator parameters of the historical water quality monitoring data as auxiliary points, obtain a number of physical-chemical indicator change curves by fitting the historical chemical indicator parameters of the historical monitoring data corresponding to each auxiliary point, and use the historical biological indicator parameters of the historical monitoring data corresponding to each auxiliary point as smoothing factors, obtain a number of comprehensive indicator change curves by moving average of the several physical-chemical indicator change curves, and update the preset deduction model parameter library based on the several comprehensive indicator change curves to obtain a water quality monitoring deduction model; The water quality risk value calculation module 203 is used to input the water quality parameters of the target water area into the water quality monitoring deduction model, use the auxiliary point that meets the preset deviation requirements as the deduction starting point to deduce and record the deduced values ​​of each indicator parameter, obtain the number of time intervals in which the deduced values ​​of each indicator exceed the standard through different preset red line thresholds and preset prediction time intervals, and calculate the initial water quality risk value; The water quality risk value optimization module 204 is used to update the water quality monitoring data of different monitoring points in real time to obtain the corresponding actual indicator parameters, calculate the difference between each actual indicator parameter and the deduced value of each indicator parameter, update the parameter library of the water quality monitoring deduction model according to the difference calculation result, and re-deduce through the updated water quality monitoring deduction model to obtain the optimized water quality risk value.

[0041] The embodiment of the present invention proposes a water quality risk value determination system for industrial sewage. The indicator acquisition module performs physical, biological and chemical multi-level indicator analysis on the water quality monitoring data of different monitoring points, which can more objectively and comprehensively analyze the water quality status of the target water area. The multi-indicator analysis can further improve the accuracy of determining the water quality risk value. In addition, the deduction model construction module also splits the historical water quality monitoring data into three-level indicators: physical, chemical and biological. The physical indicator parameters are used as auxiliary points, and the chemical indicator parameters are combined to fit a number of physical-chemical indicator change curves. Then, the biological indicator parameters are combined to perform smooth optimization to obtain a number of comprehensive indicator change curves. The water quality monitoring deduction model is trained in this way. The multi-indicator joint training improves the robustness of the water quality monitoring deduction model, thereby improving the accuracy of determining the water quality risk value. The water quality risk value calculation module selects the deduction starting point to deduce and record the deduced values ​​of various indicator parameters. The fixed-point deduction to reflect the changes in indicator parameters helps to improve the accuracy of water quality monitoring. The initial water quality risk value is calculated through different preset red line thresholds and preset prediction time intervals. Time intervals, early warning of future indicator change trends, to ensure the reliability of water quality monitoring, and the water quality risk value optimization module is used to update the water quality monitoring data of different monitoring points in real time, and feedback is used to optimize the water quality monitoring deduction model to achieve continuous optimization and updating of the model to obtain more reliable water quality risk values. Therefore, by analyzing the numerical monitoring data at multiple levels and continuously optimizing and updating the water quality monitoring deduction model, more reliable and accurate water quality risk values ​​can be obtained, which improves the accuracy of water quality monitoring of industrial wastewater.

[0042] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

[0043] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the described specific features, structures, materials or characteristics may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0044] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

Claims

1. A method for determining the water quality risk value of industrial wastewater, characterized in that: include: Acquire water quality monitoring data from different monitoring points, select representative characteristic indicators of the water quality monitoring data from different monitoring points by comparing the neighborhood radius of characteristic indicators, obtain physical indicator parameters, chemical indicator parameters and biological indicator parameters, and construct water quality parameters of the target water area; Taking historical physical indicator parameters of historical water quality monitoring data as auxiliary points, a number of physical-chemical indicator change curves are obtained by fitting the historical chemical indicator parameters of historical monitoring data corresponding to each auxiliary point, and taking the historical biological indicator parameters of historical monitoring data corresponding to each auxiliary point as smoothing factors, a number of comprehensive indicator change curves are obtained by moving average of the several physical-chemical indicator change curves, and a preset deduction model parameter library is updated based on the several comprehensive indicator change curves to obtain a water quality monitoring deduction model; The water quality parameters of the target water area are input into the water quality monitoring deduction model, and the auxiliary point that meets the preset deviation requirements is used as the deduction starting point for deduction and the deduction value of each indicator parameter is recorded. Through different preset red line thresholds and time intervals of the preset prediction time interval, the number of time intervals in which the deduced value of each indicator exceeds the standard is obtained, and the initial water quality risk value is calculated; Update the water quality monitoring data of different monitoring points in real time to obtain the corresponding actual indicator parameters, calculate the difference between the actual indicator parameters and the deduced values ​​of each indicator parameter, update the parameter library of the water quality monitoring deduction model according to the difference calculation results, and re-deduct through the updated water quality monitoring deduction model to obtain the optimized water quality risk value.

2. The method for determining the water quality risk value of industrial wastewater according to claim 1, characterized in that: The method of obtaining water quality monitoring data from different monitoring points, selecting representative characteristic indicators of the water quality monitoring data from different monitoring points by comparing the neighborhood radius of characteristic indicators, obtaining physical indicator parameters, chemical indicator parameters and biological indicator parameters and constructing water quality parameters of the target water area includes: Respectively calculating the physical characteristic neighborhood radius, chemical characteristic neighborhood radius and biological characteristic neighborhood radius of the water quality monitoring data of the different monitoring points; Compare the physical characteristic neighborhood radius, chemical characteristic neighborhood radius and biological characteristic neighborhood radius of the water quality monitoring data of the different monitoring points one by one, take the physical characteristic, chemical characteristic and biological characteristic with the largest corresponding neighborhood radius as the representative characteristic index, and obtain the physical characteristic index value, chemical characteristic index value and biological characteristic index value corresponding to the water quality monitoring data of the different monitoring points; The physical characteristic index values, chemical characteristic index values ​​and biological characteristic index values ​​corresponding to the water quality monitoring data at different monitoring points are respectively divided by the preset alignment factors and the absolute values ​​are respectively calculated to obtain the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data at different monitoring points; The physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points are aligned in time domain, and the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points with the same time domain are integrated into the water quality parameters of the target water area.

3. The method for determining the water quality risk value of industrial wastewater according to claim 2, characterized in that: The calculation formulas of the physical index parameters, chemical index parameters and biological index parameters are as follows: ； In the formula, , and They represent physical index parameters, chemical index parameters and biological index parameters respectively; , and They are physical characteristic index value, chemical characteristic index value and biological characteristic index value respectively; is the preset alignment factor.

4. The method for determining the water quality risk value of industrial wastewater according to claim 3, characterized in that: The physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points are aligned in the time domain, and the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points with the same time domain are integrated into the water quality parameters of the target water area, including: Adding preset time scales to the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points, aligning the physical indicator parameters, chemical indicator parameters and biological indicator parameters corresponding to the water quality monitoring data of the different monitoring points with the same preset time scales into indicator parameters of the same time domain, and obtaining time domain physical indicator parameters, time domain chemical indicator parameters and time domain biological indicator parameters; The time-domain physical index parameters, time-domain chemical index parameters and time-domain biological index parameters are weightedly calculated to obtain the water quality parameters of the target water area.

5. The method for determining the water quality risk value of industrial wastewater according to claim 1, characterized in that: The method uses the historical physical indicator parameters of the historical water quality monitoring data as auxiliary points, obtains a plurality of physical-chemical indicator change curves by fitting the historical chemical indicator parameters of the historical monitoring data corresponding to each auxiliary point, uses the historical biological indicator parameters of the historical monitoring data corresponding to each auxiliary point as smoothing factors, obtains a plurality of comprehensive indicator change curves by moving average of the plurality of physical-chemical indicator change curves, and updates the preset deduction model parameter library based on the plurality of comprehensive indicator change curves to obtain a water quality monitoring deduction model, including: The historical physical index parameter of each historical monitoring data is set as the auxiliary point corresponding to the historical monitoring data, and the historical chemical index parameter and the historical biological index parameter of the historical monitoring data corresponding to the auxiliary point are read by sliding to the auxiliary point with a preset sliding distance; The historical chemical index parameters of the historical monitoring data corresponding to the several auxiliary points are divided into several data sets with equal data intervals, and the historical chemical index parameters of the corresponding historical monitoring data and the auxiliary points of each data set are fitted into several physical-chemical index change curves; Using the historical biological indicator parameters of the historical monitoring data corresponding to the auxiliary point as smoothing factors, traversing the plurality of physical-chemical indicator change curves through a preset smoothing window for moving average, and obtaining a plurality of comprehensive indicator change curves; Based on the several comprehensive indicator change curves, several comprehensive indicator analysis results are obtained, and the parameter library of the preset deduction model is updated until the several comprehensive indicator analysis results are all updated to obtain a water quality monitoring deduction model.

6. A method for determining water quality risk value of industrial wastewater according to claim 5, characterized in that: Based on the multiple comprehensive index change curves, multiple comprehensive index analysis results are obtained, and the parameter library of the preset deduction model is updated until the multiple comprehensive index analysis results are updated to obtain a water quality monitoring deduction model, including: Extracting data features of the plurality of comprehensive indicator change curves as a plurality of comprehensive indicator analysis results, inputting the plurality of comprehensive indicator analysis results into a preset deduction model in sequence, and querying whether a parameter library of the preset deduction model contains corresponding comprehensive indicator analysis results; If the comprehensive index analysis result does not exist, inserting the comprehensive index analysis result into the parameter library of the preset deduction model to update the database; When the analysis results of several comprehensive indicators have been queried and updated, the preset deduction model after the parameter library is updated is used as the water quality monitoring deduction model.

7. The method for determining the water quality risk value of industrial wastewater according to claim 5, characterized in that: The water quality parameters of the target water area are input into the water quality monitoring deduction model, and the auxiliary point that meets the preset deviation requirements is used as the deduction starting point for deduction and the deduction value of each indicator parameter is recorded. Through different preset red line thresholds and time intervals of the preset prediction time interval, the number of time intervals in which the deduction value of each indicator exceeds the standard is obtained, and the initial water quality risk value is calculated, including: Based on the water quality monitoring deduction model, matching a number of auxiliary points in the water quality monitoring deduction model parameter library whose physical index parameters of the target water area water quality parameters meet a preset first deviation value; Compare the historical chemical index parameters corresponding to each auxiliary point with the chemical index parameters of the target water area water quality parameters one by one to see whether they meet the preset second deviation value, and compare the historical biological index parameters corresponding to each auxiliary point with the biological index parameters of the target water area water quality parameters one by one to see whether they meet the preset third deviation value; Taking the auxiliary point that meets the preset second deviation value and the preset third deviation value as the deduction starting point, recording the change values ​​of each indicator parameter of the deduction starting point on the plurality of comprehensive indicator change curves, and obtaining the deduced value of the physical indicator, the deduced value of the chemical indicator, and the deduced value of the biological indicator; Based on the time interval of the preset prediction time interval, determine whether the physical indicator deduced value, chemical indicator deduced value and biological indicator deduced value exceed the corresponding different preset red line thresholds, obtain the number of time intervals when the physical indicator deduced value exceeds the standard, the number of time intervals when the chemical indicator deduced value exceeds the standard and the number of time intervals when the biological indicator deduced value exceeds the standard, and calculate the initial water quality risk value.

8. The method for determining the water quality risk value of industrial wastewater according to claim 7, characterized in that: The calculation formula of the initial water quality risk value is: ； Where P is the initial water quality risk value, , and They are the number of time intervals when the deduced values ​​of physical indicators exceed the standard, the number of time intervals when the deduced values ​​of chemical indicators exceed the standard, and the number of time intervals when the deduced values ​​of biological indicators exceed the standard. The total number of time intervals for the forecast time interval.

9. The method for determining the water quality risk value of industrial wastewater according to claim 7, characterized in that: The real-time updating of water quality monitoring data at different monitoring points to obtain corresponding actual indicator parameters, calculating the difference between each actual indicator parameter and the deduced value of each indicator parameter, updating the parameter library of the water quality monitoring deduction model according to the difference calculation result, and re-deducing through the updated water quality monitoring deduction model to obtain the optimized water quality risk value, including: Obtain the actual physical index parameters, actual chemical index parameters and actual biological index parameters of water quality monitoring data of different monitoring points updated in real time; Respectively subtracting the actual physical indicator parameter from the physical indicator deduced value, the actual chemical indicator parameter from the chemical indicator deduced value, and the actual biological indicator parameter from the biological indicator deduced value to obtain a physical indicator deduced difference value, a chemical indicator deduced difference value, and a biological indicator deduced difference value; Iterate the deduced values ​​of various indicators that do not meet the preset deduced error range among the deduced difference values ​​of physical indicators, the deduced difference values ​​of chemical indicators and the deduced difference values ​​of biological indicators into corresponding actual indicator parameters, and update the actual indicator parameters to the water quality monitoring deduction model parameter library; Based on the water quality monitoring deduction model after the parameter library is updated, the number of time intervals when the deduced values ​​of physical indicators exceed the standard, the number of time intervals when the deduced values ​​of chemical indicators exceed the standard, and the number of time intervals when the deduced values ​​of biological indicators exceed the standard are re-obtained and the optimized water quality risk value is calculated.

10. A system for determining water quality risk value of industrial wastewater, characterized in that: The method for determining the water quality risk value of industrial wastewater according to any one of claims 1 to 9 comprises: Indicator acquisition module, deduction model construction module, water quality risk value calculation module and water quality risk value optimization module; The indicator acquisition module is used to obtain water quality monitoring data from different monitoring points, select representative characteristic indicators of the water quality monitoring data from different monitoring points by comparing the neighborhood radius of characteristic indicators, obtain physical indicator parameters, chemical indicator parameters and biological indicator parameters, and construct water quality parameters of the target water area; The deduction model construction module is used to use the historical physical indicator parameters of the historical water quality monitoring data as auxiliary points, obtain a number of physical-chemical indicator change curves by fitting the historical chemical indicator parameters of the historical monitoring data corresponding to each auxiliary point, and use the historical biological indicator parameters of the historical monitoring data corresponding to each auxiliary point as a smoothing factor, obtain a number of comprehensive indicator change curves by moving average of the several physical-chemical indicator change curves, and update the preset deduction model parameter library based on the several comprehensive indicator change curves to obtain a water quality monitoring deduction model; The water quality risk value calculation module is used to input the water quality parameters of the target water area into the water quality monitoring deduction model, use the auxiliary point that meets the preset deviation requirements as the deduction starting point to deduce and record the deduced values ​​of each indicator parameter, obtain the number of time intervals in which the deduced values ​​of each indicator exceed the standard through different preset red line thresholds and preset prediction time intervals, and calculate the initial water quality risk value; The water quality risk value optimization module is used to update the water quality monitoring data of different monitoring points in real time to obtain the corresponding actual indicator parameters, calculate the difference between each actual indicator parameter and the deduced value of each indicator parameter, update the parameter library of the water quality monitoring deduction model according to the difference calculation results, and re-deduce through the updated water quality monitoring deduction model to obtain the optimized water quality risk value.

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