Intelligent water affair dynamic monitoring system based on digital twinning technology

Abstract

This invention belongs to the field of water monitoring and management technology, specifically a smart water dynamic monitoring system based on digital twin technology. It includes a wastewater characteristic intelligent sensing module, a digital twin model construction module, a water quality insight and deduction module, a water management decision-making instruction output module, a water management adjustment monitoring and analysis module, and a water management supervision center. Through the water quality insight and deduction module, based on the digital twin model and collected real-time data, this invention achieves real-time monitoring of water quality and accurate prediction of future trends. This facilitates timely implementation of targeted measures to effectively prevent wastewater discharge from polluting nearby areas. Furthermore, by monitoring the execution of water management adjustment measures and reasonably judging their efficiency, it allows for timely training and guidance for on-site personnel and enhanced operational monitoring and control, ensuring the subsequent efficiency of adjustment measures and improving water management effectiveness.

Description

Technical Field

[0001] This invention relates to the field of water resources monitoring and management technology, specifically a smart water resources dynamic monitoring system based on digital twin technology. Background Technology

[0002] In the current field of water monitoring and management, with the acceleration of urbanization and the continuous increase of industrial activities, the amount of sewage discharge has risen sharply, and the water pollution problem has become increasingly serious, posing a serious threat to the ecological environment and human health. Traditional water monitoring and management methods mainly rely on manual sampling and testing of treated sewage. This method is not only time-consuming and labor-intensive, but also has a lag in data acquisition, making it difficult to achieve real-time and dynamic monitoring of water quality.

[0003] Chinese invention patent CN107450454A discloses a wastewater treatment discharge monitoring system based on Internet of Things (IoT) technology. The invention includes a first data acquisition system installed in the wastewater treatment plant and a second data acquisition system installed at each wastewater discharge point after treatment. The first and second data acquisition systems are connected to a host computer installed in the control center through a data communication system, which can receive and process data from all data acquisition points synchronously without the need for continuous monitoring, thus meeting the system's requirements for real-time data acquisition and transmission.

[0004] However, in practical applications, the above-mentioned invention only focuses on the real-time data collection and transmission of discharged wastewater, but it is difficult to achieve real-time monitoring of water quality and accurate prediction of future trends. This makes it difficult to take timely and targeted measures to reduce the risk of pollution from discharge, and it is also impossible to reasonably assess the performance of water management adjustment measures and accurately identify potential water management risks. This is not conducive to improving the effectiveness of water management and has a low level of intelligence.

[0005] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0006] The purpose of this invention is to provide a smart water management dynamic monitoring system based on digital twin technology, which solves the problems of existing technologies that make it difficult to achieve real-time monitoring of water quality and accurate prediction of future trends, and that cannot reasonably evaluate the performance of water management adjustment measures and accurately identify potential water management risks, thus hindering the improvement of water management effectiveness.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The smart water management dynamic monitoring system based on digital twin technology includes a wastewater characteristic intelligent sensing module, a digital twin model construction module, a water quality insight and inference module, a water management decision command output module, a water management adjustment monitoring and analysis module, and a water management monitoring center. The wastewater characteristic intelligent sensing module collects physical, chemical, and biological characteristic data of purified wastewater in real time and comprehensively, and aggregates and preliminarily processes these scattered data.

[0009] The digital twin model construction module constructs a digital twin model that matches the actual water system based on the physical structure, operating rules, and data provided by the data perception and aggregation module. The water quality insight and inference module monitors the water quality of the purified wastewater based on the real-time data provided by the digital twin model and the wastewater characteristic intelligent perception module to identify water quality anomalies and predict the future trend of water quality changes after purification. Through water quality anomaly identification and water quality change trend inference, it determines whether to generate a water quality alarm signal and sends it to the water management decision command output module when a water quality alarm signal is generated.

[0010] The water affairs decision-making instruction output module generates targeted water affairs treatment decision instructions based on water quality alarm signals and relevant water affairs management standards and specifications, and sends them to the water affairs supervision center. The water affairs supervision center then arranges personnel to implement corresponding adjustment measures based on the water affairs treatment decision instructions. The water affairs adjustment monitoring and analysis module monitors the implementation of water affairs adjustment measures, generates adjustment monitoring qualified signals or adjustment monitoring abnormal signals through analysis, and sends these signals to the water affairs supervision center. When the water affairs supervision center receives an adjustment monitoring abnormal signal, it issues a corresponding warning.

[0011] Furthermore, the wastewater characteristic intelligent sensing module deploys various types of sensors at key nodes of the water system. The data collected by these sensors is transmitted to the data aggregation node wirelessly or via wired means. The data aggregation node performs preliminary cleaning and verification on the received data and finally integrates the processed data according to a unified data format.

[0012] Furthermore, the operation process of the digital twin model building module includes:

[0013] A survey and analysis of the actual water system is conducted to obtain information on its physical structure, including the layout of sewage pipes, the installation location of equipment, and connection methods. Combining professional knowledge and operational experience in the water industry, a mathematical model of the water system is established. The mathematical model is trained and optimized using historical and real-time data provided by the intelligent sewage characteristic sensing module to continuously adjust the model parameters, and finally, a digital twin model that matches the actual water system is constructed.

[0014] Furthermore, the specific analysis process of the water affairs adjustment monitoring and analysis module includes:

[0015] The execution completion time for the corresponding adjustment measures is obtained, and the execution completion time is compared with the corresponding preset standard time. If the execution completion time exceeds the corresponding preset standard time, the execution judgment symbol WY-1 is assigned to the corresponding adjustment measures.

[0016] The number of times the judgment symbol WY-1 is assigned during the monitoring period is obtained and the ratio is calculated with the total number of times the adjustment measures are executed to obtain the water adjustment effectiveness value. The water adjustment effectiveness value is compared with the preset water adjustment effectiveness threshold. If the water adjustment effectiveness value exceeds the preset water adjustment effectiveness threshold, an adjustment monitoring abnormal signal is generated.

[0017] Furthermore, if the water adjustment effectiveness value does not exceed the preset water adjustment effectiveness threshold, the ratio of the execution completion time to the corresponding preset standard time is used to calculate the execution completion detection value, and the average of all execution completion detection values ​​within the monitoring period is used to calculate the execution completion monitoring value. The water adjustment hidden danger value is calculated by weighted summation of the water adjustment effectiveness value and the execution completion monitoring value.

[0018] The water management adjustment hazard value is compared with the preset water management adjustment hazard threshold. If the water management adjustment hazard value exceeds the preset water management adjustment hazard threshold, an adjustment monitoring abnormal signal is generated; if the water management adjustment hazard value does not exceed the preset water management adjustment hazard threshold, an adjustment monitoring qualified signal is generated.

[0019] Furthermore, the water affairs adjustment monitoring and analysis module is connected to the water affairs management auxiliary analysis module. The water affairs adjustment monitoring and analysis module sends the adjustment monitoring qualified signal to the water affairs management auxiliary analysis module. When the water affairs management auxiliary analysis module receives the adjustment monitoring qualified signal, it performs auxiliary analysis on water affairs management hidden dangers. Through analysis, it generates water affairs management high hidden danger signals or water affairs management low hidden danger signals, and sends the water affairs management high hidden danger signals or water affairs management low hidden danger signals to the water affairs supervision center. When the water affairs supervision center receives the water affairs management high hidden danger signal, it issues a corresponding warning.

[0020] Furthermore, the specific analysis process of the water management auxiliary analysis module includes:

[0021] All water quality alarm signals generated during the monitoring period are acquired and classified. The number of alarms involved in the corresponding alarm type is marked as the water quality alarm category value. The water quality alarm category value is compared with the corresponding preset water quality alarm category threshold. If the water quality alarm category value exceeds the corresponding preset water quality alarm category threshold, the corresponding alarm type is marked as a high-frequency feedback object.

[0022] If there are high-frequency feedback objects during the monitoring period, a high-risk water management signal is generated; if there are no high-frequency feedback objects during the monitoring period, the water quality alarm category value of the corresponding alarm type is calculated by the ratio of the corresponding preset water quality alarm category threshold to obtain the water quality alarm category value. Each alarm type is assigned a set of preset risk weight values ​​in advance, and the water quality alarm category value of the corresponding alarm type is multiplied by the corresponding preset risk weight value to obtain the water quality alarm analysis value.

[0023] Furthermore, the water quality alarm characteristic value is obtained by summing the water quality alarm analysis values ​​of all alarm types that occur during the monitoring period. The water quality alarm characteristic value is then compared with the preset water quality alarm characteristic threshold. If the water quality alarm characteristic value exceeds the preset water quality alarm characteristic threshold, a high-risk signal for water management is generated.

[0024] Furthermore, if the water quality alarm characteristic value does not exceed the preset water quality alarm characteristic threshold, the pollution characteristic value of each detection point in the sewage discharge area is obtained, and the pollution characteristic value is compared with the preset pollution characteristic threshold. If the pollution characteristic value exceeds the preset pollution characteristic threshold, the corresponding detection point is marked as a harmful point.

[0025] The number of hazardous points in the wastewater discharge area is obtained and the ratio is calculated to the total number of monitoring points to obtain the regional hazardous coefficient. The average pollution characteristic values ​​of all monitoring points are calculated to obtain the pollution performance value, and the pollution characteristic value with the largest value is marked as the pollution amplitude value. The regional discharge supervision value is calculated by weighted summation of the regional hazardous coefficient, pollution performance value, and pollution amplitude value. The regional discharge supervision value is compared with the preset regional discharge supervision threshold. If the regional discharge supervision value exceeds the preset regional discharge supervision threshold, a high risk signal for water management is generated; if the regional discharge supervision value does not exceed the preset regional discharge supervision threshold, a low risk signal for water management is generated.

[0026] Furthermore, the water management auxiliary analysis module is connected to the discharge area monitoring and assessment module. The discharge area monitoring and assessment module sets up several monitoring points in the sewage discharge area and assesses and analyzes the pollution status of each monitoring point. Through analysis, the pollution characteristic values ​​of the corresponding monitoring points are obtained, and the pollution characteristic values ​​of each monitoring point are sent to the water management auxiliary analysis module.

[0027] Furthermore, the specific methods for obtaining pollution characteristic values ​​are as follows:

[0028] Soil information at the corresponding detection points is collected in real time. Based on the soil information, the detection data of various pollution parameters that need to be monitored are obtained. Each pollution parameter is assigned a set of preset hazard weight values ​​in advance. The detection data of each pollution parameter is multiplied with the corresponding preset hazard weight values, and the sum of several sets of product results is marked as the real-time pollution analysis value.

[0029] A rectangular coordinate system is established with time as the X-axis and real-time pollution analysis values ​​as the Y-axis. Based on all real-time pollution analysis values ​​of the corresponding detection points during the monitoring period, a pollution change curve is plotted in the first quadrant of the rectangular coordinate system. A pollution exceedance ray parallel to the X-axis and with its endpoint on the Y-axis is plotted in the first quadrant. The portion of the pollution change curve above the pollution exceedance ray and enclosed by the pollution exceedance ray is captured, and the enclosed portion is marked as the target object. The area of ​​all target objects is collected and summed to obtain the pollution characteristic value of the corresponding detection point.

[0030] Compared with the prior art, the beneficial effects of the present invention are:

[0031] 1. In this invention, the use of digital twin models and collected real-time data enables real-time monitoring of water quality and accurate prediction of future trends. This facilitates timely implementation of targeted measures to effectively prevent sewage discharge from polluting nearby areas. Furthermore, by monitoring the implementation of water management adjustment measures and reasonably judging the efficiency of implementation, timely training and guidance for on-site staff and operational monitoring and control can be strengthened, which is conducive to improving the effectiveness of water management.

[0032] 2. In this invention, the pollution status of each detection point in the sewage discharge area is evaluated and analyzed through the discharge area monitoring and evaluation module, so as to accurately judge the pollution management status of each detection point in the sewage discharge area during the monitoring period. When generating and adjusting the qualified monitoring signal, the potential water management risks are analyzed. When generating the high potential water management risk signal, the investment in water management is increased and the subsequent water management is strengthened to further ensure the effectiveness of water management. The invention has a high level of intelligence. Attached Figure Description

[0033] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0034] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0035] Figure 2 This is a system block diagram of Embodiments 2 and 3 of the present invention. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Example 1: As Figure 1 As shown, the intelligent water dynamic monitoring system based on digital twin technology proposed in this invention includes a wastewater characteristic intelligent sensing module, a digital twin model construction module, a water quality insight and deduction module, a water affairs decision command output module, a water affairs adjustment monitoring and analysis module, and a water affairs monitoring center.

[0038] The wastewater characteristic intelligent sensing module collects physical, chemical and biological characteristic data of the purified wastewater in real time and comprehensively, and aggregates and pre-processes these scattered data. Through comprehensive and real-time data collection and pre-processing, the accuracy and completeness of the data acquired by the system are ensured, providing a reliable data foundation for the accurate analysis of subsequent modules and avoiding analysis errors caused by inaccurate or incomplete data.

[0039] Specifically, the wastewater characteristic intelligent sensing module deploys various types of sensors at key nodes of the water system (such as wastewater discharge outlets, monitoring stations, etc.), such as chemical sensors for detecting chemical indicators such as wastewater acidity (pH value), dissolved oxygen content, chemical oxygen demand (COD), and biochemical oxygen demand (BOD), physical sensors for measuring physical parameters such as wastewater temperature, turbidity, and flow rate, and biological sensors for monitoring the types and quantities of microorganisms in wastewater.

[0040] Various sensors transmit the collected data to the data aggregation node wirelessly or via wired means. The data aggregation node performs preliminary cleaning and verification on the received data, removing noise and erroneous data, and finally integrates the processed data according to a unified data format.

[0041] The digital twin model building module constructs a digital twin model that matches the actual water system based on its physical structure, operational patterns, and data provided by the data sensing and aggregation module. By building a high-precision digital twin model, it achieves digital replication and dynamic simulation of the actual water system, facilitating real-time monitoring and predictive analysis. The operation process of the digital twin model building module is as follows:

[0042] First, a survey and analysis of the actual water system is conducted to obtain information on its physical structure, including the layout of sewage pipes, the installation location of equipment, and connection methods. Then, combining professional knowledge and operational experience in the water industry, a mathematical model of the water system is established. Historical and real-time data provided by the intelligent sewage characteristic sensing module are used to train and optimize the mathematical model to continuously adjust the model parameters, enabling it to more accurately simulate the operating state of the actual water system. Finally, a digital twin model that is highly consistent with the actual water system in terms of geometry, physics, and behavior is constructed. This digital twin model can reflect the operating status of the actual water system in real time and can be dynamically updated and simulated and predicted based on the input data.

[0043] The water quality insight and projection module, based on real-time data provided by the digital twin model and the intelligent wastewater characteristic sensing module, monitors the water quality of purified wastewater to identify water quality anomalies, such as whether key water quality indicators like ammonia nitrogen, total phosphorus, and total nitrogen exceed standards. It also projects and predicts future trends in the purified wastewater quality. For example, by analyzing historical COD data over time, it predicts the future trend of COD values. Through water quality anomaly identification and trend projection, it determines whether to generate a water quality alarm signal. When an alarm signal is generated, it is sent to the water management decision-making output module, providing strong support for regulators to take timely measures to address water quality issues and helping to prevent pollution of the surrounding environment caused by wastewater discharge.

[0044] The water management decision-making instruction output module generates targeted water treatment decision-making instructions based on water quality alarm signals and relevant water management standards and specifications, and sends them to the water management supervision center. The water management supervision center then arranges personnel to implement corresponding adjustment measures based on the water treatment decision-making instructions. It can quickly generate scientific and reasonable decision-making instructions based on real-time monitoring and predictive analysis results, guiding on-site staff to handle wastewater quality problems in a timely and effective manner, improving the efficiency and accuracy of problem handling, and ensuring the compliance rate of wastewater discharge.

[0045] For example, if the abnormal water quality is caused by equipment failure at the wastewater treatment plant, the decision-making instruction might be to immediately arrange maintenance personnel to repair the corresponding wastewater treatment equipment; if it is predicted that a certain indicator in the wastewater may exceed the standard in the future, the decision-making instruction might be to adjust the operating parameters of the wastewater treatment equipment or increase the corresponding dosage of chemicals, etc.

[0046] The water management adjustment monitoring and analysis module monitors the implementation of water management adjustment measures. It generates qualified or abnormal adjustment monitoring signals through analysis and sends these signals to the water management supervision center. Upon receiving an abnormal adjustment monitoring signal, the water management supervision center issues a corresponding warning to remind supervisory personnel to strengthen training and guidance for on-site staff and improve operational monitoring and control, ensuring the subsequent implementation efficiency of adjustment measures and improving water management effectiveness. The specific analysis process of the water management adjustment monitoring and analysis module is as follows:

[0047] The execution completion time for the corresponding adjustment measures is obtained. The execution completion time is compared with the corresponding preset standard time. If the execution completion time exceeds the corresponding preset standard time, it indicates that the execution operation for the corresponding adjustment measures is slow. Then, the corresponding adjustment measures are assigned the execution judgment symbol WY-1.

[0048] The number of times the judgment symbol WY-1 is assigned during the monitoring period is obtained and the ratio is calculated with the total number of times the adjustment measures are executed to obtain the water adjustment efficiency value. The water adjustment efficiency value is compared with the preset water adjustment efficiency threshold. If the water adjustment efficiency value exceeds the preset water adjustment efficiency threshold, it indicates that the water adjustment implementation efficiency is poor during the monitoring period, and an adjustment monitoring abnormal signal is generated.

[0049] Furthermore, if the water adjustment efficiency value does not exceed the preset water adjustment efficiency threshold, the ratio of the execution completion time to the corresponding preset standard time is used to calculate the completion detection value, and the average of all completion detection values ​​within the monitoring period is used to calculate the completion monitoring value.

[0050] The water management adjustment hazard value is calculated by weighted summation of the water management adjustment effectiveness value and the implementation monitoring value. Specifically, a corresponding preset weight coefficient is assigned to the water management adjustment effectiveness value and the implementation monitoring value, and the water management adjustment effectiveness value and the implementation monitoring value are multiplied by the corresponding preset weight coefficient. The sum of the two sets of products is marked as the water management adjustment hazard value. It should be noted that the larger the value of the water management adjustment hazard value, the worse the overall performance of the water management measures implementation efficiency during the monitoring period.

[0051] The water management adjustment hazard value is compared with the preset water management adjustment hazard threshold. If the water management adjustment hazard value exceeds the preset water management adjustment hazard threshold, it indicates that the overall performance of the water management measures adjustment implementation efficiency during the monitoring period is poor, and an adjustment monitoring abnormal signal is generated. If the water management adjustment hazard value does not exceed the preset water management adjustment hazard threshold, it indicates that the overall performance of the water management measures adjustment implementation efficiency during the monitoring period is good, and an adjustment monitoring qualified signal is generated.

[0052] Example 2: Figure 2 As shown, the difference between this embodiment and Embodiment 1 is that the water affairs adjustment monitoring and analysis module is communicatively connected to the water affairs management auxiliary analysis module. The water affairs adjustment monitoring and analysis module sends the adjustment monitoring qualified signal to the water affairs management auxiliary analysis module. When the water affairs management auxiliary analysis module receives the adjustment monitoring qualified signal, it performs auxiliary analysis on water affairs management hidden dangers and generates water affairs management high hidden danger signals or water affairs management low hidden danger signals through analysis.

[0053] Furthermore, high-risk or low-risk water management signals are sent to the water management supervision center. Upon receiving a high-risk signal, the water management supervision center issues a corresponding warning to remind supervisors to increase investment in water management, strengthen subsequent water management, and further ensure the effectiveness of subsequent water management. The specific analysis process of the water management auxiliary analysis module is as follows:

[0054] All water quality alarm signals generated during the monitoring period are acquired and classified. The number of alarms involved in the corresponding alarm type is marked as the water quality alarm category value. The water quality alarm category value is compared with the corresponding preset water quality alarm category threshold. If the water quality alarm category value exceeds the corresponding preset water quality alarm category threshold, it indicates that the corresponding alarm type occurs frequently and is difficult to resolve effectively. In this case, the corresponding alarm type is marked as a high-frequency feedback object.

[0055] If high-frequency feedback objects exist during the monitoring period, it indicates a high risk of water management problems, and a high risk of water management problems signal is generated. If no high-frequency feedback objects exist during the monitoring period, the water quality alarm category value of the corresponding alarm type is calculated by the ratio of the water quality alarm category value of the corresponding alarm type to the corresponding preset water quality alarm category threshold. Each alarm type is assigned a set of preset risk weight values ​​with a value greater than zero. Furthermore, the greater the difficulty in handling the corresponding alarm type and the greater the risk it brings, the greater the value of the preset risk weight value that matches it.

[0056] The water quality alarm category value of the corresponding alarm type is multiplied by the corresponding preset hidden danger weight value to obtain the water quality alarm analysis value; and the water quality alarm analysis values ​​of all alarm types that occurred during the monitoring period are summed to obtain the water quality alarm characteristic value. The water quality alarm characteristic value is compared with the preset water quality alarm characteristic threshold. If the water quality alarm characteristic value exceeds the preset water quality alarm characteristic threshold, it indicates that the water management hidden danger is high, and a high hidden danger signal for water management is generated.

[0057] Furthermore, if the water quality alarm characteristic value does not exceed the preset water quality alarm characteristic threshold, the pollution characteristic value of each detection point in the sewage discharge area is obtained, and the pollution characteristic value is compared with the preset pollution characteristic threshold. If the pollution characteristic value exceeds the preset pollution characteristic threshold, it indicates that the pollution management status of the corresponding detection point is poor, and the corresponding detection point is marked as a harmful point.

[0058] The number of hazardous points in the wastewater discharge area is obtained and the ratio of this number to the total number of monitoring points is used to calculate the regional hazard coefficient. The average value of the pollution characteristic values ​​of all monitoring points is used to calculate the pollution performance value, and the pollution characteristic value with the largest value is marked as the pollution amplitude value.

[0059] The regional emission regulatory value is calculated by weighting and summing the regional hazard coefficient, pollution performance value, and pollution amplitude value. Specifically, each of the three values ​​is assigned a corresponding preset weight coefficient, and then multiplied by the respective preset weight coefficient. The sum of these three products is then marked as the regional emission regulatory value. It should be noted that the larger the regional emission regulatory value, the worse the overall regulatory performance of wastewater treatment discharge during the monitoring period, and the higher the potential water management risks.

[0060] The regional emission monitoring value is compared with the preset regional emission monitoring threshold. If the regional emission monitoring value exceeds the preset regional emission monitoring threshold, it indicates that the overall performance of the monitoring of wastewater treatment emissions during the monitoring period is poor, and the potential water management risks are high, thus generating a high water management risk signal. If the regional emission monitoring value does not exceed the preset regional emission monitoring threshold, it indicates that the overall performance of the monitoring of wastewater treatment emissions during the monitoring period is good, thus generating a low water management risk signal.

[0061] Example 3: Figure 2 As shown, the difference between this embodiment and Embodiments 1 and 2 is that the water management auxiliary analysis module is communicatively connected to the discharge area monitoring and assessment module. The discharge area monitoring and assessment module sets up several monitoring points in the sewage discharge area and assesses and analyzes the pollution status of each monitoring point. Through analysis, it obtains the pollution characteristic values ​​of the corresponding monitoring points and sends the pollution characteristic values ​​of each monitoring point to the water management auxiliary analysis module and the water supervision center. This not only accurately assesses the pollution management status of each monitoring point in the sewage discharge area during the monitoring period, but also provides data support for the analysis process of the water management auxiliary analysis module, thereby ensuring the rationality and accuracy of its analysis results. The specific method for obtaining the pollution characteristic values ​​is as follows:

[0062] Soil information at the corresponding monitoring points is collected in real time. Based on the soil information, the detection data of various pollution parameters that need to be monitored are obtained. Each pollution parameter is assigned a set of preset hazard weight values ​​with a value greater than zero. The more serious the hazard caused by the corresponding pollution parameter, the larger the value of the preset hazard weight value. The detection data of each pollution parameter is multiplied by the corresponding preset hazard weight value, and the sum of several sets of product results is marked as the real-time pollution analysis value.

[0063] A rectangular coordinate system is established with time as the X-axis and real-time pollution analysis value as the Y-axis. Based on all real-time pollution analysis values ​​of the corresponding detection points during the monitoring period, a pollution change curve is plotted in the first quadrant of the rectangular coordinate system. In the first quadrant, a pollution exceedance ray is plotted parallel to the X-axis with its endpoint located on the Y-axis.

[0064] The pollution change curve is captured in the area enclosed by the pollution exceeding the standard ray and the pollution exceeding the standard ray. This enclosed area is marked as the target object. The area of ​​all target objects is collected and summed to obtain the pollution characteristic value of the corresponding detection point. It should be noted that the larger the value of the pollution characteristic value, the worse the pollution management status of the corresponding detection point during the monitoring period.

[0065] The working principle of this invention is as follows: During use, the wastewater characteristic intelligent sensing module collects and processes various characteristic data of the purified wastewater in real time and comprehensively. The digital twin model construction module constructs a digital twin model highly consistent with the actual water system. The water quality insight and deduction module dynamically simulates the operating status of the actual water system based on the digital twin model and the collected real-time data, achieving real-time monitoring of water quality and accurate prediction of future trends. Upon detecting water quality anomalies or predicting potential water quality problems, a water quality alarm signal is immediately generated, and targeted water treatment decision instructions are automatically generated to guide on-site personnel to take timely measures to effectively prevent wastewater discharge from polluting the surrounding environment. Furthermore, the water adjustment monitoring and analysis module monitors the execution of water adjustment measures. When an abnormal adjustment monitoring signal is generated, training and guidance for on-site personnel are strengthened, and operational monitoring and control are enhanced to ensure the subsequent execution efficiency of adjustment measures, thereby improving water management effectiveness.

[0066] In this invention, the threshold, preset value, or preset range settings are for result comparison and analysis to determine whether the result is good or bad. The magnitude of these values ​​is determined by a combination of large-scale model analysis of sample data and human experience, and can also be appropriately adjusted based on seasonal or common-sense influence conditions. Similarly, the preset weight coefficients and influence factors are assigned specific values ​​based on the magnitude of each parameter's influence on the result, ultimately reflecting the impact on the result. These settings are also determined by a combination of large-scale model analysis of sample data and human experience, and can also be appropriately adjusted based on seasonal or common-sense influence conditions.

[0067] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, enabling those skilled in the art to better understand and utilize it. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A smart water management dynamic monitoring system based on digital twin technology, characterized in that, It includes a wastewater characteristic intelligent sensing module, a digital twin model construction module, a water quality insight and deduction module, a water affairs decision command output module, a water affairs adjustment monitoring and analysis module, and a water affairs supervision center. The wastewater characteristic intelligent sensing module collects various characteristic data of purified wastewater and performs aggregation and preliminary processing. The digital twin model construction module constructs a digital twin model that matches the actual water affairs system. The water quality insight and deduction module, based on the digital twin model and real-time data, determines whether to generate a water quality alarm signal through water quality anomaly identification and water quality change trend deduction. When a water quality alarm signal is generated, it is sent to the water affairs decision command output module. The water affairs decision-making instruction output module generates targeted water affairs treatment decision instructions based on water quality alarm signals and relevant water affairs management standards and specifications, and sends them to the water affairs supervision center. The water affairs supervision center then arranges personnel to implement corresponding adjustment measures based on the water affairs treatment decision instructions. The water affairs adjustment monitoring and analysis module monitors the implementation of water affairs adjustment measures, generates adjustment monitoring qualified signals or adjustment monitoring abnormal signals through analysis, and sends the adjustment monitoring qualified signals or adjustment monitoring abnormal signals to the water affairs supervision center. The specific analysis process of the water affairs adjustment monitoring and analysis module includes: The execution completion time for the corresponding adjustment measures is obtained, and the execution completion time is compared with the corresponding preset standard time. If the execution completion time exceeds the corresponding preset standard time, the execution judgment symbol WY-1 is assigned to the corresponding adjustment measures. The number of times the judgment symbol WY-1 is assigned during the monitoring period is obtained and the ratio is calculated with the total number of times the adjustment measures are executed to obtain the water adjustment effectiveness value. The water adjustment effectiveness value is compared with the preset water adjustment effectiveness threshold. If the water adjustment effectiveness value exceeds the preset water adjustment effectiveness threshold, an adjustment monitoring abnormal signal is generated. If the water adjustment effectiveness value does not exceed the preset water adjustment effectiveness threshold, the ratio of the execution completion time to the corresponding preset standard time is used to calculate the execution completion detection value, and the average of all execution completion detection values ​​within the monitoring period is used to calculate the execution completion monitoring value. The water adjustment hidden danger value is calculated by weighted summation of the water adjustment effectiveness value and the execution completion monitoring value. The water management adjustment hazard value is compared with the preset water management adjustment hazard threshold. If the water management adjustment hazard value exceeds the preset water management adjustment hazard threshold, an adjustment monitoring abnormal signal is generated; if the water management adjustment hazard value does not exceed the preset water management adjustment hazard threshold, an adjustment monitoring qualified signal is generated. The water affairs adjustment monitoring and analysis module is connected to the water affairs management auxiliary analysis module. The water affairs adjustment monitoring and analysis module sends the adjustment monitoring qualified signal to the water affairs management auxiliary analysis module. When the water affairs management auxiliary analysis module receives the adjustment monitoring qualified signal, it performs auxiliary analysis on water affairs management hidden dangers. Through analysis, it generates water affairs management high hidden danger signal or water affairs management low hidden danger signal and sends the water affairs supervision center. When the water affairs supervision center receives the water affairs management high hidden danger signal, it issues a corresponding warning. The specific analysis process of the water management auxiliary analysis module includes: All water quality alarm signals generated during the monitoring period are acquired and classified. The number of alarms involved in the corresponding alarm type is marked as the water quality alarm category value. The water quality alarm category value is compared with the corresponding preset water quality alarm category threshold. If the water quality alarm category value exceeds the corresponding preset water quality alarm category threshold, the corresponding alarm type is marked as a high-frequency feedback object. If there are high-frequency feedback objects during the monitoring period, a high-risk water management signal is generated; if there are no high-frequency feedback objects during the monitoring period, the water quality alarm category value of the corresponding alarm type is calculated by the ratio of the corresponding preset water quality alarm category threshold to obtain the water quality alarm category value. Each alarm type is assigned a set of preset risk weight values ​​in advance, and the water quality alarm category value of the corresponding alarm type is multiplied by the corresponding preset risk weight value to obtain the water quality alarm analysis value. Furthermore, the water quality alarm characteristic value is obtained by summing the water quality alarm analysis values ​​of all alarm types that occur during the monitoring period. The water quality alarm characteristic value is then compared with the preset water quality alarm characteristic threshold. If the water quality alarm characteristic value exceeds the preset water quality alarm characteristic threshold, a high-risk signal for water management is generated. If the water quality alarm characteristic value does not exceed the preset water quality alarm characteristic threshold, the pollution characteristic value of each detection point in the sewage discharge area is obtained, and the pollution characteristic value is compared with the preset pollution characteristic threshold. If the pollution characteristic value exceeds the preset pollution characteristic threshold, the corresponding detection point is marked as a harmful point. The system obtains the number of hazardous points in the wastewater discharge area and calculates the regional hazard coefficient by comparing it with the total number of monitoring points. It also calculates the pollution performance value by averaging the pollution characteristic values ​​of all monitoring points and marks the pollution amplitude value as the highest value. The regional discharge supervision value is calculated by weighted summing of the regional hazard coefficient, pollution performance value, and pollution amplitude value. This regional discharge supervision value is then compared with a preset regional discharge supervision threshold. If the regional discharge supervision value exceeds the preset threshold, a high-risk signal for water management is generated; otherwise, a low-risk signal for water management is generated. The water management auxiliary analysis module is connected to the discharge area monitoring and assessment module. The discharge area monitoring and assessment module sets up several monitoring points in the sewage discharge area and assesses and analyzes the pollution status of each monitoring point. Through analysis, the pollution characteristic values ​​of the corresponding monitoring points are obtained, and the pollution characteristic values ​​of each monitoring point are sent to the water management auxiliary analysis module. The specific methods for obtaining pollution characteristic values ​​are as follows: Soil information at the corresponding detection points is collected in real time. Based on the soil information, the detection data of various pollution parameters that need to be monitored are obtained. Each pollution parameter is assigned a set of preset hazard weight values ​​in advance. The detection data of each pollution parameter is multiplied with the corresponding preset hazard weight values, and the sum of several sets of product results is marked as the real-time pollution analysis value. A rectangular coordinate system is established with time as the X-axis and real-time pollution analysis values ​​as the Y-axis. Based on all real-time pollution analysis values ​​of the corresponding detection points during the monitoring period, a pollution change curve is plotted in the first quadrant of the rectangular coordinate system. A pollution exceedance ray parallel to the X-axis and with its endpoint on the Y-axis is plotted in the first quadrant. The portion of the pollution change curve above the pollution exceedance ray and enclosed by the pollution exceedance ray is captured, and the enclosed portion is marked as the target object. The area of ​​all target objects is collected and summed to obtain the pollution characteristic value of the corresponding detection point.

2. The intelligent water management dynamic monitoring system based on digital twin technology according to claim 1, characterized in that, The wastewater characteristic intelligent sensing module deploys various types of sensors at key nodes of the water system. The sensors transmit the collected data to the data aggregation node, which performs preliminary cleaning, verification and integration of the received data.

3. The intelligent water management dynamic monitoring system based on digital twin technology according to claim 1, characterized in that, The operation process of the digital twin model construction module includes: acquiring the physical structure information of the water system, combining professional knowledge and operational experience in the water field, establishing a mathematical model of the water system, using historical and real-time data provided by the wastewater feature intelligent sensing module to train and optimize the mathematical model to continuously adjust the model parameters, and finally constructing a digital twin model that matches the actual water system.

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