Intelligent monitoring method and system for sewage treatment

Abstract

The present application relates to sewage treatment technical field, especially sewage treatment intelligent monitoring method and system, including: through sensor obtains rainwater collection drainage node's sewage discharge, water quality parameter and drainage point coordinate, and carries out pretreatment. Based on real-time sewage discharge and pipeline design maximum flow rate, the real-time load rate is calculated, the water quality difference between adjacent nodes and the pipeline water quality difference are analyzed, the path distance is calculated combined with the drainage point coordinates, the exponential function is used to comprehensively evaluate the discharge suitability index, the comprehensive dynamic weight is formed by fusing the real-time load rate, and the A algorithm is used to obtain the optimal path. Based on the comprehensive dynamic weight processing conflict, the intelligent selection of the drainage path is realized, and the operation of the drainage network is optimized. The present application optimizes the selection of the discharge path by calculating the water quality difference between the drainage nodes and the pipeline water quality difference, thereby reducing the risk of pollutant diffusion, improving the sewage treatment efficiency and suitability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sewage treatment. In particular, it relates to a sewage treatment intelligent monitoring method and system. BACKGROUND

[0002] A sponge city is a modern urban rainwater management concept that aims to absorb, infiltrate, and purify rainwater in a natural way, just like a sponge, so that the city can absorb and store rainwater during rainfall and release it when needed. This concept not only helps to alleviate urban waterlogging problems, but also effectively improves the urban ecological environment and promotes the sustainable use of water resources. In the construction of a sponge city, sewage treatment is a key link that is important for protecting the quality of the urban water environment and ecological balance.

[0003] Sewage treatment is an integral part of sponge city construction, and it directly affects the quality of the urban water environment and the health of the ecological system. Effective sewage treatment can reduce pollutant emissions, reduce pollution of natural water bodies, protect biodiversity, and also help improve the quality of life of urban residents. In addition, through reasonable sewage treatment and reuse, water resources can be recycled, alleviating the problem of urban water shortages.

[0004] However, existing sewage treatment systems still have some problems when faced with the requirements of sponge city construction. The existing technology has the defect that the pipeline connection is fixed and cannot be dynamically adjusted according to real-time load. This static topology limitation makes it difficult for the system to effectively respond to sudden changes in water volume. In addition, the existing system does not integrate water quality parameters and spatial location information, making the scheduling decision lack comprehensive data support. At the same time, manual analysis of sensor data is time-consuming and cannot meet the rapid response requirements of minute-level water volume mutations. SUMMARY

[0005] To solve the problem of how to achieve load balancing at each drainage point, dynamically optimize the discharge path from the drainage node to the target node, and reduce the comprehensive cost of sewage treatment, the present application provides solutions in the following aspects.

[0006] In a first aspect, an intelligent monitoring method for sewage treatment includes: acquiring sewage discharge parameters, water quality parameters, and drainage point coordinates at multiple rainwater collection and drainage nodes, and preprocessing, wherein the water quality parameters include node water quality parameters and pipeline water quality parameters; analyzing the real-time load rate of each drainage point based on the real-time sewage discharge and the designed maximum flow rate of the pipeline, calculating the water quality difference of the same water quality parameters between adjacent drainage nodes, and the pipeline water quality difference between the node water quality parameters of the drainage node and the water quality parameters of the connected pipeline, and calculating the path distance between adjacent drainage nodes based on the drainage point coordinates; comprehensively evaluating the discharge suitability index using an exponential function based on the water quality difference between adjacent drainage nodes, the pipeline water quality difference, and the path distance; fusing the real-time load rate and the discharge suitability index to form a comprehensive dynamic weight, and using the A algorithm to obtain the optimal path, and based on the comprehensive dynamic weight, processing the path conflict when multiple drainage nodes discharge simultaneously and the optimal path appears node conflict, to realize the selection of the drainage path of the drainage network.

[0007] The intelligent monitoring and dynamic optimization method significantly improves the efficiency and response capability of the sponge city sewage treatment system, ensures stable operation in the face of extreme conditions such as heavy rain, and effectively reduces the risk of pollutant diffusion and sewage treatment costs, while enhancing environmental protection, thereby achieving more sustainable and economically efficient urban water management.

[0008] Preferably, the calculation method of the real-time load rate includes:

[0009] The product of the cross-sectional area of the drainage pipe and the maximum allowable flow rate is taken as the pipeline maximum flow rate, and the ratio of the real-time sewage discharge to the pipeline maximum flow rate is taken as the real-time load rate.

[0010] Preferably, the calculation of the water quality difference of the same water quality parameters at adjacent drainage nodes includes:

[0011] Taking any drainage node as a target node, acquiring other nodes connected to the target node through the water pipe, calculating the square root of the sum of the differences between the water quality parameters of the target node and other nodes, and obtaining the water quality difference between the target node and other nodes.

[0012] By calculating the water quality difference between drainage nodes, the water quality similarity is quantitatively evaluated, and a smaller value indicates a higher water quality similarity. This helps to identify drainage paths with lower pollution diffusion risk and higher suitability, thereby enhancing the efficiency and effectiveness of sewage treatment and providing strong support for environmental protection, ensuring that the drainage system can be more intelligent and flexible to adapt to changing water quality conditions and treatment needs.

[0013] Preferably, the pipe water quality difference includes:

[0014] Taking any drainage node as the target node, the square root of the sum of the squares of the difference between the water quality parameters of the pipes connected to the target node and the water quality parameters of the target node is calculated to obtain the pipe water quality difference between the target node and the corresponding pipe.

[0015] By accurately calculating the water quality difference between the drainage node and the connected pipe, the optimization of the drainage path selection is realized. When the calculated water quality difference value is small, it indicates that the pipe water quality is highly consistent with the target node water quality, which helps to reduce the diffusion risk of pollutants in the drainage process and improve the suitability of the discharge path. This significantly improves the accuracy and efficiency of the sewage treatment system, while providing strong protection for environmental protection, ensuring that the system can flexibly adapt to changing water quality conditions and treatment needs.

[0016] Preferably, the calculation method of the discharge suitability index includes:

[0017] In response to the existence of multiple direct pipes between two drainage nodes, the product of the water quality difference, the preset distance weight coefficient and the path distance, and the pipe water quality difference are respectively processed using a negative exponential function, the obtained results are multiplied, and the maximum value is selected as the discharge suitability index;

[0018] In response to the absence of multiple direct pipes between two drainage nodes, the product of the water quality difference and the product of the preset distance weight coefficient and the path distance is processed using a negative exponential function, and the discharge suitability index is obtained by multiplication;

[0019] In response to the absence of direct pipes between two drainage nodes, it indicates that the two drainage nodes cannot directly communicate drainage.

[0020] By accurately evaluating the suitability of different discharge paths in a complex drainage network, the path selection is optimized, the diffusion risk of pollutants is reduced, and the efficiency and environmental friendliness of the sewage treatment system are improved, ensuring that the system can intelligently adapt to different water quality conditions and treatment needs.

[0021] Preferably, the A algorithm based on the comprehensive dynamic weight uses to obtain the optimal path, including the steps of:

[0022] Establishing a drainage network diagram, wherein each drainage point is defined as a node in the diagram, the connection between the drainage points is defined as an edge in the diagram, and the weight of each edge is determined based on the comprehensive dynamic weight, and the starting point and the endpoint of the A algorithm are determined;

[0023] The heuristic function is constructed by using the comprehensive dynamic weight of each edge as a factor affecting the Euclidean distance, to estimate the shortest path cost from any node to the end point and obtain the optimal path.

[0024] Preferably, the path conflict is processed based on the comprehensive dynamic weight when multiple nodes are drained, including:

[0025] In response to multiple paths passing through one or more same nodes at the same time, the cumulative comprehensive dynamic weight of the starting point of each path and the conflict node is calculated, the path corresponding to the maximum cumulative comprehensive weight is selected to pass through the conflict node preferentially, the pipeline occupation is marked, the conflict node is removed from the available node set, re-distribution is performed, the discharge suitability index and the comprehensive dynamic weight are recalculated, the path is re-planned, and the efficiency and stability of system operation are ensured.

[0026] In the second aspect, an intelligent sewage treatment monitoring system includes a processor and a memory, and the memory stores computer program instructions which, when executed by the processor, implement the above-mentioned intelligent sewage treatment monitoring method.

[0027] The present application has the following effects:

[0028] 1. The present application can identify a discharge path with higher water quality matching degree by calculating the water quality difference between drainage nodes and the water quality difference of the pipeline. Selecting a path with high water quality matching degree for discharge can reduce the risk of pollutant diffusion when sewage is mixed, improve discharge suitability, reduce the difficulty of sewage treatment caused by water quality mismatch, make the treatment process more efficient, reduce treatment cost, optimize the discharge path, reduce the load of the sewage treatment plant, and improve overall treatment efficiency.

[0029] 2. The heuristic function can more accurately estimate the path cost from any node to the end point by reflecting the Euclidean distance of the comprehensive dynamic weight. This cost includes not only the physical distance, but also factors such as water quality difference and real-time load rate, thereby providing a more comprehensive path cost evaluation. By selecting the path with the lowest cost, the operation cost of sewage treatment and transportation can be reduced, and cost-effectiveness maximization can be achieved. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 is a method flowchart of steps S1-S4 in an embodiment of the sewage treatment intelligent monitoring method of the present application.

[0031] Figure 2 is a structural block diagram of an embodiment of the sewage treatment intelligent monitoring system of the present application. DETAILED DESCRIPTION

[0032] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described below. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application.

[0033] Specific implementation scenarios:

[0034] In the control of sponge city sewage treatment, there are multiple key nodes and pipelines that jointly affect the entire sewage treatment system. The collection points usually include: rainwater collection points, initial rainwater collection points, industrial area sewage collection points, and other collection points.

[0035] Among them, the rainwater collection point is a facility for collecting natural rainfall and transporting it to the drainage pipeline network. It is distributed in various areas of the city, such as streets, squares, parks, rooftops, and parking lots, etc. Its main function is to collect rainwater, reduce pre-examination runoff, alleviate urban waterlogging, protect the urban drainage system, cover various open areas of the city, collect relatively clean rainwater with low pollutant concentration, and transport it to the drainage pipeline network. However, during heavy rain, the water volume at the node increases sharply, causing a sudden increase in pipeline load rate, triggering local overload or even blockage, and affecting the normal operation of the drainage system.

[0036] The initial rainwater collection point is a facility specifically designed to collect rainwater formed during the initial stage of rainfall. These rainwaters usually contain high concentrations of pollutants. The initial rainwater collection point is mainly distributed in low-lying areas of the city or at the entrance of the drainage system to quickly collect initial rainwater. Since initial rainwater will scour the ground during its formation, it carries a large amount of pollutants such as chemical oxygen demand (COD), suspended solids (SS), heavy metals, and oils, etc. Therefore, it needs to be pretreated. Pretreatment methods include sedimentation, filtration, and biological treatment, etc., with the purpose of reducing pollutant concentration and reducing the entry of high-concentration pollutants into the drainage system. This not only helps to reduce the impact on the sewage treatment plant, but also effectively protects the water environment.

[0037] The industrial area sewage collection point is located in the industrial area, close to the factory drainage outlet or the centralized drainage system, and is mainly responsible for collecting industrial wastewater containing harmful substances such as heavy metals (such as lead, copper, zinc, etc.), organic solvents, chemical oxygen demand (COD), biochemical oxygen demand (BOD), etc. These wastewaters need to be treated deeply, including chemical, physical, and biological treatment, to ensure that the concentration of harmful substances meets the discharge standards, thereby reducing environmental pollution and improving the treatment efficiency of the sewage treatment plant.

[0038] During heavy rain, the water volume at the rainwater collection point and the initial rainwater collection point increases sharply, which may cause a sudden increase in pipeline load rate and affect the normal operation of the drainage system. Therefore, it is necessary to dynamically adjust the discharge path through an intelligent monitoring system to avoid overload and blockage.

[0039] Industrial wastewater collection points contain specific hazardous substances, so special attention needs to be paid to the selection of their discharge routes in order to reduce their impact on the environment.

[0040] A drainage network diagram is constructed for each region, where each node represents a drainage point and edges represent pipe connections between nodes. The weight of each edge is determined by a comprehensive dynamic weight that considers factors such as water quality differences, path distance, and real-time load rate. In this way, the drainage network diagram can reflect the structure and operational status of the entire wastewater treatment system.

[0041] Reference Figure 1 A wastewater treatment intelligent monitoring method includes steps S1-S4, as detailed below:

[0042] S1: Obtain sewage discharge parameters, water quality parameters, and drainage point coordinates at multiple rainwater collection and drainage nodes, and perform preprocessing. The water quality parameters include node water quality parameters and pipeline water quality parameters.

[0043] Deploy a multi-parameter real-time sensor network at rainwater harvesting and drainage nodes to collect real-time sewage discharge data. (Unit: m³ / s) Water quality parameters (Concentrations of pollutants such as COD, TN, TP, etc., in mg / L) and GPS coordinates (latitude and longitude) of the drainage point, with water quality parameters sampled once per second.

[0044] If there are multiple directly connected pipes between nodes, a supplementary sensor network is deployed at key points of the pipes to obtain the pipe segment (the first segment) at the corresponding drainage node from two adjacent linked drainage nodes. The node to the first Real-time pollutant concentration (through pipelines between nodes) The sampling frequency is 1 time per second. When the sensors in the pipeline malfunction or the data is unavailable, the real-time pollutant concentration at the corresponding node within the pipeline segment is used. As an approximation of the concentration of pollutants inside the pipeline.

[0045] Water quality parameters are preprocessed, and a data cleaning procedure is performed to identify and remove invalid data or outliers caused by sensor malfunctions or external interference, ensuring the accuracy and reliability of the input data. Valid water quality parameter data are standardized to eliminate incomparability caused by different dimensions, ensuring consistent measurement standards for all parameters in subsequent analyses.

[0046] Obtain the maximum flow rate of the pipeline design The pipeline connection topology is stored in the form of an adjacency matrix. The initial weight of the adjacency matrix is ​​set to the geographical distance of the pipeline, and the edge weights are dynamically updated based on the real-time load rate.

[0047] S2: According to the real-time sewage discharge of each drainage point and the pipe design maximum flow, the real-time load rate of each drainage point is analyzed, the water quality difference of the same water quality parameter between adjacent drainage nodes and the pipe water quality difference between the node water quality parameter of the drainage node and the water quality parameter of the connected pipe are calculated, and the path distance between adjacent drainage nodes is calculated based on the coordinates of the drainage points.

[0048] The product of the cross-sectional area of the drainage pipe and the maximum allowable flow rate is taken as the pipe maximum flow, and the ratio of the real-time sewage discharge to the pipe maximum flow is taken as the real-time load rate.

[0049] Specifically, the real-time load rate satisfies the following relationship:

[0050] ;

[0051] In the formula, represents the real-time load rate, represents the real-time flow in the current pipe, represents the pipe design maximum flow, represents the pipe diameter (m), represents the maximum allowable flow rate.

[0052] It should be noted that, is the cross-sectional area of the pipe, and the flow is the volume passing through the pipe cross-section per unit time, and the maximum speed of the fluid flowing in the pipe is determined by the design standard or safety requirement to prevent the fluid in the pipe from causing excessive pressure or wear on the pipe.

[0053] Taking any drainage node as a target node, other nodes connected to the target node through the water pipe are obtained, the square root of the sum of the differences between the water quality parameters of the target node and other nodes is calculated, and the water quality difference between the target node and other nodes is obtained.

[0054] Specifically, the water quality difference of the same water quality parameter at adjacent drainage nodes satisfies the following relationship:

[0055] ;

[0056] In the formula, represents the water quality difference of the same water quality parameter between the th node and the th node, represents the number of types of water quality, represents the th water quality parameter at the th node, is the th water quality parameter at the th node, and there are The smaller the value of the water quality parameter, the smaller the difference in water quality. The smaller the value of the water quality parameter, the smaller the difference in water quality.

[0057] Taking any drainage node as the target node, the square root of the sum of the differences between the water quality parameters of the pipes connected to the target node and the water quality parameter of the target node is calculated to obtain the pipe water quality difference between the target node and the corresponding pipe.

[0058] ;

[0059] In the formula, represents the water quality difference of the pipe connected to the first node and the water quality difference of the pipe between the first node and the second node, The smaller the value of the water quality parameter, the smaller the difference in water quality. The smaller the value of the water quality parameter, the smaller the difference in water quality. The smaller the value of the water quality parameter, the smaller the difference in water quality. represents the number of types of water quality, represents the first water quality parameter in the pipe, represents the first water quality parameter at the first node.

[0060] To further optimize the selection of drainage paths, the case of multiple pipes between adjacent drainage nodes is considered. Specifically, the system determines which pipe is most matched in water quality with the drainage node by calculating the difference between the water quality parameters of the drainage node and the water quality parameters of each pipe, thereby selecting a more suitable discharge path. This process ensures that the selected path is closest to the drainage node in terms of water quality, thereby reducing the risk of pollutant diffusion when sewage is mixed and improving the suitability of discharge.

[0061] Selecting a pipe with the same water quality parameter as the drainage node as the discharge path can reduce the risk of pollutant diffusion when sewage is mixed and ensure the water quality stability of the discharge path. Selecting the most matched pipe can ensure that the sewage discharge path is closest to the drainage node in terms of water quality, thereby improving the suitability of discharge and reducing the cumbersome operation of subsequent sewage treatment. Specifically, selecting a pipe with the smallest water quality difference as the discharge path can effectively reduce the risk of pollutant diffusion and ensure stable operation of the system, while improving the operating efficiency of the entire sewage treatment system.

[0062] S3: According to the water quality difference at adjacent drainage nodes, the pipe water quality difference and the path distance, an exponential function is used for comprehensive evaluation to obtain a discharge suitability index.

[0063] In response to the existence of multiple direct-connection pipes between two drainage nodes, the negative exponential function is applied to the water quality difference, the product of the preset distance weight coefficient and the path distance, and the pipe water quality difference. The results are then multiplied, and the maximum value is selected as the discharge suitability index.

[0064] In response to the absence of multiple direct pipes between two drainage nodes, the product of water quality differences and the preset distance weighting coefficient with the path distance is processed using a negative exponential function and then multiplied to obtain the discharge suitability index.

[0065] If there is no direct connection between two drainage nodes, it means that the two drainage nodes cannot communicate with each other for drainage.

[0066] Specifically, the emission suitability index satisfies the following relationship:

[0067] ;

[0068] ;

[0069] In the formula, Indicates the first The node to the first The emission suitability index of each node, Indicates the first The node and the first Differences in water quality at each node for the same water quality parameters This represents the distance weighting coefficient, used for adjustment. The weighting is determined through calibration using historical data, with a value range of 0.001-0.01 and a default value of 0.002, balancing the effects of distance and water quality. Indicates the first The node and the first Path distance between nodes Indicates the relationship with the first The water quality differences in the pipes connected to each node are related to the first node. Differences in pipeline water quality parameters at individual nodes Represented by natural numbers An exponential function with base 0. This represents the maximum value function.

[0070] In other words, the most suitable discharge path is selected to improve wastewater treatment efficiency and reduce the risk of pollutant diffusion. The discharge path is dynamically adjusted based on real-time data to adapt to fluctuations in water quality and quantity. By selecting a suitable discharge path, the load balance of the drainage system can be achieved to avoid overload. By optimizing the discharge path, wastewater treatment costs can be reduced.

[0071] S4: fusing the real-time load rate and the emission suitability index to form a comprehensive dynamic weight, and using A The algorithm obtains the optimal path, and when multiple drainage nodes simultaneously discharge each optimal path, the path conflict is handled when multiple nodes are drained based on the comprehensive dynamic weight, so that the selection of the drainage path of the drainage network is realized.

[0072] A drainage network graph is established, wherein each drainage point is defined as a node in the graph, the pipeline connection between the drainage points is defined as an edge in the graph, the weight of each edge is determined based on the comprehensive dynamic weight, and A The starting point and the end point of the algorithm;

[0073] The comprehensive dynamic weight of each edge is used as a factor affecting the Euclidean distance to construct a heuristic function to estimate the shortest path cost from any node to the end point, and the optimal path is obtained.

[0074] In response to the fact that multiple paths pass through one or more same nodes at the same time, the cumulative comprehensive dynamic weight of the starting point of each path and the conflict node is calculated, the path corresponding to the maximum cumulative comprehensive weight is selected to pass through the conflict node first, the pipeline occupation is marked, the conflict node is removed from the available node set, and reassignment is performed, the emission suitability index and the comprehensive dynamic weight are recalculated, the path is replanned, and the efficiency and stability of the system operation are ensured.

[0075] The application further provides a sewage treatment intelligent monitoring system. Figure 2 As shown in the figure, the system comprises a processor and a memory, and the memory stores computer program instructions, which realize the sewage treatment intelligent monitoring method according to the first aspect of the application when executed by the processor. The system further comprises a communication bus, a communication interface and other components familiar to those skilled in the art, the settings and functions of which are known in the art, and therefore will not be described here.

[0076] It should be pointed out that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the application, which are all within the protection scope of the application. Therefore, the protection scope of the application patent should be subject to the appended claims.

Claims

1. A method for intelligent monitoring of wastewater treatment, characterized in that, include: The wastewater discharge volume parameters, water quality parameters, and drainage point coordinates at multiple rainwater collection and drainage nodes are obtained and pre-processed. The water quality parameters include node water quality parameters and pipeline water quality parameters. Based on the real-time sewage discharge and pipeline design maximum flow rate of each drainage point, analyze the real-time load rate of each drainage point, calculate the water quality difference of the same water quality parameters between adjacent drainage nodes, and the pipeline water quality difference between the node water quality parameters of the drainage node and the water quality parameters of the connected pipeline. Based on the coordinates of the drainage point, calculate the path distance between adjacent drainage nodes. An appropriate discharge index is obtained by comprehensively evaluating the differences in water quality at adjacent drainage nodes, differences in water quality in pipelines, and path distance using an exponential function. The calculation method for the emission suitability index includes: In response to the existence of multiple direct-connection pipes between two drainage nodes, the negative exponential function is applied to the water quality difference, the product of the preset distance weight coefficient and the path distance, and the pipe water quality difference. The results are then multiplied, and the maximum value is selected as the discharge suitability index. In response to the absence of multiple direct pipes between two drainage nodes, the product of water quality differences and the preset distance weighting coefficient with the path distance is processed using a negative exponential function and then multiplied to obtain the discharge suitability index. If there is no direct connection between two drainage nodes, it means that the two drainage nodes cannot communicate with each other for drainage. By integrating real-time load rate and emissions suitability index to form a comprehensive dynamic weight, A is used based on this comprehensive dynamic weight. The algorithm obtains the optimal path. In response to the conflict between the optimal paths when multiple drainage nodes discharge simultaneously, it handles the path conflict when multiple nodes discharge based on comprehensive dynamic weights, and realizes the selection of drainage path in the drainage network. Construct a drainage network diagram, where each drainage point is defined as a node in the diagram, and the pipe connections between drainage points are defined as edges. The weight of each edge is determined based on a comprehensive dynamic weight. Determine A. The start and end points of the algorithm; By using the combined dynamic weight of each edge as a factor affecting the Euclidean distance, a heuristic function is constructed to estimate the shortest path cost from any node to the destination and obtain the optimal path. In response to multiple paths passing through one or more of the same nodes simultaneously, the cumulative dynamic weight of the starting point of each path and the conflicting node is calculated. The path with the largest cumulative dynamic weight is selected to pass through the conflicting node first, and the pipeline is marked as occupied. The conflicting node is removed from the set of available nodes and redistributed. The emission suitability index and the cumulative dynamic weight are recalculated, and the path is replanned to ensure the efficiency and stability of the system operation.

2. The intelligent monitoring method for wastewater treatment according to claim 1, characterized in that, The calculation method for the real-time load rate includes: The product of the cross-sectional area of ​​the drainage pipe and the maximum allowable flow velocity is taken as the maximum flow rate of the pipe, and the ratio of the real-time sewage discharge to the maximum flow rate of the pipe is taken as the real-time load rate.

3. The intelligent monitoring method for wastewater treatment according to claim 1, characterized in that, The calculation of water quality differences with the same water quality parameters at adjacent drainage nodes includes: Taking any drainage node as the target node, obtain other nodes connected to the target node through water pipes, calculate the square root of the sum of squares of the differences in water quality parameters between the target node and other nodes, and obtain the water quality differences between the target node and other nodes.

4. The intelligent monitoring method for wastewater treatment according to claim 1, characterized in that, The differences in water quality in the pipeline include: Taking any drainage node as the target node, calculate the square root of the sum of the squares of the differences between the water quality parameters of the pipes connected to the target node and the water quality parameters of the target node, and obtain the pipe water quality difference between the target node and the corresponding pipe.

5. A wastewater treatment intelligent monitoring system, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement the intelligent monitoring method for wastewater treatment according to any one of claims 1-4.

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