River pollution treatment equipment control operation system and method

Abstract

The application discloses a kind of river pollution control equipment control operation systems, for the operation control of pollution control equipment in river pollution treatment, including water quality pollution parameter index detection system, industrial internet and river pollution working point, the water quality pollution parameter index detection system and river pollution working point are set to multiple points, the industrial internet includes center server, the center server can collect and summarize the detection data of water quality pollution parameter index detection system, the center server can simultaneously start-stop control operation to each pollution control equipment;The application analyzes and judges pollution condition according to river basin pollution control standard, establishes monitoring and management quick response mechanism, timely handles the occurrence of pollution accident, obtains the pollution control efficiency and the pollution control cost synergic optimal pollution control equipment control operation scheme, to realize the unmanned intelligent control of pollution control equipment with high efficiency and low cost strategy, avoid river pollution accident expansion, reduce pollution accident loss.

Description

Technical Field

[0001] This invention relates to the field of intelligent management of river basin pollution control, specifically to a control and operation system and method for river pollution control equipment. Background Technology

[0002] With the vigorous development of society, urban economies have prospered and businesses have flourished. However, these urban economic activities have also led to the discharge of large amounts of domestic and industrial wastewater into urban rivers, causing serious pollution problems in the river basin environment. In order to keep the river basin water environment free from pollution, the government has increased its efforts to control the water quality discharged into the river basin, especially strictly controlling the water pollution parameters of fluids discharged into small and medium-sized rivers.

[0003] However, due to the presence of various types of outfalls along urban rivers, such as municipal sewage treatment plant outfalls, stormwater outfalls, and combined sewer outfalls, as well as some illegally connected, old outfalls whose sources cannot be traced, some of these outfalls discharge untreated water into urban rivers. Furthermore, while some outfalls are classified as stormwater outfalls, the inadequate separation systems along the riverbanks often result in the mixing of highly polluting wastewater, including high-silt wastewater, surface runoff, and restaurant wastewater.

[0004] Meanwhile, because urban rivers are often modified into hardened channels to effectively discharge floodwaters, their ecosystems are often incomplete, and their self-purification capacity is weak. If the sewage discharged from these outlets is not treated in a timely manner, it will cause enormous pollution to the water bodies throughout the urban rivers, dealing a devastating blow to the already fragile river ecosystems. At this point, a systematic water environment remediation is necessary to restore the polluted urban rivers to their original unpolluted state. This process requires a significant investment of human, material, time, and financial resources.

[0005] In the process of urban river pollution control, various physical and chemical treatment systems are often installed at high-risk discharge outlets in urban rivers to enable timely on-site treatment of polluted water when pollution occurs, effectively eliminating pollution and maintaining river water quality standards. However, due to the long length of the river channels, the numerous discharge outlets, and the large number of pollution control devices, each with different processes and efficiencies, maintenance costs become very high. Each discharge outlet / node requires manual inspection, equipment start-up and shutdown, and maintenance, which is not only inefficient but also extremely costly.

[0006] Therefore, it is necessary to establish a river pollution control equipment control and operation system based on the Industrial Internet to control multiple pollution control devices installed in the river based on water quality pollution parameter monitoring data, and to promptly handle pollution incidents in small and medium-sized rivers. Simultaneously, it is also necessary to find the optimal pollution control equipment control and operation method that achieves the best synergy between pollution control efficiency and cost during the operation of the river pollution control equipment control and operation system, thus obtaining the optimal pollution control equipment control and operation scheme in terms of both efficiency and cost. Summary of the Invention

[0007] The purpose of this invention is to provide a control and operation system and method for river pollution control equipment, in order to solve the technical problems of low pollution control efficiency and high operating costs in the process of urban river pollution control, where there are many pollution control devices set up at multiple outlets / nodes, with different processes and different pollution control efficiencies, all of which require manual maintenance.

[0008] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0009] In a first aspect, this invention discloses a river pollution control equipment control and operation system, including a water quality pollution parameter index detection system, an industrial internet, and river pollution control work points. The water quality pollution parameter index detection system and river pollution control work points are set up at multiple locations. The industrial internet includes a central server, which is equipped with a pollution control standard level assessment module, a pollution control equipment control and operation analysis module, an equipment remote control module, and a standard database. The pollution control standard level assessment module is used to match the water quality pollution parameter monitoring indicators measured by the water quality pollution parameter index detection system with the water quality pollution parameter monitoring indicator limits given in the standard database, and to determine the pollution control standard level. The pollution control equipment control and operation analysis module is used to output different pollution control equipment control and operation schemes according to the pollution control standard level. The equipment remote control module is used to perform start-stop control operations on the river pollution control work points according to the pollution control equipment control and operation schemes.

[0010] The river pollution control equipment control and operation system can continuously monitor river sections in different environments within a specific watershed, achieving real-time monitoring, data transmission, and remote control. This allows monitoring personnel to quickly respond to any anomalies and take timely remedial measures, effectively reducing the occurrence and impact of pollution incidents. It also facilitates more convenient monitoring and management of river water quality, improves pollution early warning capabilities, and ensures that river water pollution conditions are promptly identified for rapid response.

[0011] Preferably, the water quality pollution parameter detection system includes a sampling system, a measurement system, and a data transmission system. The sampling system includes a sampling pump, a sampling pipeline, a dedicated sampler, and a sampling control unit. The inlet and outlet of the sampling pump are respectively connected to the sampling pipeline and the dedicated sampler. The sampling control unit is used to control the start and stop of the sampling pump. The measurement system includes an online COD analyzer, an online ammonia nitrogen analyzer, an online total phosphorus analyzer, and an online heavy metal monitor. The data transmission system includes a data acquisition terminal and a communication module. The data acquisition terminal is used to collect water quality pollution parameter monitoring data measured by the measurement system. The communication module uses an Ethernet, 4G, or 5G wireless network module to communicate with the central server and transmit the water quality pollution parameter monitoring data collected in the data acquisition terminal to the central server of the industrial internet.

[0012] Specifically, the sampling process is as follows: the sampling control unit controls the sampling pump to pump the water sample into the dedicated sampler through the sampling pipeline to complete the sampling process. Then, the sample in the dedicated sampler enters each measurement system for online detection. Finally, the measurement results are summarized by the data acquisition terminal and sent to the central server through the communication module.

[0013] Preferably, the river pollution control work site is equipped with a physical treatment system and a chemical treatment system. The physical treatment system includes reoxygenation equipment or water replenishment equipment, and the chemical treatment system includes a reagent addition device. The river pollution control work site is also equipped with an intelligent equipment control module. The intelligent equipment control module can receive control commands from a central server and report the operating status of the physical treatment system and the chemical treatment system to the central server. The intelligent equipment control module is electrically connected to the reoxygenation equipment, water replenishment equipment, and reagent addition device, respectively, and is used to remotely control the start and stop of the reoxygenation equipment, water replenishment equipment, and reagent addition device.

[0014] Secondly, this invention discloses a method for controlling and operating river pollution control equipment, which can solve the technical problem that the coordination effect between various pollution control devices is poor when using the above-mentioned river pollution control equipment control and operation system, resulting in low pollution treatment efficiency and high operating costs. It is used for the operation control of pollution control equipment in river basin pollution control, and includes the following steps:

[0015] S1. Construct an analysis model for the control and operation of pollution control equipment, establish the correlation between pollution control standard levels and the corresponding control and operation of pollution control equipment, and be able to output different control and operation schemes for pollution control equipment according to different pollution control standard levels.

[0016] S2. Monitor water quality pollution parameters at each measurement point, and have the data collected and analyzed by the central server to assess the pollution control standard level.

[0017] S3. Based on the assessed pollution control standard level, match it with the pollution control equipment control and operation scheme in the pollution control equipment control and operation analysis model to obtain the pollution control equipment control and operation scheme.

[0018] S4. The central server performs start-stop control operations on each pollution control device according to the pollution control equipment control operation plan obtained in step S3.

[0019] Preferably, step S1, which involves constructing the control and operation analysis model for the pollution control equipment, specifically includes the following steps:

[0020] S1.1 Define the control and operation objectives of the pollution control equipment, namely, to achieve high pollution control efficiency and low pollution control cost while maintaining water quality standards.

[0021] S1.2 Collect data related to various water quality pollution parameters and monitoring indicators at various measurement points in the target river and transmit them to the central server;

[0022] S1.3 Preprocess the collected data to improve data quality and accuracy;

[0023] S1.4 Based on the decision tree model, according to the pollution control standard level, different water quality pollution parameter monitoring indicators are used as root nodes, the corresponding water quality pollution parameter monitoring indicator limits are used as internal nodes, and the attributes of the corresponding pollution control equipment are used as leaf nodes to construct the basic model.

[0024] S1.5. Collect the measured values ​​of multiple sets of water quality pollution parameter monitoring indicators and transmit them to the central server. The central server uses the measured values ​​of multiple sets of water quality pollution parameter monitoring indicators to verify and evaluate the basic model constructed in step S1.4.

[0025] S1.6. The information gain algorithm is used to optimize the basic model. The model path with high pollution control efficiency and low pollution control cost is selected as the selected pollution control equipment control and operation scheme to obtain the optimized model.

[0026] S1.7. For the optimized model in step S1.6, the optimized model is further verified and evaluated by using the measured values ​​of multiple sets of water pollution parameter monitoring indicators. OEE accounting is then used to further improve and optimize the model, and finally, the optimal pollution control equipment control and operation scheme with the best synergy between pollution control efficiency and pollution control cost corresponding to different water pollution parameter monitoring indicators is obtained.

[0027] Preferably, in step S1.3, the collected data is preprocessed, including data cleaning, missing value handling, outlier detection, and noise reduction.

[0028] Preferably, in step S1.4, the attributes of the pollution control equipment include the on / off status, cost, efficiency, etc.

[0029] As a preferred option, in step S1.6, the pollution control efficiency and pollution control cost of each type of pollution control equipment are first calculated, the information gain of the start-up path of each type of pollution control equipment is calculated, and the model path with the larger information gain is taken as the model path after the pollution control efficiency and pollution control cost are jointly optimized, so as to obtain the optimized pollution control equipment control operation scheme.

[0030] As a preferred option, in step S1.7, the optimized model is verified and evaluated by measuring the values ​​of multiple sets of water pollution parameter monitoring indicators. The model path with the largest information gain is selected as the model path with the optimal synergy between pollution control efficiency and pollution control cost. This yields the pollution control equipment control and operation schemes with the optimal synergy between pollution control efficiency and pollution control cost for different pollution control standard levels.

[0031] As a preferred option, in step S2, a linkage alarm threshold is set. When the water quality pollution parameters of each measuring point are monitored and the data is collected and analyzed by the central server to assess the pollution control standard level, if the assessed pollution control standard level exceeds the linkage alarm threshold, the central server will output alarm information and save it.

[0032] This invention offers the following advantages: The river pollution control equipment control and operation system and method disclosed herein are used for the operation control of pollution control equipment in river basin pollution management. Based on the river basin pollution control level standards, it analyzes and judges the pollution status, establishes a rapid response mechanism for monitoring and treatment, and promptly handles pollution accidents. It obtains a pollution control equipment control and operation scheme with optimal synergy between pollution control efficiency and cost, achieving unmanned intelligent control of pollution control equipment with a high-efficiency and low-cost strategy, preventing the escalation of river pollution accidents and reducing pollution accident losses. Based on the data processing capabilities of the industrial internet's big data platform, this invention utilizes connected online hydrological and water quality monitoring equipment for data collection. Combined with monitoring indicators of different water quality pollution parameters, and through a pollution control equipment control and operation analysis model, it outputs a pollution control equipment control and operation scheme with optimal synergy between pollution control efficiency and cost based on different levels of exceedance of pollution control standards. This achieves fully intelligent management of pollution control equipment, reduces costs, and improves pollution control efficiency. Attached Figure Description

[0033] To make the objectives, technical solutions, and advantages of the invention clearer, the invention will now be described in further detail with reference to the accompanying drawings, wherein:

[0034] Figure 1 This is a schematic diagram of the control and operation method of the river pollution control equipment of the present invention.

[0035] Figure 2 This is a schematic diagram of the composition and structure of the river pollution control equipment control and operation system used in this embodiment of the invention.

[0036] Figure 3 This is a flowchart illustrating the operation process of the river pollution control equipment control system in an embodiment of the present invention.

[0037] Figure 4 This is a schematic diagram of the basic decision tree model constructed using COD as an example in an embodiment of the present invention.

[0038] Figure 5 This is a schematic diagram of a model optimized using the measured values ​​of multiple water pollution parameters, with COD as an example, in an embodiment of the present invention.

[0039] Figure 6 This is a schematic diagram of the model optimized using the information gain algorithm, constructed using COD as an example in an embodiment of the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0041] It should be noted that similar reference numerals and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the figures, or the orientation or positional relationship commonly used when the product is in use. They are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance. In addition, the terms "horizontal," "vertical," etc., do not indicate that the component is required to be absolutely horizontal or suspended, but can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted. In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0042] This invention can be applied to the environmental governance and water purification industries, mainly targeting river basin pollution control based on the Industrial Internet, especially dynamic water pollution control in small and medium-sized river basins. It improves the methods of linkage and joint control of pollution control equipment based on the Industrial Internet, in order to achieve pollution control results while maintaining low operating costs, thus achieving the technical effect of cost reduction and efficiency improvement.

[0043] This invention solves the technical problem in the prior art of urban river pollution control, where the large number of pollution control devices at multiple outlets / nodes, with different processes and varying pollution control efficiencies, all require manual maintenance, resulting in low pollution treatment efficiency and high operating costs.

[0044] In a first aspect, this invention discloses a river pollution control equipment control and operation system, including a water quality pollution parameter index detection system, an industrial internet, and river pollution control work points. The water quality pollution parameter index detection system and river pollution control work points are set up at multiple locations. The industrial internet includes a central server, which is equipped with a pollution control standard level assessment module, a pollution control equipment control and operation analysis module, an equipment remote control module, and a standard database. The pollution control standard level assessment module is used to match the water quality pollution parameter monitoring indicators measured by the water quality pollution parameter index detection system with the water quality pollution parameter monitoring indicator limits given in the standard database, and to determine the pollution control standard level. The pollution control equipment control and operation analysis module is used to output different pollution control equipment control and operation schemes according to the pollution control standard level. The equipment remote control module is used to perform start-stop control operations on the river pollution control work points according to the pollution control equipment control and operation schemes.

[0045] The river pollution control equipment control and operation system can continuously monitor river sections in different environments within a specific watershed, achieving real-time monitoring, data transmission, and remote control. This allows monitoring personnel to quickly respond to any anomalies and take timely remedial measures, effectively reducing the occurrence and impact of pollution incidents. It also facilitates more convenient monitoring and management of river water quality, improves pollution early warning capabilities, and ensures that river water pollution conditions are promptly identified for rapid response.

[0046] Preferably, the water quality pollution parameter detection system includes a sampling system, a measurement system, and a data transmission system. The sampling system includes a sampling pump, a sampling pipeline, a dedicated sampler, and a sampling control unit. The inlet and outlet of the sampling pump are respectively connected to the sampling pipeline and the dedicated sampler. The sampling control unit is used to control the start and stop of the sampling pump. The measurement system includes an online COD analyzer, an online ammonia nitrogen analyzer, an online total phosphorus analyzer, and an online heavy metal monitor. The data transmission system includes a data acquisition terminal and a communication module. The data acquisition terminal is used to collect water quality pollution parameter monitoring data measured by the measurement system. The communication module uses an Ethernet, 4G, or 5G wireless network module to communicate with the central server and transmit the water quality pollution parameter monitoring data collected in the data acquisition terminal to the central server of the industrial internet.

[0047] Specifically, the sampling process is as follows: the sampling control unit controls the sampling pump to pump the water sample into the dedicated sampler through the sampling pipeline to complete the sampling process. Then, the sample in the dedicated sampler enters each measurement system for online detection. Finally, the measurement results are summarized by the data acquisition terminal and sent to the central server through the communication module.

[0048] Preferably, the river pollution control work site is equipped with a physical treatment system and a chemical treatment system. The physical treatment system includes reoxygenation equipment or water replenishment equipment, and the chemical treatment system includes a reagent addition device. The river pollution control work site is also equipped with an intelligent equipment control module. The intelligent equipment control module can receive control commands from a central server and report the operating status of the physical treatment system and the chemical treatment system to the central server. The intelligent equipment control module is electrically connected to the reoxygenation equipment, water replenishment equipment, and reagent addition device, respectively, and is used to remotely control the start and stop of the reoxygenation equipment, water replenishment equipment, and reagent addition device.

[0049] Specifically, the chemical treatment system includes a water pump, a mixing tank, a reagent dosing device, a stirring device, and a drainage pipe. The water pump draws polluted river water into the mixing tank, the reagent dosing device adds reagents to the mixing tank, the stirring device mixes the reagents with the river water, and the drainage pipe discharges the treated river water from the mixing tank back into the river. By introducing various chemical agents into the polluted river section, this method has advantages such as rapid treatment speed, short treatment cycle, and significant effects, but the treatment cost is relatively high. This equipment is suitable for situations where total phosphorus, turbidity, or heavy metals exceed standards.

[0050] Specifically, the remote control module, distributed control system module, programmable logic controller, and remote terminal unit control module, combined with the central server, can automatically determine the occurrence of pollution and autonomously carry out pollution control, ensuring that the water quality pollution parameters monitoring indicators in the river basin meet the water quality management goals of the river basin, eliminating pollution in a timely manner, preventing the expansion of river pollution accidents, and reducing the losses from pollution accidents.

[0051] Specifically, for example, if COD or ammonia nitrogen levels in a river exceed standards, or dissolved oxygen levels decrease, it is necessary to activate reoxygenation equipment and / or water replenishment equipment, i.e., a physical treatment system. The reoxygenation equipment includes oxygen generators, aeration machines, aeration tanks, high-pressure blowers, wave generators, and propeller-type aeration devices. By artificially oxygenating rivers in anoxic or anaerobic conditions, the river's self-purification capacity is enhanced, water quality is improved, and the river's ecological environment is improved or restored. This equipment is suitable for situations where COD or ammonia nitrogen levels exceed standards, or where dissolved oxygen is insufficient. A commonly used aeration method for rivers is high-pressure blower aeration. The principle of blower aeration is to send compressed air through a pipeline system to an air diffuser at the bottom of the river, where it diffuses into the fluid in the form of bubbles, causing the oxygen in the bubbles to rapidly transfer to the liquid phase for the microorganisms to use.

[0052] Rivers with excessive COD or ammonia nitrogen levels provide excessive nutrients for microorganisms and algae, leading to their proliferation. This, in turn, consumes large amounts of oxygen, resulting in oxygen deficiency and low dissolved oxygen levels in the polluted water, creating an anaerobic (or hypoxic) state. Reoxygenation equipment can reoxygenate river water, enhancing the river's self-purification capacity, improving water quality, and restoring the river's ecological environment. Reoxygenation equipment has a simple process, relatively low cost, and no secondary pollution.

[0053] If total phosphorus, turbidity, or heavy metal levels exceed the standards, the contaminated water must be pumped out of the river and treated with chemical agents for flocculation and sedimentation until it meets the standards before being discharged back into the river. This necessitates the activation of a chemical treatment system. The chemical treatment system includes various agent dispensers, automatic mixing pumps, mixing and agitating devices, and a pipeline system. It can continuously and dynamically dispense chemical agents onto the river cross-section to chemically treat the river fluid and promptly address river pollution.

[0054] According to the pollution control equipment control and operation plan, these devices are managed through a remote monitoring and control system based on the Internet of Things (IoT). Specifically, control systems such as DCS (Distributed Control System), PLC (Programmable Logic Controller), and RTU (Remote Terminal Unit) are used to remotely control the physical and chemical treatment systems set up within the watershed. This enables automatic detection of pollution occurrence and autonomous pollution remediation, ensuring that the water quality pollution parameters monitored within the river basin meet the water quality treatment targets of the river basin, eliminating pollution in a timely manner, preventing the escalation of river pollution incidents, and reducing the losses from pollution incidents.

[0055] Among them, IoT remote monitoring and control systems refer to the use of Internet of Things (IoT) technology to remotely monitor and control pollution control equipment. DCS is a control system used for real-time control and monitoring of complex industrial processes. A distributed control system consists of multiple controllers located in different locations, interconnected via a communication network. Each controller is responsible for controlling and monitoring a specific piece of equipment or process area. The DCS system centrally processes and manages data from multiple controllers and provides an operator interface, data logging, and alarm functions.

[0056] A Programmable Logic Controller (PLC) is a specialized control device designed for industrial automation systems. Based on a programmable logic controller, it controls inputs and outputs according to pre-written logic programs. PLCs are typically used to control discrete processes, such as machine operation, assembly line control, and safety systems. PLCs offer high reliability, real-time performance, and flexibility, managing multiple input and output devices and communicating and controlling via digital or analog signals.

[0057] An Remote Control Unit (RTU) is a device used for remote monitoring and control, typically in distributed or remote unattended industrial environments. An RTU integrates data acquisition, processing, storage, and communication functions. It can acquire data from sensors, instruments, and other devices and transmit the data to a central control center for monitoring and analysis. RTUs usually have multiple communication interfaces, such as serial ports, Ethernet, and Modbus, for communicating with various devices and systems.

[0058] However, in the process of river pollution control based on the Industrial Internet, the coordinated control of various pollution control devices in the river pollution control equipment operation system sometimes results in high efficiency and high cost. For example, if water pollution is detected at the same monitoring point in the same river, and multiple pollution control devices at that point are turned on simultaneously, it will lead to resource waste and high costs. Another example is that water pollution, specifically COD exceeding the standard, is detected at a monitoring point in a river, but it is difficult to determine the start time or power of the physical treatment system based on the COD measurement value. This may lead to technical problems such as low pollution control efficiency and incomplete pollution elimination.

[0059] Secondly, please refer to Figure 1 The present invention also discloses a method for controlling and operating river pollution control equipment, used for the operation control of pollution control equipment in river basin pollution control. This method solves the technical problem that when using the above-mentioned river pollution control equipment control and operation system, the coordination effect between various pollution control devices is poor, leading to low pollution treatment efficiency and high operating costs. The method includes the following steps:

[0060] S1. Construct an analysis model for the control and operation of pollution control equipment, establish the correlation between pollution control standard levels and the corresponding control and operation of pollution control equipment, and be able to output different control and operation schemes for pollution control equipment according to different pollution control standard levels.

[0061] S2. Monitor water quality pollution parameters at each measurement point, and have the data collected and analyzed by the central server to assess the pollution control standard level.

[0062] S3. Based on the assessed pollution control standard level, match it with the pollution control equipment control and operation scheme in the pollution control equipment control and operation analysis model to obtain the pollution control equipment control and operation scheme.

[0063] S4. The central server performs start-stop control operations on each pollution control device according to the pollution control equipment control operation plan obtained in step S3.

[0064] Specifically, in step S1, the pollution control standard level is determined based on relevant national standards, and the monitoring indicators for each water quality pollution parameter are refined, serving as the standard for the central server to evaluate the pollution control standard level. The specific relevant national standard is the "Surface Water Environmental Quality Standard" (GB3838-2002), and the limit values ​​for each water quality pollution parameter monitoring indicator are shown in Table 1.

[0065] Table 1. Surface Water Environmental Quality Standard (GB3838-2002) (Unit: mg / L)

[0066]

[0067]

[0068] Table 1 shows the monitoring indicators for various water pollution parameters related to river pollution, including chemical oxygen demand (COD), pH value, ammonia nitrogen (NH3-N), total phosphorus (P), dissolved oxygen (DO), copper, zinc, cadmium, hexavalent chromium, and lead. Among these, copper, zinc, cadmium, hexavalent chromium, and lead are all heavy metal water pollution parameters.

[0069] According to Table 1, the first row shows Class I, Class II, Class III, Class IV, and Class V as pollution control standard levels. Each level corresponds to a suitable pollution control equipment control and operation plan. It is necessary to control and operate the pollution control equipment based on the inherent treatment mechanism of the pollution control equipment for each different water quality pollution parameter monitoring index to ensure that the water quality pollution parameter monitoring index of the water body in the river basin meets the treatment target of the river basin.

[0070] Specifically, in step S2, water pollution parameters are monitored by various online hydrological and water quality monitoring devices at multiple points along the river basin. All devices operate in an unmanned, automated mode and are distributed across key monitoring nodes along the river, such as river dam outlets, gorges, sewage outlets, tributary confluences, municipal sewage treatment plant outlets, sluice gates, administrative district river outlets, and riverbanks. Simultaneously, the central server collects real-time data on water pollution parameters and controls the start / stop of each online hydrological and water quality monitoring device, monitoring its operational status.

[0071] Preferably, step S1, which involves constructing the control and operation analysis model for the pollution control equipment, specifically includes the following steps:

[0072] S1.1 Define the control and operation objectives of the pollution control equipment, namely, to achieve high pollution control efficiency and low pollution control cost while maintaining water quality standards.

[0073] S1.2 Collect data related to various water quality pollution parameters and monitoring indicators at various measurement points in the target river and transmit them to the central server;

[0074] S1.3 Preprocess the collected data to improve data quality and accuracy;

[0075] S1.4 Based on the decision tree model, according to the pollution control standard level, different water quality pollution parameter monitoring indicators are used as root nodes, the corresponding water quality pollution parameter monitoring indicator limits are used as internal nodes, and the attributes of the corresponding pollution control equipment are used as leaf nodes to construct the basic model.

[0076] S1.5. Collect the measured values ​​of multiple sets of water quality pollution parameter monitoring indicators and transmit them to the central server. The central server uses the measured values ​​of multiple sets of water quality pollution parameter monitoring indicators to verify and evaluate the basic model constructed in step S1.4.

[0077] S1.6. The information gain algorithm is used to optimize the basic model. The model path with high pollution control efficiency and low pollution control cost is selected as the selected pollution control equipment control and operation scheme to obtain the optimized model.

[0078] S1.7. For the optimized model in step S1.6, the optimized model is further verified and evaluated by using the measured values ​​of multiple sets of water pollution parameter monitoring indicators. OEE accounting is then used to further improve and optimize the model, and finally, the optimal pollution control equipment control and operation scheme with the best synergy between pollution control efficiency and pollution control cost corresponding to different water pollution parameter monitoring indicators is obtained.

[0079] Specifically, in step S1.3, the collected data is preprocessed, including data cleaning, missing value handling, outlier detection, and noise reduction.

[0080] Specifically, in step S1.4, a decision tree is a basic classification and regression method. Based on the known probabilities of various scenarios, it constructs a decision tree to calculate the probability that the expected net present value is greater than or equal to zero, evaluating project risk and determining its feasibility. It's a graphical method that intuitively applies probability analysis. The decision tree model has a tree-like structure. The main idea of ​​the decision tree algorithm is to select the best features from the dataset, dividing the dataset into smaller subsets until a predefined stopping condition is reached. At each node, the feature that minimizes the impurity of the current dataset is selected for partitioning. Commonly used impurity metrics include information gain, Gini index, and gain ratio. The structure of a decision tree is similar to the human decision-making process, making it easy to understand and visualize. It can handle multi-class classification problems and is effective for imbalanced datasets. It can also handle numerical and discrete features, requires minimal data preprocessing, and can handle missing values ​​without imputation.

[0081] In classification problems, a decision tree represents the process of classifying instances based on features. A decision tree mainly contains three types of nodes: the root node (also called the initial node), internal nodes, and leaf nodes. In a decision tree, if the features of a sample are consistent with the features on the path or the instance satisfies the conditions of the rules, then each sample will only be covered by one path.

[0082] Specifically, in step S1.4, the attributes of the pollution control equipment include the on / off status, cost, and efficiency of the pollution control equipment.

[0083] In step S1.5, the base model is validated and its performance and generalization ability are evaluated in this way, which ensures that the base model can run effectively in the real environment.

[0084] Specifically, in step S1.6, for the same water pollution parameter monitoring indicator, starting different equipment for pollution control is highly related to pollution control efficiency and pollution control cost. Therefore, by calculating the information gain of different equipment starting paths as the model path with the best synergy between pollution control efficiency and pollution control cost, the optimal pollution control equipment control and operation scheme can be obtained.

[0085] Specifically, in step S1.6, the pollution control efficiency and pollution control cost of each type of pollution control equipment are first calculated, the information gain of the start-up path of each type of pollution control equipment is calculated, and the model path with the larger information gain is taken as the model path after the pollution control efficiency and pollution control cost are jointly optimized, so as to obtain the optimized pollution control equipment control operation scheme.

[0086] Specifically, the information gain of each pollution control equipment startup path is calculated using the following method: Utilizing the information gain of the decision tree, i.e. the reduction in information entropy, the optimal pollution control equipment control and operation scheme is calculated under different water quality pollution parameter monitoring indicators using the following formula. This means that the pollution control cost should be low while also having high pollution control efficiency.

[0087] Suppose feature a has N possible values ​​{a1, a2, ..., a...} N If feature 'a' is used to partition the sample set D, N branch nodes will be generated. Each branch node contains all samples in the sample set D that have a value of 'a' on feature 'a'. n The sample is denoted as D. n Where n∈{1,2,...,N}, the new information entropy newEntropy(D) of the sample set D is the N information entropies Entropy(D) after partitioning based on feature a. n The weighted sum of ) is shown in equation (1).

[0088]

[0089] The information gain Gain(D,a) obtained by partitioning the sample set D with feature a is shown in equation (2):

[0090]

[0091] Where Entropy(D) is the original information entropy of the sample set D, and newEntropy(D) is the new information entropy of the sample set D. n ) is the information entropy of each branch node in the sample set D, where n∈{1,2,...,N} and N is the number of branch nodes.

[0092] Information gain is used to select the optimal feature for splitting a dataset. If splitting samples using a certain feature results in a decrease in the information entropy of the resulting subsets, it indicates that the subsets are purer, meaning their impurity is reduced. Information entropy is a measure of the purity or uncertainty of a dataset. Information entropy is lowest and dataset purity is highest when all samples in a dataset belong to the same category. Conversely, information entropy is highest and dataset purity is lowest when samples are evenly distributed across categories. Decision tree algorithms select the optimal feature to split datasets, aiming to make samples in subsets as similar as possible to belong to the same category, thereby reducing the dataset's impurity or information entropy. When splitting samples using a certain feature, a decrease in the information entropy of the resulting subsets means a reduction in impurity, as the subsets become purer. Therefore, a higher information gain indicates increased purity and reduced impurity after splitting using a particular feature. The minimum information entropy indicates that the pollution control operation scheme using that feature achieves optimal pollution control efficiency and cost.

[0093] Specifically, in step S1.7, the optimized model is verified and evaluated by measuring the values ​​of multiple sets of water pollution parameter monitoring indicators. The model path with the largest information gain is selected as the model path with the optimal synergy between pollution control efficiency and pollution control cost. The pollution control equipment control and operation schemes with the optimal synergy between pollution control efficiency and pollution control cost corresponding to different pollution control standard levels are obtained.

[0094] As a preferred option, in step S2, a linkage alarm threshold is set. When the water quality pollution parameters of each measuring point are monitored and the data is collected and analyzed by the central server to assess the pollution control standard level, if the assessed pollution control standard level exceeds the linkage alarm threshold, the central server will output alarm information and save it.

[0095] The working principle of this invention is that, for pollution control at the same pollution control standard level, different equipment can be controlled to treat the pollution based on the different exceedance of various water pollution parameters. However, their treatment efficiency and cost are different. Based on the decision tree model and using the information gain algorithm to optimize the basic model, the control and operation scheme of the pollution control equipment can be optimized to obtain the model path with optimal synergy between treatment efficiency and treatment cost, that is, to obtain the pollution control equipment control and operation scheme with optimal synergy between treatment efficiency and treatment cost.

[0096] The river pollution control equipment control and operation system and method disclosed in this invention have the following technical effects: Based on the river basin pollution control level standards, this invention analyzes and judges the pollution status, establishes a rapid response mechanism for monitoring and treatment, and promptly handles pollution accidents. It achieves unmanned intelligent control of pollution control equipment with a high-efficiency and low-cost strategy, ensuring that the water quality pollution parameters in the river basin are within the range of national environmental protection standards, avoiding the expansion of river pollution accidents, and reducing pollution accident losses.

[0097] This invention leverages the data processing capabilities of a big data platform based on the Industrial Internet. By utilizing connected online hydrological and water quality monitoring equipment, it collects data and combines it with monitoring indicators of different water pollution parameters. Through a pollution control equipment control and operation analysis model, it outputs the optimal pollution control equipment control and operation scheme that balances pollution control efficiency and cost based on different levels of pollution exceeding the control standard. This achieves fully intelligent management of pollution control equipment, reduces costs, and improves pollution control efficiency.

[0098] To further illustrate the river pollution control equipment control and operation system and method of the present invention, the following embodiments are disclosed.

[0099] Example

[0100] This embodiment uses the treatment of pollution at the level of excessive COD (Chemical Oxygen Demand) in a river as an example to elaborate on the river pollution control equipment control and operation system and method disclosed in this invention. Other water quality pollution parameters are monitored in a similar manner. By employing the above-mentioned river pollution control equipment control and operation system and method, this embodiment can solve the technical problem in the prior art of poor synergy between various pollution control devices in the process of river basin pollution control based on the Industrial Internet, resulting in low pollution treatment efficiency and high operating costs.

[0101] In this embodiment, the water quality control level of the river basin is Class IV. According to the national standard "Surface Water Environmental Quality Standard" (GB3838-2002), the monitoring limits for various water pollution parameters of Class IV water bodies are shown in Table 1. Table 1 lists the monitoring indicators for various water pollution parameters related to river pollution, including Chemical Oxygen Demand (COD), pH value, ammonia nitrogen (NH3-N), total phosphorus (P), dissolved oxygen (DO), copper, zinc, cadmium, hexavalent chromium, and lead. Among these, copper, zinc, cadmium, hexavalent chromium, and lead are all heavy metal water pollution parameters. The corresponding pollution indicators at each monitoring point within the river basin must not exceed the standard limits. If they exceed these limits, it indicates that the river fluid pollution is exceeding the standards, and physical and chemical treatment systems need to be activated promptly for pollution control.

[0102] This embodiment uses a river pollution control and operation system to monitor water quality pollution parameters of a certain river. The river pollution control and operation system includes hydrological and water quality monitoring equipment, industrial internet, and river pollution control work points. The pollution control equipment is installed in the river pollution control work points. The river pollution control and operation system communicates data through Ethernet communication technology or 4G / 5G wireless communication technology.

[0103] River pollution control sites include various physical and chemical treatment systems and are the equipment used for river pollution control. They are mainly distributed on the land along the banks of rivers such as river outlets, gorges, sewage outlets, tributary confluences, municipal sewage treatment plant outlets, sluice gates, river outlets within administrative districts, and river beaches.

[0104] Please see Figure 2 The river pollution control and operation system used in this embodiment includes a water quality pollution parameter index detection system, an industrial internet, and river pollution control work points. The water quality pollution parameter index detection system and river pollution control work points are set up at multiple points.

[0105] The water quality pollution parameter detection system includes a sampling system, a measurement system, and a data transmission system. The sampling system includes a sampling pump, sampling pipeline, a dedicated sampler, and a sampling control unit. The inlet and outlet of the sampling pump are connected to the sampling pipeline and the dedicated sampler, respectively. The sampling control unit controls the start and stop of the sampling pump. The measurement system includes an online COD analyzer, an online ammonia nitrogen analyzer, an online total phosphorus analyzer, and an online heavy metal monitor. The data transmission system includes a data acquisition terminal and a communication module. The data acquisition terminal collects water quality pollution parameter monitoring data measured by the measurement system. The communication module uses an Ethernet, 4G, or 5G wireless network module to communicate with the central server, transmitting the water quality pollution parameter monitoring data collected by the data acquisition terminal to the central server of the industrial internet. Specifically, the sampling process is as follows: the sampling control unit controls the sampling pump to pump the water sample to the dedicated sampler through the sampling pipeline, completing the sampling process. Then, the sample in the dedicated sampler enters each measurement system for online detection. Finally, the measurement results are summarized by the data acquisition terminal and sent to the central server through the communication module.

[0106] The river pollution control site is equipped with a physical treatment system and a chemical treatment system. The physical treatment system includes reoxygenation equipment or water replenishment equipment, and the chemical treatment system includes a reagent addition device. The river pollution control site is also equipped with an intelligent equipment control module. The intelligent equipment control module can receive control commands from the central server and report the operating status of the physical treatment system and the chemical treatment system back to the central server. The intelligent equipment control module is electrically connected to the reoxygenation equipment, water replenishment equipment, and reagent addition device, respectively, and is used to remotely control the start and stop of the reoxygenation equipment, water replenishment equipment, and reagent addition device.

[0107] The physical treatment system used in this embodiment consists of a reoxygenation device and a water replenishment device. The reoxygenation device uses a riverbed aeration system and a floating aerator, while the water replenishment device uses qualified water to supplement the river water.

[0108] The main equipment of the riverbed aeration system used in this embodiment is a high-pressure blower aeration device, which can send compressed air through a pipeline system into the air diffusion device at the bottom of the river, and diffuse it into the fluid in the form of bubbles, so that the oxygen in the bubbles can be quickly transferred to the liquid phase to meet the needs of microorganisms. This can enhance the self-purification capacity of the river, improve water quality, improve or restore the ecological environment of the river. The reoxygenation equipment has a simple process, relatively low cost, and no secondary pollution.

[0109] The chemical treatment system includes a water pump, a mixing tank, a reagent dosing device, a stirring device, and a drainage pipe. The water pump draws polluted river water into the mixing tank, the reagent dosing device adds reagents to the mixing tank, the stirring device mixes the reagents with the river water, and the drainage pipe discharges the treated river water from the mixing tank back into the river. By introducing various chemical agents into the polluted river section, this method has advantages such as rapid treatment speed, short treatment cycle, and significant effects, but the treatment cost is relatively high. This equipment is suitable for situations where total phosphorus, turbidity, or heavy metals exceed standards.

[0110] The industrial internet includes a central server, which is equipped with a pollution control standard level assessment module, a pollution control equipment control and operation analysis module, an equipment remote control module, and a standard database. The pollution control standard level assessment module is used to match the water quality pollution parameter monitoring indicators measured by the water quality pollution parameter index detection system with the water quality pollution parameter monitoring indicator limits given in the standard database, and to determine the pollution control standard level. The pollution control equipment control and operation analysis module is used to output different pollution control equipment control and operation schemes according to the pollution control standard level. The equipment remote control module is used to perform start and stop control operations on the river pollution control work points according to the pollution control equipment control and operation schemes.

[0111] The river pollution control equipment control and operation system can continuously monitor river sections in different environments within a specific watershed, achieving real-time monitoring, data transmission, and remote control. This allows monitoring personnel to quickly respond to any anomalies and take timely remedial measures, effectively reducing the occurrence and impact of pollution incidents. It also facilitates more convenient monitoring and management of river water quality, improves pollution early warning capabilities, and ensures that river water pollution conditions are promptly identified for rapid response.

[0112] Please refer to the flowchart of the river pollution control equipment control and operation system used in this embodiment. Figure 3 .

[0113] According to the river pollution control equipment control and operation method disclosed in this application, taking COD as an example, the following steps are included:

[0114] D1. Construct an analysis model for the control and operation of pollution control equipment, establish the correlation between pollution control standard levels and the corresponding control and operation of pollution control equipment, and be able to output different control and operation schemes for pollution control equipment according to different pollution control standard levels.

[0115] D2. Monitor water quality pollution parameters at each measurement point, and have the data collected and analyzed by the central server to assess the pollution control standard level.

[0116] D3. Based on the assessed pollution control standard level, match it with the pollution control equipment control and operation scheme in the pollution control equipment control and operation analysis model to obtain the pollution control equipment control and operation scheme.

[0117] D4. The central server performs start-stop control operations on each pollution control device according to the pollution control equipment control and operation plan obtained in step D3.

[0118] In step D1, the construction of the pollution control equipment control and operation analysis model specifically includes the following steps:

[0119] D1.1 Define the control and operation objectives of the pollution control equipment, namely, to achieve high pollution control efficiency and low pollution control cost while maintaining water quality standards.

[0120] D1.2 Collect data related to various water quality pollution parameters and monitoring indicators at various measurement points in the target river and transmit them to the central server;

[0121] D1.3 Preprocess the collected data to improve data quality and accuracy;

[0122] D1.4 Based on the decision tree model, according to the pollution control standard level, the basic model is constructed with different water quality pollution parameter monitoring indicators as root nodes, the corresponding water quality pollution parameter monitoring indicator limits as internal nodes, and the corresponding pollution control equipment attributes as leaf nodes.

[0123] D1.5 Collect the measured values ​​of multiple sets of water quality pollution parameter monitoring indicators and transmit them to the central server. The central server uses the measured values ​​of multiple sets of water quality pollution parameter monitoring indicators to verify and evaluate the basic model constructed in step D1.4.

[0124] D1.6. The information gain algorithm is used to optimize the basic model. The model path with high pollution control efficiency and low pollution control cost is selected as the selected pollution control equipment control and operation scheme to obtain the optimized model.

[0125] D1.7. Based on the optimized model in step D1.6, the optimized model is further verified and evaluated using the measured values ​​of multiple sets of water pollution parameter monitoring indicators. OEE accounting is then used to further improve and optimize the model, ultimately obtaining the optimal pollution control equipment control and operation scheme for different water pollution parameter monitoring indicators, which synergistically optimizes pollution control efficiency and pollution control cost.

[0126] For this embodiment, the pollution limit for chemical oxygen demand (COD) needs to comply with the "Surface Water Environmental Quality Standard" (GB3838-2002), Class IV water body standard, and the specific values ​​are shown in Table 1.

[0127] Please see Figure 4 This is a basic model for the control and operation of pollution control equipment related to chemical oxygen content (COD) constructed using the decision tree method. Figure 4 The root node of the decision tree is the content of water quality pollution parameter monitoring indicators. The decision tree uses the magnitude of water quality pollution parameter monitoring indicators as the feature evaluation standard. Figure 4 By setting the values ​​of monitoring indicators for different characteristic water pollution parameters (COD content in the inner node box), the equipment operation model path under various characteristic water pollution parameter monitoring conditions can be obtained, thereby creating equipment start-up control schemes under different characteristic pollution values.

[0128] Each inner leaf node in the model corresponds to the name and type of the equipment to be started. Based on the pollution control process of that equipment, attribute data such as equipment operating cost and pollution control efficiency can be obtained. The system can easily calculate the total operating cost and efficiency of the start-up control scheme. It is determined that the COD (Chemical Oxygen Demand) at each monitoring point in the river basin should not exceed 30 mg / L. When it exceeds this standard limit, it indicates that the river's COD pollution is exceeding the standard, and physical and chemical treatment systems need to be activated for COD pollution control and treatment.

[0129] For example, the water pollution parameter detection system detected a COD content of 36 mg / L. According to the national "Surface Water Environmental Quality Standard" (GB3838-2002) Class IV water quality control standard, it is necessary to activate the pollution control equipment for treatment. Through... Figure 4 The basic model constructed in the system is optimized using measured values ​​of multiple sets of water quality pollution parameters to obtain the equipment control and operation model under the current conditions. The system will activate the aeration equipment, water replenishment equipment, and chemical equipment A for pollution control. Please refer to [link / reference]. Figure 5 .

[0130] Then, please see Figure 6 This is a schematic diagram of the model optimized using the information gain algorithm. After optimizing the basic model using the information gain algorithm, the value of the COD content of a certain node in the decision tree changes, which in turn changes the device startup method. The structure of the decision tree will also differ from the previous diagram. Please refer to [link / reference]. Figure 6 If the COD standard value of the first internal node is changed from ≤32mg / L to ≤35mg / L, and the COD standard value of the second internal node is changed from ≤35mg / L to ≤38mg / L, the system will only activate the aeration equipment and the water replenishment equipment for pollution treatment. The different feature values ​​in these two scenarios affect the equipment startup control path, meaning the type and number of devices activated by the system will differ. The system will use the information gain formula of the decision tree to calculate the information gain of different equipment startup schemes to optimize the equipment startup configuration.

[0131] In this example of the pollution control process, the system's central server will also perform OEE (Overall Equipment Effectiveness) calculations based on the cost, efficiency, and number of devices, and comprehensively select the optimal equipment operating mode. OEE is an indicator and method for evaluating equipment efficiency. It is a basic manufacturing term, typically used to measure the performance and utilization rate of equipment in a production process. OEE calculation assesses the overall efficiency of equipment by comprehensively considering its availability, performance, and quality. It uses three main indicators to calculate the equipment's OEE value: Availability, Performance, and Quality. Availability measures the ratio of actual operating time to theoretical operating time within the planned production time. It is affected by factors such as equipment failure, downtime, and planned maintenance. The performance indicator measures the ratio between the actual operating speed and the theoretical maximum speed within the planned production time. It measures whether the equipment is operating at maximum efficiency. The quality indicator measures the ratio between the number of good products produced under normal operating conditions and the total output. It examines the quality level of the products produced by the equipment. These three indicators are multiplied together to obtain the equipment's OEE value, typically ranging from 0 to 1, and can also be expressed as a percentage. A higher OEE value indicates higher overall equipment efficiency. The purpose of OEE (Operational Equipment Effectiveness) accounting is to help understand equipment efficiency and utilization so that manufacturers can identify and improve factors that lead to inefficiency and take appropriate measures to improve production efficiency. By monitoring and analyzing OEE data, manufacturers can identify opportunities for improvement in areas such as equipment failure, downtime, low output, and quality issues, and take appropriate steps to improve equipment performance.

[0132] Based on the optimal pollution control equipment control and operation scheme, this embodiment utilizes an IoT remote DCS, PLC, and RTU control system to remotely control physical and chemical pollution control equipment within the river basin, automatically carrying out pollution remediation. This ensures that water quality pollution parameters within the river basin are within national environmental protection standards, preventing the escalation of river pollution incidents and minimizing pollution losses. This embodiment analyzes and judges the pollution status based on river basin pollution control level standards, establishes a rapid response mechanism for monitoring and treatment, and promptly handles pollution incidents. It achieves unmanned intelligent control of pollution control equipment with a high-efficiency and low-cost strategy, ensuring that water quality pollution parameters within the river basin are within national environmental protection standards, preventing the escalation of river pollution incidents, and minimizing pollution losses. This embodiment leverages the data processing capabilities of an industrial internet big data platform, utilizing connected online hydrological and water quality monitoring equipment for data collection. Combined with different water quality pollution parameter monitoring indicators, and through a pollution control equipment control and operation analysis model, it outputs the optimal pollution control equipment control and operation scheme for pollution exceeding control standards, based on different exceedance situations. This achieves fully intelligent management of pollution control equipment, reducing costs while improving pollution control efficiency.

[0133] It is understood that the present invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Under the teachings of the present invention, modifications can be made to these features and embodiments to adapt to specific situations and materials without departing from the spirit and scope of the invention. The embodiments described in this invention are only a part of the embodiments of the invention, not all of them. The components of the embodiments of the invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. Therefore, the invention is not limited to the specific embodiments disclosed herein, and all other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the present invention.

Claims

1. A method for controlling and operating river pollution control equipment, utilizing a river pollution control equipment control and operation system for the operation control of pollution control equipment in river basin pollution control, characterized in that... The river pollution control equipment control and operation system includes a water quality pollution parameter detection system, an industrial internet, and river pollution control work points. The water quality pollution parameter detection system and river pollution control work points are set up at multiple locations. The industrial internet includes a central server, which contains a pollution control standard level assessment module, a pollution control equipment control and operation analysis module, an equipment remote control module, and a standard database. The pollution control standard level assessment module matches the water quality pollution parameter monitoring indicators measured by the water quality pollution parameter detection system with the water quality pollution parameter monitoring indicator limits given in the standard database and determines the pollution control standard level. The pollution control equipment control and operation analysis module outputs different pollution control equipment control and operation schemes based on the pollution control standard level. The equipment remote control module performs start-stop control operations on the river pollution control work points according to the pollution control equipment control and operation schemes. The method includes the following steps: S1. Construct a pollution control equipment control and operation analysis model to establish the correlation between pollution control standard levels and the corresponding pollution control equipment control and operation, enabling the output of different pollution control equipment control and operation schemes based on different pollution control standard levels; the specific steps involved in constructing the pollution control equipment control and operation analysis model are as follows: S1.1 Define the control and operation objectives of the pollution control equipment, namely, to achieve high pollution control efficiency and low pollution control cost while maintaining water quality standards. S1.2 Collect data related to various water quality pollution parameters and monitoring indicators at various measurement points in the target river and transmit them to the central server; S1.3 Preprocess the collected data to improve data quality and accuracy; S1.4 Based on the decision tree model, according to the pollution control standard level, different water quality pollution parameter monitoring indicators are used as root nodes, the corresponding water quality pollution parameter monitoring indicator limits are used as internal nodes, and the attributes of the corresponding pollution control equipment are used as leaf nodes to construct the basic model. S1.

5. Collect the measured values ​​of multiple sets of water quality pollution parameter monitoring indicators and transmit them to the central server. The central server uses the measured values ​​of multiple sets of water quality pollution parameter monitoring indicators to verify and evaluate the basic model constructed in step S1.

4. S1.

6. The information gain algorithm is used to optimize the basic model. The model path with high pollution control efficiency and low pollution control cost is selected as the selected pollution control equipment control and operation scheme to obtain the optimized model. S1.

7. For the optimized model in step S1.6, the optimized model is further verified and evaluated by using the measured values ​​of multiple sets of water pollution parameter monitoring indicators. OEE accounting is used to further improve and optimize the model, and finally the optimal pollution control equipment control and operation scheme with the best synergy between pollution control efficiency and pollution control cost corresponding to different water pollution parameter monitoring indicators is obtained. S2. Monitor water quality pollution parameters at each measurement point, and have the data collected and analyzed by the central server to assess the pollution control standard level. S3. Based on the assessed pollution control standard level, match it with the pollution control equipment control and operation scheme in the pollution control equipment control and operation analysis model to obtain the pollution control equipment control and operation scheme. S4. The central server performs start-stop control operations on each pollution control device according to the pollution control equipment control operation plan obtained in step S3.

2. The method for controlling and operating river pollution control equipment according to claim 1, characterized in that, In step S1.3, the collected data is preprocessed, including data cleaning, missing value handling, outlier detection, and noise reduction.

3. The method for controlling and operating river pollution control equipment according to claim 1, characterized in that, In step S1.4, the attributes of the pollution control equipment include the on / off status, cost, and efficiency of the pollution control equipment.

4. The method for controlling and operating river pollution control equipment according to claim 1, characterized in that, In step S1.6, the pollution control efficiency and pollution control cost of each type of pollution control equipment are first calculated, the information gain of the start-up path of each type of pollution control equipment is calculated, and the model path with the larger information gain is taken as the model path after the pollution control efficiency and pollution control cost are jointly optimized, so as to obtain the optimized pollution control equipment control operation scheme.

5. The method for controlling and operating river pollution control equipment according to claim 1, characterized in that, In step S1.7, the optimized model is verified and evaluated by measuring the values ​​of multiple sets of water pollution parameter monitoring indicators. The model path with the largest information gain is selected as the model path with the optimal synergy between pollution control efficiency and pollution control cost. The pollution control equipment control and operation schemes with the optimal synergy between pollution control efficiency and pollution control cost corresponding to different pollution control standard levels are obtained.

6. The method for controlling and operating river pollution control equipment according to claim 1, characterized in that, In step S2, a linkage alarm threshold is set. When the water quality pollution parameters of each measuring point are monitored and the data is collected and analyzed by the central server to assess the pollution control standard level, if the assessed pollution control standard level exceeds the linkage alarm threshold, the central server will output an alarm message and save it.

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