Sewage plant monitoring control method and system based on digital twinning

Abstract

The invention discloses a sewage plant monitoring control method and system based on digital twinning, and relates to the technical field of sewage plant monitoring control, and the method comprises the following steps: 1, respectively deploying sensors at a water inlet, a biological reaction tank, a sedimentation tank, a water outlet and a key area of a plant area of a sewage plant, the sensors comprise a water quality monitoring sensor, a process operation monitoring sensor and an environment and safety monitoring sensor; 2, collecting data output by each sensor through an edge computing gateway, and carrying out filtering and normalization preprocessing on the collected data; according to the sewage plant monitoring control method and system based on digital twinning, full-process dynamic monitoring is realized: multiple types of sensors are deployed in a key area, a physical entity state is synchronized in real time in combination with a digital twinning model, and a process dynamic state is visually reproduced, so that the problem that a working condition is difficult to visually master by only depending on data fusion traditionally is solved; and the process abnormity can be quickly found.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment plant monitoring and control technology, specifically to a wastewater treatment plant monitoring and control method and system based on digital twins. Background Technology

[0002] With the rapid pace of industrialization and urbanization in my country, the water environment faces complex pollution pressures. Wastewater treatment plants, as core infrastructure for water purification and aquatic ecological protection, directly impact residents' health, food security, and ecological balance through their operational stability and treatment efficiency. According to the "National Surface Water Environmental Quality Status from January to December 2024," 9.6% of national monitoring sections still failed to meet Class III water quality standards, and the risk of a resurgence of black and odorous water bodies in some areas is becoming increasingly prominent. Furthermore, the "Water Ecological Environment Protection Plan" sets a rigid target of "94.5% of surface water reaching excellent or good quality by 2025." The traditional "end-of-pipe treatment" model is no longer sufficient to meet the needs of the entire treatment chain, from source control to process management to end-of-pipe treatment. The wastewater treatment industry urgently needs technological upgrades to improve monitoring accuracy and control efficiency.

[0003] Currently, my country has over 5,000 urban wastewater treatment plants with a daily treatment capacity exceeding 300 million cubic meters, basically covering all county-level administrative regions. However, the industry's operational needs are upgrading towards refinement and efficiency. On the one hand, the scale of wastewater treatment and the complexity of operating conditions continue to increase. For example, in riverside cities like Chongqing, the concentrations of COD and ammonia nitrogen in the influent can fluctuate by more than 30% within one hour due to backflow of rainwater during the flood season, requiring real-time dynamic adjustment of process parameters to ensure that the effluent meets standards. On the other hand, wastewater treatment plants bear the pressure of energy consumption and cost control. The energy consumption of the aeration system accounts for more than 60% of the total energy consumption of the plant, and the consumption of carbon sources, flocculants, and other chemicals directly affects operating costs. The annual electricity and chemical expenditures of a 100,000-ton-class wastewater treatment plant often exceed ten million yuan, urgently requiring cost reduction and efficiency improvement through precise monitoring and intelligent control.

[0004] For example, Chinese invention patent application number 202311484548.3 discloses a wastewater treatment monitoring and control method and system based on data fusion. This method utilizes data fusion to allow for the comprehensive consideration of multiple parameters, thereby providing more comprehensive information, assessing the overall performance of the system, and ultimately better managing the wastewater treatment system, reducing resource waste, and mitigating environmental risks. However, the method and system still have certain shortcomings.

[0005] Technically, a dynamic virtual mapping of the physical entity of the wastewater treatment plant has not been constructed. It relies solely on data fusion assessment, which cannot intuitively reproduce the dynamics of the process and the effect of simulated parameter adjustment. Process optimization depends on experience and trial and error. The control logic is "data acquisition - analysis and evaluation - post-event adjustment", which lacks real-time closed-loop control. The time difference between data acquisition and command issuance is relatively long, making it difficult to cope with sudden changes in influent water quality and other emergencies.

[0006] Therefore, we propose a monitoring and control method and system for wastewater treatment plants based on digital twins to address the problems mentioned above. Summary of the Invention

[0007] The purpose of this invention is to provide a wastewater treatment plant monitoring and control method and system based on digital twins, in order to solve the problems mentioned in the background art. Currently, the monitoring and control of wastewater treatment plants on the market does not technically construct a dynamic virtual mapping of the physical entity of the wastewater treatment plant, but only relies on data fusion evaluation. It cannot intuitively reproduce the process dynamics and simulate the effect of parameter adjustment. Process optimization relies on experience trial and error, lacks real-time closed-loop control, and has a long time difference from data acquisition to command issuance, making it difficult to cope with sudden operating conditions such as sudden changes in influent water quality.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a wastewater treatment plant monitoring and control method and system based on digital twins, comprising the following steps:

[0009] Step 1: Deploy sensors at the wastewater treatment plant inlet, biological reactor, sedimentation tank, effluent outlet, and key areas of the plant. The sensors include water quality monitoring sensors, process operation monitoring sensors, and environmental and safety monitoring sensors.

[0010] Step 2: Collect data output from each sensor through the edge computing gateway, and perform filtering and normalization preprocessing on the collected data;

[0011] Step 3: Construct a digital twin model of the physical entity of the wastewater treatment plant. The digital twin model includes a geometric model, a physical model, a behavioral model, and a rule model. The geometric model reproduces the dimensions of the wastewater treatment plant's equipment and pipelines in proportion.

[0012] Step 4: Transmit the preprocessed data to the digital twin platform to synchronize the digital twin model with the physical entity;

[0013] Step 5: Based on the real-time data received by the digital twin platform, generate a visual interface for the wastewater treatment plant's process operation;

[0014] Step Six: Issue control commands to the wastewater treatment plant control system through the digital twin platform. The control commands include aeration system adjustment commands, dosing system adjustment commands, and valve adjustment commands.

[0015] Preferably, in step one, the water quality monitoring sensors include a chemical oxygen demand (COD) analysis sensor, a five-day biochemical oxygen demand (BOD) monitoring sensor, a suspended solids monitoring sensor, a nitrogen and phosphorus analysis sensor, and a conventional multi-parameter water quality sensor; and the process operation monitoring sensors include a flow monitoring sensor, a liquid level monitoring sensor, a sludge characteristic monitoring sensor, and an aeration system monitoring sensor.

[0016] By adopting the above technical solution, water quality monitoring sensors and process operation monitoring sensors are deployed in categories to collect key data on wastewater quality and process operation, providing categorized data support for subsequent data processing and process evaluation.

[0017] Preferably, in step two, the edge computing gateway uses dual-link data transmission, and the data acquisition frequency is set according to parameter type, with different acquisition frequencies for key water quality parameters and environmental temperature and humidity parameters.

[0018] Using the above technical solution, the edge computing gateway employs dual links to ensure data transmission stability, sets the collection frequency according to the importance of parameters, and collects key water quality parameters and environmental temperature and humidity parameters differently to ensure that core data is acquired at high frequency and non-core data is collected reasonably, thus balancing data integrity and transmission efficiency.

[0019] Preferably, in step three, the physical model is constructed based on the activated sludge digestion model, the behavioral model defines the equipment operation logic through scripts, and the rule model includes preset thresholds for wastewater treatment plant process adjustments.

[0020] Using the above technical solution, the physical model restores the biochemical reaction law of wastewater based on the activated sludge digestion model, the behavioral model defines the operation logic such as equipment start-up and shutdown and parameter adjustment through scripts, and the rule model presets the process adjustment threshold. The combination of the three constructs the core of the digital twin model, ensuring that the virtual model can simulate the operating state and process constraints of the physical entity.

[0021] Preferably, in step four, data transmission uses an encrypted protocol, and the digital twin model maintains data synchronization with the physical entity.

[0022] The above technical solution employs an encryption protocol to ensure data transmission security, while establishing a data synchronization mechanism to enable the digital twin model to receive and update preprocessed data in real time. This ensures that the virtual model's state remains consistent with the physical operating state of the wastewater treatment plant, providing an accurate data foundation for subsequent visualization and control.

[0023] Preferably, in step five, the visualization interface is developed using a 3D engine and supports 3D scene roaming and real-time rendering.

[0024] The above technical solution employs a 3D engine to develop a visualization interface that dynamically presents the wastewater treatment plant's process operation status through real-time rendering technology. This allows maintenance personnel to roam through 3D scenes, intuitively view the equipment, water quality, and process flow in each area, and quickly grasp the overall plant operation status.

[0025] Preferably, in step six, the control command needs to undergo permission verification before it is issued. The permission verification is based on the job permission model, and different job personnel have different command operation permissions.

[0026] By adopting the above technical solution, before the control command is issued, the operator's permissions are verified based on the job permission model. Personnel in different positions can only operate the commands corresponding to their permissions, avoiding process errors caused by unauthorized operations and ensuring the security and standardization of command issuance.

[0027] A wastewater treatment plant monitoring and control system based on digital twins includes a sensing layer, an edge computing layer, a digital twin layer, and a control execution layer;

[0028] The sensing layer includes water quality monitoring sensors, process operation monitoring sensors, and environmental and safety monitoring sensors. All sensors are corrosion-resistant and waterproof.

[0029] The edge computing layer includes an edge computing gateway and a local data preprocessing module, and the edge computing gateway is deployed near each process unit;

[0030] The digital twin layer includes a digital twin platform and a data storage module, and the data storage module adopts a hybrid database architecture;

[0031] The control execution layer includes a control system, an aeration system, a dosing system, and a valve system. The aeration system is equipped with a speed regulating device, and the dosing system uses a metering pump.

[0032] Preferably, the digital twin platform adopts a microservice architecture, which separates the core services of data collection, model simulation, visualization and command issuance. Each service is registered and discovered through a service management component.

[0033] By adopting the above technical solution, the digital twin platform splits the core services according to the microservice architecture. Each service is registered and discovered through the service management component, enabling independent operation and collaborative linkage of functions such as data collection, model simulation, visualization display, and command issuance, thus ensuring the platform's flexible expansion and stable operation.

[0034] Preferably, in the control execution layer, the regulating valve adopts a linear stroke structure and has a set stroke time and positioning accuracy; the backup power generation equipment is linked with the control system and automatically starts when power is interrupted.

[0035] Using the above technical solution, in the control execution layer, the linear stroke regulating valve adjusts its opening according to the set logic to ensure precise adjustment of process parameters; the backup power generation equipment is linked with the control system and automatically starts when a power outage is detected to ensure uninterrupted operation of key processing units and maintain process stability.

[0036] Compared with the prior art, the beneficial effects of the present invention are: the wastewater treatment plant monitoring and control method and system based on digital twins:

[0037] 1. Achieve dynamic monitoring of the entire process: By deploying multiple types of sensors in key areas and combining them with digital twin models to synchronize the physical status in real time, the dynamics of the process can be intuitively reproduced, solving the problem that traditional data fusion alone is not enough to intuitively grasp the working conditions, and helping to quickly detect process anomalies.

[0038] 2. Improve the timeliness of regulation: The edge computing gateway preprocesses the data, and the digital twin platform directly issues control commands, forming a real-time closed loop. This shortens the time from data collection to command issuance, effectively responding to sudden changes in influent water quality and reducing the risk of effluent exceeding standards.

[0039] 3. Ensure data security and stability: Data transmission adopts an encrypted protocol, dual-link transmission through the edge computing gateway, and data storage using a hybrid database architecture, reducing the risk of data leakage and loss, while ensuring stable data transmission and storage, providing reliable data support for monitoring and control;

[0040] 4. Optimize operation and maintenance experience and security: The 3D visualization interface supports scene roaming, making it easy for operation and maintenance personnel to intuitively grasp the status of the entire plant; permission verification before issuing instructions avoids unauthorized operations, which not only improves operation and maintenance efficiency, but also ensures the safety and standardization of process operations.

[0041] 5. Ensure stable system operation: The control and execution layer regulates valves precisely, the backup power generation equipment automatically starts when power is interrupted, and the microservice architecture of the digital twin platform can be flexibly expanded, ensuring the stable operation of the sewage treatment plant process and the long-term reliability of the system from multiple dimensions. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0043] Figure 2 This is a schematic diagram of the data acquisition and preprocessing stages of the present invention;

[0044] Figure 3 This is a schematic diagram of the digital twin modeling and synchronization stage of the present invention;

[0045] Figure 4 This is a schematic diagram illustrating the visualization and control execution phase of the present invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Please see Figures 1-4This invention provides a technical solution: a wastewater treatment plant monitoring and control method and system based on digital twins, comprising the following steps:

[0048] Step 1: Deploy sensors at the wastewater treatment plant inlet, biological reactor, sedimentation tank, effluent outlet, and key areas of the plant. The sensors include water quality monitoring sensors, process operation monitoring sensors, and environmental and safety monitoring sensors.

[0049] Step 2: Collect data output from each sensor through the edge computing gateway, and perform filtering and normalization preprocessing on the collected data;

[0050] Step 3: Construct a digital twin model of the wastewater treatment plant's physical entity. The digital twin model includes a geometric model, a physical model, a behavioral model, and a rule model. The geometric model scales up to the dimensions of the wastewater treatment plant's equipment and pipes.

[0051] Step 4: Transmit the preprocessed data to the digital twin platform to synchronize the digital twin model with the physical entity;

[0052] Step 5: Based on the real-time data received by the digital twin platform, generate a visual interface for the wastewater treatment plant's process operation;

[0053] Step Six: Issue control commands to the wastewater treatment plant control system through the digital twin platform. The control commands include aeration system adjustment commands, dosing system adjustment commands, and valve adjustment commands.

[0054] In step one, the water quality monitoring sensors include chemical oxygen demand (COD) analysis sensors, five-day biochemical oxygen demand (BOD) monitoring sensors, suspended solids monitoring sensors, nitrogen and phosphorus analysis sensors, and conventional multi-parameter water quality sensors; and the process operation monitoring sensors include flow monitoring sensors, liquid level monitoring sensors, sludge characteristic monitoring sensors, and aeration system monitoring sensors.

[0055] By adopting the above technical solution, water quality monitoring sensors and process operation monitoring sensors are deployed in categories to collect key data on wastewater quality and process operation, providing categorized data support for subsequent data processing and process evaluation.

[0056] In step two, the edge computing gateway uses dual links to transmit data. The data acquisition frequency is set according to the parameter type. Key water quality parameters and environmental temperature and humidity parameters are acquired at different frequencies. The edge computing gateway uses dual links to ensure the stability of data transmission. The acquisition frequency is set according to the importance of parameters. Key water quality parameters and environmental temperature and humidity parameters are acquired differently to ensure that core data is acquired at high frequency and non-core data is acquired reasonably, thus balancing data integrity and transmission efficiency.

[0057] In step three, the physical model is built based on the activated sludge digestion model, the behavioral model defines the equipment operation logic through scripts, and the rule model contains preset thresholds for process adjustment in the wastewater treatment plant. The physical model restores the biochemical reaction law of wastewater based on the activated sludge digestion model, the behavioral model defines the operation logic such as equipment start-up and shutdown and parameter adjustment through scripts, and the rule model presets process adjustment thresholds. The three are combined to build the core of the digital twin model, ensuring that the virtual model can simulate the operating state and process constraints of the physical entity.

[0058] In step four, data transmission uses an encrypted protocol to ensure data synchronization between the digital twin model and the physical entity. The encrypted protocol also ensures data security. At the same time, a data synchronization mechanism is established to enable the digital twin model to receive and update the preprocessed data in real time, ensuring that the virtual model's state is consistent with the operating state of the wastewater treatment plant's physical entity, thus providing an accurate data foundation for subsequent visualization and control.

[0059] In step five, the visualization interface is developed using a 3D engine, supporting 3D scene roaming and real-time rendering. The visualization interface, developed using a 3D engine, dynamically presents the process operation status of the wastewater treatment plant through real-time rendering technology, allowing operation and maintenance personnel to roam the 3D scene and intuitively view the equipment, water quality, and process flow in each area, helping them to quickly grasp the overall operation status of the plant.

[0060] In step six, permission verification is required before control commands are issued. Permission verification is based on the job-specific permission model. Different job personnel have different command operation permissions. Before the control commands are issued, the permissions of the operators are verified according to the job-specific permission model. Personnel in different positions can only operate commands with corresponding permissions to avoid process errors caused by unauthorized operations and ensure the security and standardization of command issuance.

[0061] A wastewater treatment plant monitoring and control system based on digital twins includes a sensing layer, an edge computing layer, a digital twin layer, and a control execution layer;

[0062] The sensing layer includes water quality monitoring sensors, process operation monitoring sensors, and environmental and safety monitoring sensors. All sensors are corrosion-resistant and waterproof.

[0063] The edge computing layer includes an edge computing gateway and a local data preprocessing module, with the edge computing gateway deployed near each process unit;

[0064] The digital twin layer includes a digital twin platform and a data storage module, and the data storage module adopts a hybrid database architecture;

[0065] The control and execution layer includes a control system, an aeration system, a dosing system, and a valve system. The aeration system is equipped with a speed control device, and the dosing system uses a metering pump.

[0066] The digital twin platform adopts a microservice architecture, separating core services such as data acquisition, model simulation, visualization, and command issuance. Each service registers and discovers through a service management component. The digital twin platform separates core services according to the microservice architecture, and each service registers and discovers through the service management component, enabling independent operation and collaborative linkage of functions such as data acquisition, model simulation, visualization, and command issuance, ensuring the platform's flexible expansion and stable operation.

[0067] In the control and execution layer, the regulating valve adopts a linear stroke structure with a set stroke time and positioning accuracy; the backup power generation equipment is linked with the control system and automatically starts when power is interrupted. In the control and execution layer, the linear stroke regulating valve adjusts its opening according to the set logic to ensure precise adjustment of process parameters; the backup power generation equipment is linked with the control system and automatically starts when a power outage is detected to ensure uninterrupted operation of key processing units and maintain process stability.

[0068] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

[0069] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A digital-twin-based sewage plant monitoring control method and system, characterized in that: The method comprises the following steps: Step 1: Deploy sensors at the influent inlet, biological reaction tank, sedimentation tank, effluent outlet and key areas of the sewage plant, and the sensors include water quality monitoring sensors, process operation monitoring sensors and environmental and safety monitoring sensors; Step 2: Collect the data output by the sensors through an edge computing gateway, and perform filtering and normalization preprocessing on the collected data; Step 3: Construct a digital twin model of the physical entity of the sewage plant, wherein the digital twin model comprises a geometric model, a physical model, a behavior model and a rule model, and the geometric model restores the sizes of the sewage plant equipment and pipes in proportion; Step 4: Transmit the preprocessed data to the digital twin platform, so that the digital twin model and the physical entity realize data synchronization; Step 5: Based on the real-time data received by the digital twin platform, generate a visual interface of the process operation of the sewage plant; Step 6: Issue control instructions, including aeration system adjustment instructions, dosing system adjustment instructions and valve adjustment instructions, to the sewage plant control system through the digital twin platform.

2. The digital-twin-based wastewater treatment plant monitoring control method and system according to claim 1, characterized in that: In step 1, the water quality monitoring sensors include chemical oxygen demand analysis sensors, five-day biochemical oxygen demand monitoring sensors, suspended solids monitoring sensors, nitrogen and phosphorus analysis sensors and conventional water quality multi-parameter sensors; and the process operation monitoring sensors include flow monitoring sensors, liquid level monitoring sensors, sludge property monitoring sensors and aeration system monitoring sensors.

3. The digital-twin-based wastewater treatment plant monitoring control method and system of claim 1, wherein: In step 2, the edge computing gateway transmits data using dual-link, and the data collection frequency is set hierarchically according to parameter types, and different collection frequencies are used for water quality key parameters and environmental temperature and humidity parameters.

4. The digital-twin-based wastewater treatment plant monitoring control method and system of claim 1, wherein: In step 3, the physical model is constructed based on the activated sludge digestion model, the behavior model defines the device operation logic through scripts, and the rule model contains preset thresholds for process adjustment of the sewage plant.

5. The digital-twin-based wastewater treatment plant monitoring control method and system according to claim 1, characterized in that: In step 4, the data transmission uses an encryption protocol, and the digital twin model and the physical entity keep data synchronization.

6. The digital-twin-based wastewater treatment plant monitoring control method and system according to claim 1, characterized in that: In step 5, the visual interface is developed using a three-dimensional engine, supporting three-dimensional scene roaming and real-time rendering.

7. The digital-twin-based wastewater treatment plant monitoring control method and system according to claim 1, characterized in that: In step 6, the control instructions need to pass through permission verification before being issued, and the permission verification is realized based on a post permission model, and different post personnel correspond to different instruction operation permissions.

8. A digital-twin-based sewage plant monitoring control system, characterized by: The system comprises a perception layer, an edge computing layer, a digital twin layer and a control execution layer; The perception layer comprises water quality monitoring sensors, process operation monitoring sensors and environmental and safety monitoring sensors, and all the sensors have corrosion, waterproof and protection capabilities; The edge computing layer comprises an edge computing gateway and a local data preprocessing module, and the edge computing gateway is deployed near each process unit; The digital twin layer comprises a digital twin platform and a data storage module, and the data storage module adopts a hybrid database architecture; The control execution layer comprises a control system, an aeration system, a dosing system and a valve system, and the aeration system is equipped with a speed regulation device, and the dosing system uses a metering pump.

9. The digital-twin-based wastewater treatment plant monitoring control system of claim 8, wherein: The digital twin platform adopts a micro-service architecture, and splits data collection, model simulation, visual display and instruction issuing core services, and each service realizes service registration and discovery through a service management component.

10. The digital-twin-based wastewater treatment plant monitoring control system of claim 8, wherein: The control execution layer adopts a straight stroke structure, has set stroke time and positioning accuracy, and the standby power generation equipment is linked with the control system and automatically starts when power is off.

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