Intelligent sewage disposal monitoring system for water intake and drainage tunnel based on digital twinning

Abstract

The invention belongs to the technical field of hydraulic engineering monitoring, and particularly discloses a digital twinning-based intelligent sewage disposal monitoring system for a water intake and drainage tunnel, which comprises a data acquisition module, a digital twinning model construction module, a data analysis and decision module, a sewage disposal equipment control module and a visual display and interaction module, the data acquisition module is used for acquiring water quality, flow, equipment state and image data in a tunnel in real time; the digital twin model construction module is used for constructing and dynamically updating a three-dimensional virtual model of a tunnel; the data analysis and decision module is used for analyzing data through a machine learning algorithm and generating a decontamination strategy; the cleaning equipment control module is used for automatically controlling the cleaning equipment to execute cleaning operation; the visual display and interaction module is used for providing a three-dimensional visual interface and man-machine interaction; through a digital twinborn technology and intelligent monitoring, analysis and control, real-time, precise, automatic and visual sewage disposal monitoring of the water taking and draining tunnel is realized.

Description

Technical Field

[0001] This invention relates to the field of water conservancy engineering monitoring technology, specifically to an intelligent cleaning and pollution monitoring system for intake and drainage tunnels based on digital twins. Background Technology

[0002] A water passage tunnel excavated into a mountain or underground. Hydraulic tunnels can be used for irrigation, power generation, water supply, drainage, water conveyance, construction diversion, and navigation. Tunnels where the water flow has a free surface inside are called unpressurized tunnels; those that fill the entire cross-section, subjecting the tunnel walls to a certain water pressure, are called pressurized tunnels.

[0003] Water intake and drainage tunnels play a vital role in water conservancy projects, industrial production, and urban water supply. However, silt, debris, and other pollutants easily accumulate within these tunnels, affecting their normal operation and water flow quality. Traditional methods for monitoring water intake and drainage primarily rely on manual inspections and periodic maintenance, which suffer from problems such as untimely monitoring, inaccurate data, high labor costs, and significant safety risks. Furthermore, they struggle to provide comprehensive and precise management and optimization of the cleaning and drainage process. Therefore, a more intelligent and efficient water intake and drainage monitoring system is needed to address these issues. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent cleaning and pollution monitoring system for water intake and drainage tunnels based on digital twins, so as to achieve intelligent and efficient cleaning and pollution monitoring.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a digital twin-based intelligent cleaning and monitoring system for water intake and drainage tunnels, comprising a data acquisition module, a digital twin model construction module, a data analysis and decision-making module, a cleaning and equipment control module, and a visualization and interaction module.

[0006] The data acquisition module is used to collect water quality, flow rate, equipment status, and image data in the tunnel in real time.

[0007] The digital twin model building module is used to build and dynamically update a three-dimensional virtual model of the tunnel.

[0008] The data analysis and decision-making module is used to analyze data and generate cleaning strategies through machine learning algorithms.

[0009] The cleaning equipment control module is used to automatically control the cleaning equipment to perform cleaning operations.

[0010] The visualization and interaction module is used to provide a three-dimensional visualization interface and human-computer interaction functions.

[0011] As a preferred embodiment of the present invention, the data acquisition module includes sensors installed in the water intake and drainage tunnel, including water quality sensors, flow sensors, liquid level sensors, image sensors, and equipment status sensors.

[0012] Water quality sensors are used to monitor water quality indicators, including pH, turbidity, and dissolved oxygen; flow sensors are used to monitor water flow velocity and flow rate; level sensors are used to monitor water level; image sensors, such as high-definition cameras, are used to capture images and videos inside tunnels to monitor the distribution and accumulation of pollutants; and equipment status sensors are used to monitor the operating parameters of cleaning equipment, including motor speed and power.

[0013] As a preferred embodiment of the present invention, the sensor collects the tunnel's operational data and environmental information in real time, and transmits the data to the data processing center via a wired or wireless communication network.

[0014] As a preferred embodiment of the present invention, the digital twin model construction module utilizes computer simulation technology to construct a virtual digital twin model that is completely mapped to the physical tunnel based on the design drawings, geological exploration data, and construction record information of the water intake and drainage tunnel. This model includes static information such as the tunnel's geometry, internal structure, and material properties, while also reflecting the tunnel's dynamic operating status in real time, including water flow conditions, pollutant distribution, and the working status of cleaning equipment. Furthermore, by continuously updating the data in the model, the digital twin model is ensured to be highly consistent with the physical tunnel.

[0015] As a preferred embodiment of the present invention, the data analysis and decision-making module performs in-depth analysis on the collected real-time data and the data in the digital twin model. The analysis method includes the following steps:

[0016] S1. Utilize big data analysis, machine learning, and artificial intelligence algorithms to identify the sources, types, distribution patterns, and development trends of pollutants.

[0017] S2. Evaluate the operating efficiency and performance of the cleaning equipment and predict potential equipment failures.

[0018] S3. Based on the analysis results, combined with preset rules and optimization objectives, generate cleaning plans and equipment control instructions; automatically adjust the working time, intensity, and path of the cleaning equipment according to water quality changes and pollutant accumulation; and promptly issue early warning information and provide maintenance suggestions when equipment abnormalities are detected.

[0019] As a preferred embodiment of the present invention, the cleaning equipment control module remotely controls the cleaning equipment in the water intake and drainage tunnel according to the control instructions generated by the data analysis and decision-making module. The cleaning equipment includes, but is not limited to, cleaning robots, sludge scrapers, and sludge pumps. By precisely controlling the operation of the cleaning equipment, automated cleaning operations are achieved, improving cleaning efficiency and quality. At the same time, the working status of the cleaning equipment is monitored in real time to ensure the safe and stable operation of the equipment.

[0020] As a preferred embodiment of the present invention, the visualization and interaction module displays the digital twin model, monitoring data, analysis results, and pollution control plan information to the user in an intuitive and visual manner, specifically including:

[0021] Using 3D visualization technology, a virtual model of the water intake and drainage tunnel is presented on the computer screen, and users can view, operate and control it in real time through an interactive interface.

[0022] Users can remotely view real-time images and videos inside the tunnel to understand the progress of pollutant cleanup; adjust cleanup plans and equipment parameters; and query historical data and analysis reports.

[0023] This module supports simultaneous online collaboration among multiple users, facilitating information sharing and communication between different departments and personnel.

[0024] Compared with the prior art, the beneficial effects of the present invention are:

[0025] This invention relates to an intelligent cleaning and monitoring system for water intake and drainage tunnels based on digital twin technology. Through digital twin technology and intelligent monitoring, analysis, and control methods, it achieves real-time, precise, automated, and visualized monitoring of cleaning and pollution in water intake and drainage tunnels. This system effectively improves cleaning efficiency and effectiveness, reduces operating costs and safety risks, and ensures the normal operation of the tunnel and the quality of water flow, resulting in significant economic and social benefits. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0027] 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.

[0028] Example 1

[0029] like Figure 1 As shown, this embodiment provides a data acquisition module in a digital twin-based intelligent cleaning and monitoring system for water intake and drainage tunnels, which is used to collect water quality, flow rate, equipment status and image data in the tunnel in real time.

[0030] The data acquisition module includes sensors installed inside the water intake and drainage tunnel, including water quality sensors, flow sensors, liquid level sensors, image sensors, and equipment status sensors.

[0031] Water quality sensors are used to monitor water quality indicators, including pH, turbidity, and dissolved oxygen; flow sensors are used to monitor water flow velocity and flow rate; level sensors are used to monitor water level; image sensors, such as high-definition cameras, are used to capture images and videos inside tunnels to monitor the distribution and accumulation of pollutants; and equipment status sensors are used to monitor the operating parameters of cleaning equipment, including motor speed and power.

[0032] The sensors collect tunnel operation data and environmental information in real time and transmit the data to the data processing center via wired or wireless communication networks.

[0033] Based on the actual conditions and monitoring needs of the intake and drainage tunnels, various sensors should be rationally deployed. Water quality sensors should be installed in locations where the water flow is relatively stable and representative to accurately monitor changes in water quality; image sensors should be installed in locations that can cover the main areas of the tunnel to ensure clear imaging of the distribution of pollutants.

[0034] Choose an appropriate communication method to transmit the data collected by the sensor to the data processing center. For sensors that are close to the data source, wired communication methods such as Ethernet or fiber optics can be used to ensure the stability and reliability of data transmission. For sensors that are far away or difficult to wire, wireless communication methods such as ZigBee, LoRa, and 4G / 5G can be used.

[0035] Example 2

[0036] like Figure 1 As shown, this embodiment provides a digital twin model construction module in a digital twin-based intelligent cleaning and monitoring system for water intake and drainage tunnels, which is used to construct and dynamically update a three-dimensional virtual model of the tunnel.

[0037] The digital twin model construction module utilizes computer simulation technology to construct a virtual digital twin model that perfectly maps to the physical tunnel, based on the design drawings, geological exploration data, and construction records of the water intake and drainage tunnel. This model includes static information such as the tunnel's geometry, internal structure, and material properties, while also reflecting the tunnel's dynamic operating status in real time, including water flow conditions, pollutant distribution, and the working status of cleaning equipment. Furthermore, by continuously updating the data in the model, it ensures a high degree of consistency between the digital twin model and the physical tunnel.

[0038] Collect relevant data on the intake and drainage tunnels, including design drawings, geological reports, and construction records, and organize and preprocess the data.

[0039] Using professional modeling software, such as 3DMAX and Maya, combined with Geographic Information System (GIS) technology, a three-dimensional geometric model of the water intake and drainage tunnel is constructed.

[0040] Real-time data collected by sensors is fused with a digital twin model, and real-time synchronization and updates are achieved through data interfaces and communication protocols. Simulation algorithms and physical models are used to simulate water flow, pollutant diffusion, and cleaning processes within the tunnel, enabling the digital twin model to accurately reflect the actual operating status of the physical tunnel.

[0041] Example 3

[0042] like Figure 1 As shown, this embodiment provides a data analysis and decision-making module in a digital twin-based intelligent cleaning and monitoring system for water intake and drainage tunnels, which is used to analyze data and generate cleaning and pollution control strategies through machine learning algorithms.

[0043] The data analysis and decision-making module performs in-depth analysis on the collected real-time data and data in the digital twin model. The analysis method includes the following steps:

[0044] S1. Utilize big data analysis, machine learning, and artificial intelligence algorithms to identify the sources, types, distribution patterns, and development trends of pollutants;

[0045] S2. Evaluate the operating efficiency and performance of the cleaning equipment and predict potential equipment failures;

[0046] S3. Based on the analysis results, combined with preset rules and optimization objectives, generate cleaning plans and equipment control instructions; automatically adjust the working time, intensity, and path of the cleaning equipment according to water quality changes and pollutant accumulation; and promptly issue early warning information and provide maintenance suggestions when equipment abnormalities are detected.

[0047] Establish a data storage and management system to classify, store, and back up the large amounts of collected data. Employ database technologies such as MySQL and Oracle to ensure data security and accessibility.

[0048] Big data analytics tools and algorithms, such as Hadoop, Spark, and TensorFlow, are used to clean, mine, and analyze the data. Machine learning algorithms, such as decision trees, neural networks, and support vector machines, are used to establish pollutant prediction models, equipment failure early warning models, and pollution control scheme optimization models.

[0049] Based on the analysis results and preset rules, a cleaning plan and equipment control commands are generated. These commands are then sent to the cleaning equipment control module to achieve automated control of the cleaning equipment.

[0050] Example 4

[0051] like Figure 1As shown, this embodiment provides a cleaning equipment control module in a digital twin-based intelligent cleaning and monitoring system for water intake and drainage tunnels, which is used to automatically control the cleaning equipment to perform cleaning operations.

[0052] The cleaning equipment control module remotely controls the cleaning equipment in the water intake and drainage tunnel according to the control commands generated by the data analysis and decision-making module. The cleaning equipment includes, but is not limited to, cleaning robots, sludge scrapers, and sludge pumps. By precisely controlling the operation of the cleaning equipment, automated cleaning operations are achieved, improving cleaning efficiency and quality. At the same time, the working status of the cleaning equipment is monitored in real time to ensure the safe and stable operation of the equipment.

[0053] The cleaning equipment is upgraded to be intelligent, enabling it to have remote communication and control functions. Controllers and communication modules are installed on the cleaning equipment, allowing it to receive control commands and execute corresponding operations through a communication interface with the data processing center.

[0054] Establish an equipment monitoring and management system to monitor the operating status and parameters of the cleaning equipment in real time. When equipment malfunctions, promptly issue alarm messages and take corresponding protective measures, such as automatic shutdown and adjustment of operating parameters.

[0055] Regularly maintain and service the cleaning equipment to ensure its normal operation and lifespan. Develop reasonable maintenance plans and repair solutions based on equipment operating data and fault warning information.

[0056] Example 5

[0057] like Figure 1 As shown, this embodiment provides a visualization and interaction module in a digital twin-based intelligent cleaning and monitoring system for water intake and drainage tunnels, which provides a three-dimensional visualization interface and human-computer interaction functions.

[0058] The visualization and interaction module presents the digital twin model, monitoring data, analysis results, and pollution control plan information to users in an intuitive and visual way, specifically including:

[0059] Using 3D visualization technology, a virtual model of the water intake and drainage tunnel is presented on the computer screen, and users can view, operate and control it in real time through an interactive interface;

[0060] Users can remotely view real-time images and videos inside the tunnel to understand the progress of pollutant removal; adjust cleaning plans and equipment parameters; and query historical data and analysis reports.

[0061] This module supports simultaneous online collaboration among multiple users, facilitating information sharing and communication between different departments and personnel.

[0062] Develop a visualization platform that uses Web or mobile application technologies to present digital twin models, monitoring data, analysis results, and other information to users in intuitive graphical, chart, and report formats.

[0063] The user interface is designed to allow users to interact with and control the displayed content using devices such as a mouse, keyboard, and touchscreen. Users can perform operations such as zooming, rotating, and panning to view different angles and details of the digital twin model; they can also query historical data, generate reports, and set alert thresholds.

[0064] This system enables multi-user access control and collaboration, assigning different access permissions based on user roles and responsibilities. Different users can share information and collaborate on the same platform, improving work efficiency and management effectiveness.

[0065] Based on the embodiments 1-5, this invention monitors the tunnel's operating status and environmental data in real time by deploying various sensors (water quality, flow rate, liquid level, images, equipment status, etc.); data is transmitted to a data processing center via wired / wireless networks to provide a foundation for subsequent analysis. A high-precision three-dimensional virtual model is constructed based on tunnel design drawings and geological data, fusing static (geometric structure, material properties) and dynamic (water flow, pollutant distribution, equipment status) data; real-time data updates ensure that the virtual model and the physical tunnel remain synchronously mapped. Big data analysis, machine learning, and AI algorithms are used to identify the sources, types, and distribution patterns of pollutants, predict development trends, evaluate the performance of cleaning equipment, predict faults, and generate maintenance suggestions; based on the analysis results, optimized cleaning strategies are dynamically generated (such as adjusting equipment working time, path, and intensity), and control commands are triggered. Commands from the decision module are received to remotely control cleaning robots, scrapers, sludge pumps, and other equipment to perform automated operations; real-time monitoring of equipment operating status ensures safe and efficient execution of cleaning tasks. The tunnel model, real-time data, pollutant distribution, and cleanup progress are displayed intuitively through a 3D visualization interface; human-computer interaction is supported: users can remotely view images / videos, adjust parameters, query historical data, and support collaborative operations among multiple departments.

[0066] It is worth noting that the entire device is controlled by a master control button. Since the device matched with the control button is a common device and belongs to existing mature technology, its electrical connection relationship and specific circuit structure will not be described in detail here.

[0067] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A digital twin-based intelligent monitoring system for water intake and drainage tunnels, characterized in that: It includes a data acquisition module, a digital twin model construction module, a data analysis and decision-making module, a cleaning equipment control module, and a visualization and interaction module; The data acquisition module is used to collect water quality, flow rate, equipment status and image data in the tunnel in real time. The digital twin model building module is used to build and dynamically update a three-dimensional virtual model of the tunnel; The data analysis and decision-making module is used to analyze data and generate cleaning strategies through machine learning algorithms. The cleaning equipment control module is used to automatically control the cleaning equipment to perform cleaning operations; The visualization and interaction module is used to provide a three-dimensional visualization interface and human-computer interaction functions.

2. The intelligent pollution monitoring system for water intake and drainage tunnels based on digital twins as described in claim 1, characterized in that, The data acquisition module includes sensors installed inside the water intake and drainage tunnel, including water quality sensors, flow sensors, liquid level sensors, image sensors, and equipment status sensors.

3. The intelligent pollution monitoring system for water intake and drainage tunnels based on digital twins according to claim 2, characterized in that, The water quality sensor is used to monitor water quality indicators, including pH, turbidity, dissolved oxygen, etc.; the flow sensor is used to monitor water flow velocity and flow rate; the liquid level sensor is used to monitor water level height; the image sensor, such as a high-definition camera, is used to capture images and videos inside the tunnel to monitor the distribution and accumulation of pollutants; and the equipment status sensor is used to monitor the operating parameters of the cleaning equipment, including motor speed and power.

4. The intelligent pollution monitoring system for water intake and drainage tunnels based on digital twins according to claims 2-3, characterized in that, The sensors collect tunnel operation data and environmental information in real time and transmit the data to the data processing center via wired or wireless communication networks.

5. The intelligent pollution monitoring system for water intake and drainage tunnels based on digital twins according to claim 1, characterized in that, The digital twin model construction module utilizes computer simulation technology to construct a virtual digital twin model that perfectly maps to the physical tunnel, based on the design drawings, geological exploration data, and construction records of the water intake and drainage tunnel. This model includes static information such as the tunnel's geometry, internal structure, and material properties, while also reflecting the tunnel's dynamic operating status in real time, including water flow conditions, pollutant distribution, and the working status of cleaning equipment. Furthermore, by continuously updating the data in the model, it ensures a high degree of consistency between the digital twin model and the physical tunnel.

6. The intelligent pollution monitoring system for water intake and drainage tunnels based on digital twins according to claim 1, characterized in that, The data analysis and decision-making module performs in-depth analysis on the collected real-time data and data in the digital twin model. The analysis method includes the following steps: S1. Utilize big data analysis, machine learning, and artificial intelligence algorithms to identify the sources, types, distribution patterns, and development trends of pollutants; S2. Evaluate the operating efficiency and performance of the cleaning equipment and predict potential equipment failures; S3. Based on the analysis results, combined with preset rules and optimization objectives, generate cleaning plans and equipment control instructions; automatically adjust the working time, intensity, and path of the cleaning equipment according to water quality changes and pollutant accumulation; and promptly issue early warning information and provide maintenance suggestions when equipment abnormalities are detected.

7. The intelligent pollution monitoring system for water intake and drainage tunnels based on digital twins according to claim 1, characterized in that, The cleaning equipment control module remotely controls the cleaning equipment in the water intake and drainage tunnel according to the control commands generated by the data analysis and decision-making module. The cleaning equipment includes, but is not limited to, cleaning robots, sludge scrapers, and sludge pumps. By precisely controlling the operation of the cleaning equipment, automated cleaning operations are achieved, improving cleaning efficiency and quality. At the same time, the working status of the cleaning equipment is monitored in real time to ensure the safe and stable operation of the equipment.

8. The intelligent pollution monitoring system for water intake and drainage tunnels based on digital twins according to claim 1, characterized in that, The visualization and interaction module presents the digital twin model, monitoring data, analysis results, and pollution control plan information to users in an intuitive and visual way, specifically including: Using 3D visualization technology, a virtual model of the water intake and drainage tunnel is presented on the computer screen, and users can view, operate and control it in real time through an interactive interface; Users can remotely view real-time images and videos inside the tunnel to understand the progress of pollutant cleanup; Adjust the cleaning and decontamination plan and equipment parameters; query historical data and analysis reports; This module supports simultaneous online collaboration among multiple users, facilitating information sharing and communication between different departments and personnel.

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