Intelligent detection platform for pipe gallery

Abstract

This application discloses a smart inspection platform for underground utility tunnels, relating to the field of safety monitoring technology for urban underground integrated utility tunnels. The tunnel monitoring component is used to: deploy multi-dimensional sensors through an IoT sensing layer to collect real-time data on tunnel structure, environment, equipment operation, and water quality; collect inspection data from inspection equipment and edge computing devices; and upload this data to a data processing center. The data processing center is used to: store, organize, aggregate, integrate, analyze, and monitor the data, and construct a risk assessment model. The operational monitoring system is used to: display the data in real-time in three dimensions using digital twin technology; call the risk assessment model and combine it with the data to perform risk prediction and obtain risk assessment results; then, combine the collected data to issue anomaly alarms; and determine emergency plans based on the risk assessment results. This application can significantly improve the intelligent management level of the entire life cycle of utility tunnels, realizing a shift from a passive response to a proactive prevention management model.

Description

Technical Field

[0001] This application relates to the field of safety monitoring technology for urban underground utility tunnels, and in particular to a smart monitoring platform for utility tunnels. Background Technology

[0002] Traditional utility tunnel systems still rely on manual inspection methods, which generally face prominent problems such as aging and disrepair of pipelines, significant structural safety hazards, frequent operational failures, and high maintenance costs. In a utility tunnel environment, sudden accidents such as leaks, pipe bursts, power outages, or structural collapses can easily pose a serious threat to the safety of the surrounding environment. Therefore, accelerating the construction of an intelligent utility tunnel safety monitoring system to comprehensively improve operational management efficiency and emergency response capabilities has become an urgent task in the field of urban infrastructure construction. Summary of the Invention

[0003] The purpose of this application is to provide a smart inspection platform for utility tunnels, which can significantly improve the level of intelligent management throughout the entire life cycle of utility tunnels and realize the transformation of management mode from passive response to proactive prevention.

[0004] To achieve the above objectives, this application provides the following solution.

[0005] A smart inspection platform for utility tunnels includes utility tunnel monitoring components, a data processing center, and an operational monitoring system; The utility tunnel monitoring component is used to: deploy multi-dimensional sensors through the Internet of Things (IoT) sensing layer and collect utility tunnel structure data, utility tunnel environmental data, equipment operation data, and water quality data in real time; collect utility tunnel inspection data from inspection equipment and edge computing devices; and upload the utility tunnel structure data, utility tunnel environmental data, water quality data, equipment operation data, and utility tunnel inspection data as raw collected data to the data processing center in real time. The data processing center is used for: storing, organizing, aggregating, integrating, analyzing, and monitoring the raw collected data to obtain environmental change and equipment operation data; and constructing a risk assessment model. The business monitoring system is used to: use digital twin technology to display the original collected data and the environmental changes and equipment operation data in real time in three dimensions; call the risk assessment model, combine the original collected data and the environmental changes and equipment operation data to perform risk prediction and obtain risk assessment results; combine the risk assessment results, the original collected data and the environmental changes and equipment operation data to generate abnormal alarms; and determine emergency plans based on the risk assessment results.

[0006] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application deploys multi-dimensional sensors through the IoT sensing layer and collects real-time data on the pipe gallery structure, environment, equipment operation, and water quality; it also collects pipe gallery inspection data from inspection equipment and edge computing devices. The collection of these various data sources ensures a rich and sufficient data foundation for subsequent processing. The collected data is processed and managed by the data processing center, and then a high-precision virtual mapping model of the physical pipe gallery is constructed in the business monitoring system based on digital twin technology, achieving dynamic fusion and display of data and three-dimensional scenes. Furthermore, a risk assessment model is used to perform real-time analysis and risk prediction on multi-source data to obtain risk assessment results. Based on the risk assessment results, anomaly alarms are triggered and emergency plans are determined. Thus, this application integrates the IoT sensing layer, digital twin, and dynamic risk assessment to form a "perception-modeling-assessment-early warning" technical collaborative mechanism, which can significantly improve the intelligent management level of the entire life cycle of the pipe gallery and realize a shift from a passive response to a proactive prevention management model. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0008] Figure 1 This is a schematic diagram of a smart inspection platform for utility tunnels in one embodiment of this application. Detailed Implementation

[0009] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0010] This application provides a "1+5+N" platform architecture, namely: one center, five systems, and N sensors. The one center refers to a data center responsible for collecting, cleaning, managing, and analyzing data generated by all sensors, information systems, edge computing devices, and personnel. The five systems refer to five smart construction project emergency management platform systems, including: basic information management, a 3D visualization and analysis system, a comprehensive risk assessment system, a real-time monitoring and alarm system, and an emergency auxiliary decision-making system. The N sensors refer to fixed-point monitoring equipment, intelligent inspection equipment, edge computing devices, etc., integrated within the construction project.

[0011] This application is based on technologies such as the Internet of Things, cloud computing, big data, and mobile internet, and comprehensively utilizes sensing, GIS, BIM, and other methods to form a comprehensive monitoring platform for utility tunnels, integrating functions such as comprehensive monitoring, operation, data application, and emergency command. This application can also provide historical sensor information and, combined with artificial intelligence analysis results, provide data-driven decision-making support for managers.

[0012] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0013] In one exemplary embodiment, such as Figure 1 As shown, a smart inspection platform for utility tunnels is provided, including utility tunnel monitoring components, a data processing center, and a business monitoring system.

[0014] (i) The utility tunnel monitoring component is used to: deploy multi-dimensional sensors through the Internet of Things sensing layer and collect utility tunnel structure data, utility tunnel environment data, equipment operation data and water quality data in real time; collect utility tunnel detection data from inspection equipment and edge computing equipment; and upload the utility tunnel structure data, utility tunnel environment data, water quality data, equipment operation data and utility tunnel detection data as raw collected data to the data processing center in real time.

[0015] In a specific application, the multi-dimensional sensors are used for fixed-point monitoring, including sensors for monitoring the pipe gallery structure, sensors for monitoring the pipe gallery environment, sensing components for monitoring equipment operation, and sensors for monitoring water quality. Specifically, appropriate fixed-point monitoring equipment, such as temperature sensors, humidity sensors, gas sensors, and water level sensors, is selected according to actual needs. The fixed-point monitoring equipment is rationally arranged to ensure comprehensive monitoring of environmental parameters and equipment operating status within the pipe gallery. Furthermore, the fixed-point monitoring equipment is regularly calibrated and maintained to ensure its accuracy and reliability.

[0016] The multi-dimensional sensors used in this application include non-vibrating wire RS485 sensors and vibrating wire sensors, which collect raw data of physical quantities (such as pressure, temperature, displacement, etc.) on site.

[0017] After acquiring raw physical quantity data, the non-vibrating wire RS485 sensor transmits the data directly to the gateway at the transmission layer via the RS485 bus according to its own communication protocol. Upon receiving the data, the gateway performs protocol conversion (e.g., converting Modbus RTU to MQTT or Modbus TCP), and then sends the data to the data processing center via network transmission (Ethernet or 4G, etc.). When selecting a non-vibrating wire sensor with appropriate range and accuracy based on monitoring requirements, it is crucial to pay close attention to its communication parameters, including baud rate (commonly 9600bps, 19200bps, etc.), parity bits (e.g., no parity, odd parity, even parity), data bits, and stop bits, ensuring they match the RS485 interface parameters of the gateway. Simultaneously, products with good stability and anti-interference capabilities should be selected to adapt to complex field environments.

[0018] The vibrating wire sensor acquires the raw frequency signal and transmits it to the MCU. The MCU processes and converts the raw frequency signal into digital data that the gateway can recognize. The converted data is then transmitted to the gateway via the MCU's UART or RS485 interface. After receiving the data, the gateway performs protocol conversion and then sends the data to the data processing center via the network. The selection of a vibrating wire sensor depends on the type and range of the physical quantity being monitored, taking into account its excitation method (e.g., pulse excitation, sinusoidal excitation) and signal characteristics (output signal is a frequency signal). When selecting a sensor, emphasis should be placed on its measurement accuracy, long-term stability, and environmental adaptability to ensure accurate data acquisition under different operating conditions.

[0019] Specifically, in terms of monitoring the structure of utility tunnels, the sensors include: Differential pressure static level is used to monitor the overall and segmental settlement of the utility tunnel. Laser rangefinder is used to monitor the deformation of the utility tunnel structure. Inclinometer is used to monitor the tilt angle of the utility tunnel structure. Displacement gauge is used to monitor the relative / absolute displacement of predetermined parts of the utility tunnel structure. Vibrating wire strain gauge is used to monitor the internal forces and material stress state of the utility tunnel structure. Fixed crack gauge is used to monitor the opening, closing, and propagation of cracks in the utility tunnel structure.

[0020] In terms of environmental monitoring of utility tunnels, sensors include: A temperature and humidity meter is used to monitor the temperature and humidity values ​​within the utility tunnel in real time. A level gauge is used to monitor the water depth within the utility tunnel in real time. A distributed fiber optic sensing monitoring system is used to locate anomalies; these anomalies at least refer to cable overheating or thermal pipeline leaks, and the specific nature of the anomalies can be defined as needed. A composite gas detector and alarm is used to monitor the concentration of toxic gases within the utility tunnel.

[0021] In terms of equipment operation monitoring, the sensing components include: The gateway monitors whether the device is online; the signal strength sensor monitors the signal strength in real time; and the MCU or battery module monitors the battery level in real time.

[0022] In water quality monitoring, sensors include: Water quality analyzers are used to monitor indicators such as pH, dissolved oxygen, turbidity, and suspended solids in water resources.

[0023] The inspection equipment includes both automated and manual inspection devices. The automated inspection equipment must be intelligent and possess functions such as autonomous navigation, automatic obstacle avoidance, automatic early warning, path planning, a lifting platform, visual analysis, data acquisition (e.g., infrared temperature measurement, noise detection), and remote control. An inspection plan should be developed as needed, and the intelligent inspection equipment should be scheduled to conduct regular inspections of the utility tunnel. During the inspection, the automated inspection equipment will automatically collect various data within the utility tunnel (data collection settings will be configured as needed) and transmit the collected data to the data processing center. Furthermore, the intelligent inspection equipment will be maintained and managed to ensure its normal operation.

[0024] In a specific application, the automated inspection equipment of this application mainly consists of an explosion-proof wheeled inspection robot, a power supply platform, a communication platform, and backend software. Through this platform, the robot can be managed and controlled in real time to perform online inspection tasks. Simultaneously, the inspection status and results can be transmitted from the robot itself to the backend software, allowing for immediate communication with on-site personnel. An inspection report can be generated upon completion of the inspection. Information such as the robot's inspection footage and results can be shared with management departments in real time, enabling remote monitoring and management of the robot's status.

[0025] The edge computing devices are deployed within the utility tunnel to locally process and analyze the data collected by the multi-dimensional sensors, obtaining aggregated features and statistical data, which are then labeled as utility tunnel detection data. Edge computing devices can reduce data transmission volume and improve the real-time performance of data processing. They can communicate with the data processing center, uploading processed data and receiving instructions and updates from the center to configure and manage the devices, ensuring they meet the operational and maintenance needs of the utility tunnel.

[0026] In a practical application, the platform also includes a conversion layer and a transmission layer between the utility tunnel monitoring component and the data processing center.

[0027] The conversion layer is used to convert the raw acquired data output by the pipe gallery monitoring component into a data format and upload it to the transmission layer. Specifically, the conversion layer, taking into account the signal characteristics of the vibrating wire sensor, sets up a microcontroller unit (MCU) to convert the raw signal output by the vibrating wire sensor into a data format that can be recognized by the gateway. In application, an MCU with suitable interface and processing capabilities should be selected. It should have an analog-to-digital conversion interface to acquire the raw frequency signal of the vibrating wire sensor, and a UART (Universal Asynchronous Receiver / Transmitter) or RS485 interface for transmitting the converted data to the gateway. The MCU's processing speed should meet the real-time requirements of data conversion, and it should have a certain degree of anti-interference capability and low power consumption to adapt to long-term stable operation in the field.

[0028] The transmission layer deploys gateway devices to upload data from the conversion layer to the data processing center. Specifically, the transmission layer acts as an intermediate node for data transmission, receiving direct data from non-vibrating wire RS485 sensors and vibrating wire sensor data converted by the MCU, and transmitting the data to the data processing center. The gateway supports an RS485 interface to connect with both the non-vibrating wire RS485 sensors and the vibrating wire sensor data converted by the MCU. It also features network transmission capabilities, allowing selection of gateways supporting Ethernet, 4G, and other transmission methods based on the site's network environment. The gateway should also have data caching and protocol conversion functions to ensure stable and efficient data transmission to the server, and support multi-interface expansion to accommodate future additions of different sensor types.

[0029] (ii) The data processing center is used to: store and organize, collect and integrate, analyze and monitor the raw collected data to obtain environmental change and equipment operation data; and to build a risk assessment model.

[0030] The data processing center is a service layer, consisting of servers, that receives data transmitted from the gateway. After receiving the raw collected data, the data processing center runs preset algorithms to process the data, including filtering, calibration, and feature extraction. The processed valid data is transmitted to the business monitoring system and displayed in real time in the form of charts, numerical values, etc., and alarms are triggered when the data exceeds the limits.

[0031] In a specific application, the data processing center includes a data acquisition and transmission module, a data storage and management module, a data collection and integration module, a data analysis and monitoring module, and an algorithm management module.

[0032] The data acquisition and transmission module is used to transmit the raw collected data to the data storage and management module in real time. Specifically, various sensors (such as temperature sensors, humidity sensors, gas sensors, etc.), information systems (such as monitoring systems, communication systems, etc.), edge computing devices, and inspection devices are deployed in the smart utility tunnel. These devices transmit the collected data to the data acquisition and transmission module of the data processing center in real time via wired or wireless means. For the automatic inspection devices in the inspection equipment, various data in the utility tunnel can be automatically collected during the inspection process and transmitted to the data acquisition and transmission module via a wireless network.

[0033] The data storage and management module is used to classify, organize, and store the raw collected data. Specifically, high-performance data storage devices, such as distributed storage systems or cloud storage services, are used to ensure the storage capacity of large amounts of pipeline corridor data. The data storage and management module classifies, organizes, and stores the collected data for subsequent querying, analysis, and processing. This application also implements data backup and recovery strategies to ensure data security and reliability.

[0034] The data collection and integration module is used to: collect and integrate the raw collected data using data integration technology, based on different data sources; wherein, different data sources include different sensors, information systems, and devices. The integration process includes at least data cleaning, transformation, and standardization to ensure data consistency and usability. Furthermore, a data warehouse or data lake is established to store the integrated data for further analysis and mining.

[0035] The data analysis and monitoring module is used to: utilize data analysis tools and algorithms to analyze the data output by the data collection and integration module, extracting valuable information, namely environmental changes and equipment operation data. For example, sensor data can be analyzed to monitor environmental changes and equipment operating status within the utility tunnel. Based on the analysis results, decision support is provided for the operation and maintenance management of the utility tunnel, such as predicting equipment failures and optimizing inspection routes.

[0036] The algorithm management module is used to construct a risk assessment model. Specifically, the algorithm management module incorporates a variety of operators, with up to 100 basic operators in this application. These operators include at least the mean squared error operator, SQL operator, XGB operator, Vicuna operator, and ChatGLM operator.

[0037] The algorithm management module is used to: display all the operators to the user; receive algorithms obtained by the user through operator combination, especially supporting the user to combine operators into algorithms by "drag and drop"; these algorithms can process data, such as filtering, calibration, feature extraction, etc.; retrieve risk assessment algorithms from all algorithms; and construct risk assessment models based on the risk assessment algorithms.

[0038] In one application, within the algorithm management module, a risk assessment model is constructed based on the risk assessment algorithm, including: 1) Retrieve historical data and corresponding historical risk assessment results to construct training sample data.

[0039] 2) Load the risk assessment algorithm obtained by combining XGB operators and build the initial model.

[0040] 3) The initial model is trained using the training sample data to obtain a risk assessment model. Thus, this application has trained an intelligent model capable of capturing key features leading to risk. In subsequent processing, the trained model can be used to analyze the data and intelligently predict potential future risks and trends. Based on the results of the intelligent prediction, countermeasures can be planned and implemented in advance to mitigate or avoid the impact of potential risks.

[0041] (III) The business monitoring system is used to: display the original collected data and the environmental changes and equipment operation data in real time in three dimensions using digital twin technology; call the risk assessment model, combine the original collected data and the environmental changes and equipment operation data to perform risk prediction and obtain risk assessment results; combine the risk assessment results, the original collected data and the environmental changes and equipment operation data to perform abnormal alarms; and determine emergency plans based on the risk assessment results.

[0042] The business monitoring system is an application layer system that receives valid data processed by the server (i.e., the data processing center) and displays the data information to users in real time in the form of charts, alarms, digital twins, etc. The business monitoring system includes: a basic information management system, a 3D visualization and analysis system, a comprehensive risk assessment system, a real-time monitoring and alarm system, and an emergency auxiliary decision-making system.

[0043] The basic information management system is used to store and manage basic information about the utility tunnel, including its geographical location, structural parameters, equipment list, and maintenance records. The system provides functions for information entry, querying, modification, and deletion, facilitating management of the basic information by administrators (i.e., users). It also interacts with other systems to ensure the accuracy and timeliness of the basic information.

[0044] The 3D visualization and analysis system is used to: construct a 3D model of the utility tunnel based on its basic information using digital twin technology, intuitively displaying the tunnel's structure and layout; and integrate the original collected data, environmental changes, and equipment operation data with the 3D model to achieve real-time 3D visualization. For example, temperature distribution and equipment operating status can be displayed on the 3D model. The system also provides analysis tools, such as spatial analysis and path analysis, to assist managers in the planning, design, and operation and maintenance of the utility tunnel.

[0045] The emergency decision support system is used to: store and update an emergency plan database; the emergency plan database includes emergency plans and handling procedures for various emergencies. When an emergency occurs, the emergency decision support system automatically invokes the corresponding emergency plan based on the type and severity of the event and provides decision support. For example, it can provide suggestions on emergency resource allocation and personnel evacuation route planning. The emergency decision support system can work collaboratively with other systems, such as real-time monitoring and alarm systems and communication systems, to ensure the efficiency and accuracy of emergency response.

[0046] The comprehensive risk assessment system is used to: invoke the risk assessment model; input the original collected data and the environmental change and equipment operation data into the risk assessment model to obtain the probability of risk occurrence and the degree of impact, and mark them as risk assessment results; and, based on the risk assessment results, invoke the corresponding emergency plan from the emergency plan database.

[0047] Specifically, the comprehensive risk assessment system collects data on various risk factors within the utility tunnel, such as fire risk, flooding risk, and equipment failure risk. It then uses a risk assessment model to evaluate and analyze the overall risk of the utility tunnel. This model can consider factors such as the probability of risk occurrence and the degree of impact. Based on the risk assessment results, corresponding risk control measures and emergency plans are developed to improve the safety of the utility tunnel.

[0048] The real-time monitoring and alarm system is used to: combine the risk assessment results, the original collected data, and the environmental changes and equipment operation data to detect numerical anomalies; when a numerical anomaly is detected, an alarm signal is generated and an alarm is triggered.

[0049] Specifically, the real-time monitoring and alarm system connects to various sensors within the utility tunnel to monitor environmental parameters and equipment operating status in real time. When an abnormality is detected, an alarm signal is automatically issued to notify management personnel for timely handling. The alarm signals can be triggered via sound, SMS, or email. The system also provides alarm recording and query functions, facilitating the tracking and handling of alarm events by management personnel.

[0050] Alarm handling methods include online and offline methods.

[0051] Online: Upon receiving alarm information, online processing is required. For alarms confirmed as false alarms, the alarm can be deactivated online after verification. For alarms requiring on-site confirmation or resolution, online dispatch is supported, allowing manual or automatic selection of personnel for handling, and the dispatch information is pushed to the maintenance personnel's mobile app to guide them in handling the alarm offline.

[0052] Offline: After receiving an alarm, maintenance personnel will handle it offline. Once the alarm is resolved, the personnel can directly report the results on their mobile devices and take photos for documentation. For alarms that cannot be resolved on their own, other responsible personnel can be assigned to assist in the resolution.

[0053] In a specific application, the business monitoring system is also used to: receive event feedback from users after the emergency plan is completed, and store the original collected data and the corresponding environmental changes and equipment operation data, risk assessment results, emergency plan, and event feedback as an instance in the data processing center, while generating logs.

[0054] Specifically, in the event of an emergency, the emergency center can coordinate with on-site personnel for emergency command. The emergency command center needs to observe the surrounding situation from a global perspective, review the corresponding emergency plans, and direct on-site personnel to resolve the emergency through audio and video calls. After the emergency is resolved, an event summary report can be completed through the business monitoring system to close the emergency case.

[0055] In summary, this application can centrally collect information from multiple sources, such as power supply systems in utility tunnels, smoke detectors, drainage and smoke extraction systems, ambient temperature and humidity, combustible gas detection, access control, intrusion detection, and video data. Based on a risk assessment algorithm combined with historical sensor information, a risk assessment model is trained. By combining real-time sensor data with artificial intelligence analysis results, the model dynamically assesses the potential risks posed by current real-time data, providing managers with data-driven decision-making support. Once any anomaly is detected, such as equipment malfunction, environmental anomalies, or security incidents, the intelligent management platform will immediately push relevant alarm signals.

[0056] In a specific application, based on the intelligent utility tunnel inspection platform provided in this application, a mobile inspection tool can also be provided. This mobile inspection tool includes a situation overview function, an offline handling function, an inspection and maintenance function, and an emergency command function.

[0057] The overall situation overview function provides users with a comprehensive overview of the project's equipment and operational status. The mobile interface clearly displays key data such as the total number of devices, the normal operation rate, the total number of alarms, and the total number of faults. It also presents the current system health through an intuitive dashboard and uses pie charts to show the distribution of alarms under different categories such as reservoirs and dams, hydrology and water resources, buildings, and foundation pits. This allows users to quickly grasp the overall operational status of the project and provides data support for decision-making.

[0058] The offline handling function focuses on pending alarm events. The mobile interface lists alarm information from devices such as foundation pit earth pressure gauges and reservoir flow meters, including alarm time and specific descriptions, allowing users to quickly understand the issues requiring offline handling and thus rapidly organize personnel for on-site handling, ensuring the normal operation of project-related equipment and systems.

[0059] The inspection and maintenance function is mainly used for equipment inspection and maintenance management. The mobile interface displays information about different maintenance tasks, including the task name, start and end time, total number of equipment to be maintained, and number of equipment that has been maintained. The task is marked as "in progress," which helps users to organize equipment inspection and maintenance work in an orderly manner and ensure that the equipment is always in good operating condition.

[0060] The emergency command function revolves around emergency events and drills. The mobile interface displays records of completed emergency events and drills, allowing users to view these records, summarize experiences, and thus quickly and effectively command and dispatch resources in the face of real emergency situations, thereby improving the project's ability to respond to emergencies.

[0061] Compared with the prior art, this application has the following advantages: (1) This application employs advanced distributed fiber optic sensor technology, twin technology, and risk assessment algorithms, which can capture even the smallest signs of gas leaks and other risks, ensuring timely detection and action before risks occur. This intelligent detection method significantly improves detection efficiency and accuracy, while also reducing the complexity and cost of manual detection.

[0062] (2) Compared with traditional cloud computing, this application adopts edge computing, which brings revolutionary changes to data processing with lower cost, shorter latency, higher data privacy protection and stronger concurrent processing capabilities. By using edge computing, the data processing process is optimized, and the response speed and efficiency are improved, providing a solid foundation for realizing intelligent and automated monitoring and management, and is the key to building an efficient and reliable smart utility tunnel system.

[0063] (3) In terms of scene presentation, this application focuses on the accurate restoration of dynamic scenes throughout the entire lifecycle. Unlike traditional 3D models that can only present the state at a single time point, this application can present complex patterns in a "perceptible and predictable" way based on historical trend data after data aggregation and processing and real-time collected data. The 3D visualization technology used in this application realizes the functional innovation from "passive display" to "active decision-making" and constructs an interactive digital management scene. By integrating data analysis algorithms and 3D interactive functions, managers can directly perform data queries, trend analysis and simulation in the 3D scene.

[0064] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0065] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A smart inspection platform for utility tunnels, characterized in that, The platform includes a utility tunnel monitoring component, a data processing center, and a business monitoring system. The utility tunnel monitoring component is used to: deploy multi-dimensional sensors through the Internet of Things (IoT) sensing layer and collect utility tunnel structure data, utility tunnel environmental data, equipment operation data, and water quality data in real time; collect utility tunnel inspection data from inspection equipment and edge computing devices; and upload the utility tunnel structure data, utility tunnel environmental data, water quality data, equipment operation data, and utility tunnel inspection data as raw collected data to the data processing center in real time. The data processing center is used for: storing, organizing, aggregating, integrating, analyzing, and monitoring the raw collected data to obtain environmental change and equipment operation data; and constructing a risk assessment model. The business monitoring system is used to: use digital twin technology to display the original collected data and the environmental changes and equipment operation data in real time in three dimensions; call the risk assessment model, combine the original collected data and the environmental changes and equipment operation data to perform risk prediction, and obtain risk assessment results; Based on the risk assessment results, the original collected data, and the environmental changes and equipment operation data, an anomaly alarm is triggered; Based on the risk assessment results, an emergency response plan will be determined.

2. The intelligent inspection platform for utility tunnels according to claim 1, characterized in that, The multi-dimensional sensors are for fixed-point monitoring, including sensors for monitoring the pipe gallery structure, sensors for monitoring the pipe gallery environment, sensing components for monitoring equipment operation, and sensors for monitoring water quality. The inspection equipment includes automatic inspection equipment and manual inspection equipment; The edge computing device is used to process and analyze the data collected by the multi-dimensional sensors locally, obtain aggregated features and statistical data, and label them as pipeline inspection data.

3. The intelligent inspection platform for utility tunnels according to claim 1, characterized in that, The data processing center includes a data acquisition and transmission module, a data storage and management module, a data collection and integration module, a data analysis and monitoring module, and an algorithm management module; The data acquisition and transmission module is used to: transmit the raw collected data to the data storage and management module in real time; The data storage and management module is used to classify, organize, and store the raw collected data. The data collection and integration module is used to: collect and integrate the original collected data using data integration technology, based on different data sources; wherein, the integration process includes at least data cleaning, transformation, and standardization. The data analysis and monitoring module is used to: use data analysis tools and algorithms to analyze the data output by the data collection and integration module, and extract environmental change and equipment operation data; The algorithm management module is used to: build risk assessment models.

4. The intelligent inspection platform for utility tunnels according to claim 1, characterized in that, The business monitoring system includes: a basic information management system, a 3D visualization and analysis system, a comprehensive risk assessment system, a real-time monitoring and alarm system, and an emergency auxiliary decision-making system; The basic information management system is used to: store and manage basic information about the utility tunnel; The three-dimensional visualization and analysis system is used to: construct a three-dimensional model of the utility tunnel based on the basic information of the utility tunnel using digital twin technology; and integrate the original collected data and the environmental change and equipment operation data with the three-dimensional model of the utility tunnel to achieve real-time three-dimensional visualization. The emergency decision support system is used to: store and update the emergency response plan database; The comprehensive risk assessment system is used to: invoke the risk assessment model; input the original collected data and the environmental change and equipment operation data into the risk assessment model to obtain the probability of risk occurrence and the degree of impact, and mark them as risk assessment results; and, based on the risk assessment results, invoke the corresponding emergency plan from the emergency plan database. The real-time monitoring and alarm system is used to: combine the risk assessment results, the original collected data, and the environmental changes and equipment operation data to detect numerical anomalies; when a numerical anomaly is detected, an alarm signal is generated and an alarm is triggered.

5. The intelligent inspection platform for utility tunnels according to claim 2, characterized in that, In terms of monitoring the structure of utility tunnels, the sensors include: Differential pressure hydrostatic level is used to monitor the overall and segmental settlement of the utility tunnel; Laser rangefinders are used to monitor the deformation of pipe gallery structures; Inclinometers are used to monitor the tilt angle of utility tunnel structures. Displacement gauges are used to monitor the relative / absolute displacement of predetermined parts of the pipe gallery structure; Vibrating wire strain gauges are used to monitor the internal forces and material stress state of pipe gallery structures. Fixed crack gauges are used to monitor the opening, closing, and development of cracks in pipe gallery structures; In terms of environmental monitoring of utility tunnels, sensors include: A temperature and humidity meter is used to monitor the temperature and humidity values ​​inside the pipe gallery in real time. The level gauge is used to monitor the water depth in the pipe gallery in real time. A distributed fiber optic sensing and monitoring system is used to locate anomalies; the anomalies refer at least to cable overheating and thermal pipeline leakage. A composite gas detector and alarm is used to monitor the concentration of toxic gases in pipe racks; In water quality monitoring, sensors include: Water quality analyzers are used to monitor pH, dissolved oxygen, turbidity, and suspended solids in water resources.

6. The intelligent inspection platform for utility tunnels according to claim 1, characterized in that, The platform also includes a conversion layer and a transmission layer between the utility tunnel monitoring components and the data processing center. The conversion layer is used to convert the raw collected data output by the pipe gallery monitoring component into a data format and upload it to the transmission layer; The transport layer deploys gateway devices to upload data from the conversion layer to the data processing center.

7. The intelligent inspection platform for utility tunnels according to claim 3, characterized in that, The algorithm management module has a variety of built-in operators; these operators include at least the mean squared error operator, SQL operator, XGB operator, Vicuna operator, and ChatGLM operator. The algorithm management module is used to: display all the operators to the user; receive the algorithm obtained by the user through operator combination; retrieve the risk assessment algorithm from all the algorithms; and construct a risk assessment model based on the risk assessment algorithm.

8. The intelligent inspection platform for utility tunnels according to claim 7, characterized in that, In the algorithm management module, a risk assessment model is constructed based on the risk assessment algorithm, including: Retrieve historical data and corresponding historical risk assessment results to construct training sample data; Load the risk assessment algorithm obtained by combining XGB operators and build the initial model; The initial model is trained using the training sample data to obtain a risk assessment model.

9. The intelligent inspection platform for utility tunnels according to claim 4, characterized in that, In the real-time monitoring and alarm system, the alarm signals correspond to alert methods including sound alarms, SMS alarms, and email alarms.

10. The intelligent inspection platform for utility tunnels according to claim 1, characterized in that, The business monitoring system is also used to: receive event feedback from users after the emergency plan is completed, and store the original collected data and the corresponding environmental changes and equipment operation data, risk assessment results, emergency plan, and event feedback as an instance in the data processing center, while generating logs.

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