Intelligent pipeline state monitoring method, system and equipment based on CIM and medium

Abstract

The invention discloses a CIM-based pipeline state intelligent monitoring method, system and equipment and a medium, belongs to the technical field of urban infrastructure management, and aims to solve the technical problem of how to realize comprehensive, real-time and intelligent monitoring and management of the pipeline state of an underground pipe network, automatically analyze potential risks and abnormities and improve the management efficiency of the underground pipe network. In order to improve the management efficiency and level of the pipeline state of the underground pipe network, the adopted technical scheme is as follows: constructing a data acquisition and transmission network: constructing the data acquisition and transmission network by deploying multiple types of sensors along the pipeline, and obtaining and transmitting the real-time operation data of the pipeline; preprocessing data and constructing a model: preprocessing the pipeline operation data, and constructing a precise three-dimensional model of the pipeline by using a CIM (Common Information Model) technology; and intelligent analysis and prediction: in combination with big data analysis and data mining technologies, deep analysis and prediction of pipeline operation data are realized, and potential risks are identified and early warned.

Description

Technical Field

[0001] The present invention relates to the technical field of urban infrastructure management, and in particular to a CIM-based pipeline state intelligent monitoring method, system, equipment and medium. Background Art

[0002] Underground pipe network refers to the general term for various pipelines and their ancillary facilities buried underground, and is an important part of urban infrastructure. These pipe networks cover multiple key areas and subsystems, mainly including water supply, drainage, gas, heat, electricity, communications and other pipelines. Together, they constitute the skeleton of urban infrastructure and provide essential support for the normal operation of the city and the lives of residents.

[0003] With the acceleration of urbanization, the scale of underground pipeline networks is becoming increasingly large, and the monitoring and management of their operating status has become an important part of urban infrastructure management. However, the traditional manual inspection method has problems such as low efficiency, high cost, and slow response, which is difficult to meet the needs of modern urban management.

[0004] Therefore, how to achieve comprehensive, real-time, and intelligent monitoring and management of the status of underground pipelines, automatically analyze potential risks and anomalies, and improve the management efficiency and level of the status of underground pipelines is a technical problem that needs to be solved urgently. Summary of the invention

[0005] The technical task of the present invention is to provide a CIM-based intelligent pipeline status monitoring method, system, equipment and medium to solve the problem of how to achieve comprehensive, real-time and intelligent monitoring and management of underground pipeline network status, automatically analyze potential risks and anomalies, and improve the management efficiency and level of underground pipeline network status.

[0006] The technical task of the present invention is achieved in the following way: a CIM-based intelligent pipeline status monitoring method, the method is as follows:

[0007] Build a data collection and transmission network: Deploy multiple types of sensors along the pipeline to build a data collection and transmission network to obtain and transmit real-time pipeline operation data;

[0008] Data preprocessing and model building: preprocess the pipeline operation data and use CIM technology to build an accurate three-dimensional model of the pipeline;

[0009] Intelligent analysis and prediction: Combine big data analysis and data mining technology to achieve in-depth analysis and prediction of pipeline operation data, identify and warn of potential risks.

[0010] As a preferred method, the data collection and transmission network is constructed as follows:

[0011] Sensor network deployment: Various sensors are deployed at key locations along the underground pipeline to fully cover and monitor various operating data of the pipeline in real time; the sensors include temperature sensors, pressure sensors, flow sensors and vibration sensors;

[0012] Data collection and transmission: Each sensor is connected to the data collection terminal via wired or wireless means. The data collection terminal is used to collect sensor data, perform preliminary processing and packaging on the collected sensor data, and then transmit it to the data processing center in real time through a communication network (such as 4G / 5G, LoRa, NB-IoT, etc.).

[0013] Preferably, data preprocessing and model building are as follows:

[0014] Data processing center: Establish an efficient data processing center, which receives the collected sensor data and performs pre-processing operations such as data cleaning, denoising, compression and storage on the collected sensor data to ensure the quality and integrity of the data;

[0015] Build a CIM management platform: Use CIM technology to build an accurate three-dimensional model of the pipeline based on the information of the pipeline's geographical location, size, material and laying method; the accurate three-dimensional model of the pipeline includes the physical properties of the pipeline and is associated with the real-time operation data of the pipeline to achieve spatial display and analysis of the data.

[0016] Preferably, the intelligent analysis and prediction are as follows:

[0017] Data analysis and mining: Use big data analysis and data mining technology to conduct in-depth analysis of the processed pipeline operation data to identify the patterns, trends and anomalies in the data; and establish mathematical models and algorithms to predict the future operation status of the pipeline and assess potential risks and hidden dangers;

[0018] Intelligent early warning: Combine machine learning algorithms to build an intelligent early warning model; the intelligent early warning model automatically identifies abnormal conditions in pipeline operation, triggers the early warning process according to preset thresholds and rules, and sends early warning information to relevant personnel in a timely manner so that measures can be taken quickly; abnormal conditions in pipeline operation include abnormal pressure increase, sudden drop in flow rate and abnormal temperature.

[0019] Preferably, the method also deploys data monitoring software, pipeline management software, and mobile client applications;

[0020] The data monitoring software has the following specific functions:

[0021] ① Real-time data display: Display various operating parameters of the pipeline in real time in the form of charts and curves; the various operating parameters of the pipeline include temperature, pressure and flow;

[0022] ② Historical data query: Supports querying historical data by time period and parameter type conditions, which is convenient for trend analysis and troubleshooting;

[0023] ③Alarm and notification: When an abnormal situation is detected, the alarm mechanism is automatically triggered and relevant personnel are notified through sound and pop-up windows;

[0024] The pipeline management software has the following functions:

[0025] ①Maintenance task management: According to the operation status and early warning information of the pipeline, a maintenance task list is automatically generated and assigned to relevant personnel for execution;

[0026] ②Task tracking and feedback: Track the execution of maintenance tasks, collect task execution results and feedback, and form a closed-loop management;

[0027] ③Statistical analysis report: regularly generate statistical analysis reports on pipeline operation status;

[0028] The mobile client application has the following specific functions:

[0029] ① Remote monitoring: remotely view the operation status and real-time data of the pipeline via mobile phone or tablet;

[0030] ②Task processing: Receive and process maintenance tasks assigned to you, including task review, execution records and result feedback;

[0031] ③Message notification: Receive message notifications from the system, including warning information and task assignment, to ensure timely communication of information.

[0032] A CIM-based intelligent pipeline status monitoring system, the system comprising:

[0033] The data collection layer is used to build a data collection and transmission network by deploying multiple types of sensors along the pipeline to obtain and transmit real-time pipeline operation data;

[0034] Data processing layer: used to pre-process pipeline operation data and build accurate 3D models of pipelines using CIM technology;

[0035] The intelligent analysis layer is used to combine big data analysis and data mining technology to achieve in-depth analysis and prediction of pipeline operation data, and identify and warn of potential risks.

[0036] Preferably, the system also includes data monitoring software, pipeline management software and mobile client applications;

[0037] The data monitoring software has the following specific functions:

[0038] ① Real-time data display: Display various operating parameters of the pipeline in real time in the form of charts and curves; the various operating parameters of the pipeline include temperature, pressure and flow;

[0039] ② Historical data query: Supports querying historical data by time period and parameter type conditions, which is convenient for trend analysis and troubleshooting;

[0040] ③Alarm and notification: When an abnormal situation is detected, the alarm mechanism is automatically triggered and relevant personnel are notified through sound and pop-up windows;

[0041] The pipeline management software has the following functions:

[0042] ①Maintenance task management: According to the operation status and early warning information of the pipeline, a maintenance task list is automatically generated and assigned to relevant personnel for execution;

[0043] ②Task tracking and feedback: Track the execution of maintenance tasks, collect task execution results and feedback, and form a closed-loop management;

[0044] ③Statistical analysis report: regularly generate statistical analysis reports on pipeline operation status;

[0045] The mobile client application has the following specific functions:

[0046] ① Remote monitoring: remotely view the operation status and real-time data of the pipeline via mobile phone or tablet;

[0047] ②Task processing: Receive and process maintenance tasks assigned to you, including task review, execution records and result feedback;

[0048] ③Message notification: Receive message notifications from the system, including warning information and task assignment, to ensure timely communication of information.

[0049] More preferably, the data collection layer includes:

[0050] The sensor network deployment module is used to deploy various sensors at key locations along the underground pipeline to fully cover and monitor various operating data of the pipeline in real time; the sensors include temperature sensors, pressure sensors, flow sensors and vibration sensors;

[0051] The data acquisition and transmission module is used to connect each sensor to the data acquisition terminal by wire or wireless means. The data acquisition terminal is used to collect sensor data, preliminarily process and package the collected sensor data, and then transmit it to the data processing center in real time through the communication network (such as 4G / 5G, LoRa, NB-IoT, etc.);

[0052] The data processing layer includes:

[0053] The data processing center establishment module is used to establish an efficient data processing center. The data processing center receives the collected sensor data and performs pre-processing operations such as data cleaning, denoising, compression and storage on the collected sensor data to ensure the quality and integrity of the data;

[0054] The CIM management platform construction module is used to build an accurate three-dimensional model of the pipeline based on the geographical location, size, material and laying method of the pipeline using CIM technology. The accurate three-dimensional model of the pipeline includes the physical properties of the pipeline and is associated with the real-time operation data of the pipeline to realize the spatial display and analysis of the data;

[0055] The intelligent analysis layer includes:

[0056] The data analysis and mining module is used to use big data analysis and data mining technology to conduct in-depth analysis of the processed pipeline operation data, identify the patterns, trends and anomalies in the data; and predict the future operation status of the pipeline and evaluate potential risks and hidden dangers by establishing mathematical models and algorithms;

[0057] The intelligent early warning module is used to build an intelligent early warning model in combination with a machine learning algorithm. The intelligent early warning model automatically identifies abnormal conditions in pipeline operation, triggers the early warning process according to preset thresholds and rules, and sends early warning information to relevant personnel in a timely manner so that measures can be taken quickly. Abnormal conditions in pipeline operation include abnormal pressure increase, sudden drop in flow rate, and abnormal temperature.

[0058] An electronic device comprising: a memory and at least one processor;

[0059] Wherein, the memory stores a computer program;

[0060] The at least one processor executes the computer program stored in the memory, so that the at least one processor executes the above-mentioned CIM-based intelligent pipeline status monitoring method.

[0061] A computer-readable storage medium stores a computer program, and the computer program can be executed by a processor to implement the CIM-based intelligent pipeline status monitoring method as described above.

[0062] The CIM-based intelligent pipeline status monitoring method, system, device and medium of the present invention have the following advantages:

[0063] (1) The present invention deploys multiple types of sensors along the pipeline to build an efficient data collection and transmission network to ensure the real-time acquisition and transmission of pipeline operation parameters, and uses CIM technology to build an accurate three-dimensional model of the pipeline. Combined with big data analysis and data mining technology, it realizes in-depth analysis and prediction of pipeline operation data, effectively identifies and warns of potential risks, and realizes comprehensive, real-time, and intelligent monitoring and management of underground pipeline status;

[0064] (ii) The present invention also provides intuitive data display, flexible historical data query, intelligent alarm and notification mechanism, and automated management and tracking feedback of maintenance tasks, providing users with a comprehensive pipeline management solution. At the same time, through mobile client applications, remote monitoring and task processing are realized, further improving the convenience and efficiency of pipeline management;

[0065] (III) The present invention utilizes the three-dimensional modeling and spatial analysis capabilities of CIM, combined with the Internet of Things, big data, cloud computing and artificial intelligence technologies, to achieve comprehensive, real-time and intelligent monitoring and management of underground pipeline status;

[0066] (IV) The present invention introduces CIM (city information modeling) technology, combines the Internet of Things, big data, cloud computing and artificial intelligence technology, and creates an efficient and intelligent pipeline status monitoring method. It can fully and real-time perceive the pipeline operation status, intuitively display the pipeline status through three-dimensional visualization, and automatically analyze potential risks and anomalies using intelligent algorithms, providing timely warnings and decision-making support for managers, thereby significantly improving the efficiency and accuracy of pipeline management and promoting the intelligentization of urban infrastructure management.

[0067] (V) The present invention realizes high-precision data collection and real-time transmission through a high-density sensor network, uses intelligent analysis algorithms to deeply mine pipeline operation data, and builds a real-time early warning system to ensure timely discovery and handling of abnormal situations. It not only provides managers with intelligent decision-making support tools and optimizes maintenance plans and emergency response strategies, but also realizes visual management and remote monitoring through a three-dimensional CIM model to improve management efficiency and flexibility. As a key part of smart city infrastructure management, the present invention has promoted the intelligent upgrade of urban infrastructure, promoted efficient resource utilization and environmental protection, and laid a solid foundation for the sustainable development of cities. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The present invention is further described below in conjunction with the accompanying drawings.

[0069] Attached Figure 1 This is a flowchart of the intelligent pipeline status monitoring method based on CIM. DETAILED DESCRIPTION

[0070] The CIM-based intelligent pipeline status monitoring method, system, device and medium of the present invention are described in detail below with reference to the accompanying drawings and specific embodiments.

[0071] Embodiment 1:

[0072] As attached Figure 1 As shown, this embodiment provides a CIM-based intelligent pipeline status monitoring method, the method is as follows:

[0073] S1. Build a data collection and transmission network: By deploying multiple types of sensors along the pipeline, build a data collection and transmission network to obtain and transmit real-time pipeline operation data;

[0074] S2. Data preprocessing and model building: Preprocess the pipeline operation data and use CIM technology to build an accurate three-dimensional model of the pipeline;

[0075] S3. Intelligent analysis and prediction: Combine big data analysis and data mining technology to achieve in-depth analysis and prediction of pipeline operation data, identify and warn of potential risks.

[0076] The construction of the data collection and transmission network in step S1 of this embodiment is specifically as follows:

[0077] S101. Sensor network deployment: Various sensors are deployed at key locations along the underground pipeline to fully cover and monitor various operating data of the pipeline in real time; the sensors include temperature sensors, pressure sensors, flow sensors and vibration sensors;

[0078] S102, data collection and transmission: Each sensor is connected to the data collection terminal via wired or wireless means. The data collection terminal is used to collect sensor data, and preliminarily processes and packages the collected sensor data, and then transmits it to the data processing center in real time through a communication network (such as 4G / 5G, LoRa, NB-IoT, etc.).

[0079] The data preprocessing and model building in step S2 of this embodiment are specifically as follows:

[0080] S201, Data Processing Center: Establish an efficient data processing center, which receives the collected sensor data and performs pre-processing operations such as data cleaning, denoising, compression and storage on the collected sensor data to ensure the quality and integrity of the data;

[0081] S202. Build a CIM management platform: Use CIM technology to build an accurate three-dimensional model of the pipeline based on the information of the pipeline's geographical location, size, material and laying method; the accurate three-dimensional model of the pipeline includes the physical properties of the pipeline and is associated with the real-time operation data of the pipeline to achieve spatial display and analysis of the data.

[0082] The intelligent analysis and prediction in step S3 of this embodiment are specifically as follows:

[0083] S301, Data Analysis and Mining: Use big data analysis and data mining technology to conduct in-depth analysis of the processed pipeline operation data, identify the patterns, trends and anomalies in the data; and predict the future operation status of the pipeline and assess potential risks and hidden dangers by establishing mathematical models and algorithms;

[0084] S302, Intelligent Early Warning: Build an intelligent early warning model in combination with machine learning algorithms; the intelligent early warning model automatically identifies abnormal conditions in pipeline operation, triggers the early warning process according to preset thresholds and rules, and sends early warning information to relevant personnel in a timely manner so that measures can be taken quickly; abnormal conditions in pipeline operation include abnormal pressure increase, sudden drop in flow rate and abnormal temperature.

[0085] In this embodiment, data monitoring software, pipeline management software and mobile client applications are also deployed;

[0086] The data monitoring software has the following specific functions:

[0087] ① Real-time data display: Display various operating parameters of the pipeline in real time in the form of charts and curves; the various operating parameters of the pipeline include temperature, pressure and flow;

[0088] ② Historical data query: Supports querying historical data by time period and parameter type conditions, which is convenient for trend analysis and troubleshooting;

[0089] ③Alarm and notification: When an abnormal situation is detected, the alarm mechanism is automatically triggered and relevant personnel are notified through sound and pop-up windows;

[0090] The pipeline management software has the following functions:

[0091] ①Maintenance task management: According to the operation status and early warning information of the pipeline, a maintenance task list is automatically generated and assigned to relevant personnel for execution;

[0092] ②Task tracking and feedback: Track the execution of maintenance tasks, collect task execution results and feedback, and form a closed-loop management;

[0093] ③Statistical analysis report: regularly generate statistical analysis reports on pipeline operation status;

[0094] The mobile client application has the following specific functions:

[0095] ① Remote monitoring: remotely view the operation status and real-time data of the pipeline via mobile phone or tablet;

[0096] ②Task processing: Receive and process maintenance tasks assigned to you, including task review, execution records and result feedback;

[0097] ③Message notification: Receive message notifications from the system, including warning information and task assignment, to ensure timely communication of information.

[0098] Embodiment 2:

[0099] This embodiment provides a CIM-based intelligent pipeline status monitoring system, which includes:

[0100] The data collection layer is used to build a data collection and transmission network by deploying multiple types of sensors along the pipeline to obtain and transmit real-time pipeline operation data;

[0101] Data processing layer: used to pre-process pipeline operation data and build accurate 3D models of pipelines using CIM technology;

[0102] The intelligent analysis layer is used to combine big data analysis and data mining technology to achieve in-depth analysis and prediction of pipeline operation data, and identify and warn of potential risks.

[0103] In this embodiment, the system also includes data monitoring software, pipeline management software and mobile client applications;

[0104] The data monitoring software has the following specific functions:

[0105] ① Real-time data display: Display various operating parameters of the pipeline in real time in the form of charts and curves; the various operating parameters of the pipeline include temperature, pressure and flow;

[0106] ② Historical data query: Supports querying historical data by time period and parameter type conditions, which is convenient for trend analysis and troubleshooting;

[0107] ③Alarm and notification: When an abnormal situation is detected, the alarm mechanism is automatically triggered and relevant personnel are notified through sound and pop-up windows;

[0108] The pipeline management software has the following functions:

[0109] ①Maintenance task management: According to the operation status and early warning information of the pipeline, a maintenance task list is automatically generated and assigned to relevant personnel for execution;

[0110] ②Task tracking and feedback: Track the execution of maintenance tasks, collect task execution results and feedback, and form a closed-loop management;

[0111] ③Statistical analysis report: regularly generate statistical analysis reports on pipeline operation status;

[0112] The mobile client application has the following specific functions:

[0113] ① Remote monitoring: remotely view the operation status and real-time data of the pipeline via mobile phone or tablet;

[0114] ②Task processing: Receive and process maintenance tasks assigned to you, including task review, execution records and result feedback;

[0115] ③Message notification: Receive message notifications from the system, including warning information and task assignment, to ensure timely communication of information.

[0116] The data collection layer in this embodiment includes:

[0117] The sensor network deployment module is used to deploy various sensors at key locations along the underground pipeline to fully cover and monitor various operating data of the pipeline in real time; the sensors include temperature sensors, pressure sensors, flow sensors and vibration sensors;

[0118] The data acquisition and transmission module is used to connect each sensor to the data acquisition terminal by wire or wireless means. The data acquisition terminal is used to collect sensor data, and preliminarily process and package the collected sensor data, and then transmit it to the data processing center in real time through the communication network (such as 4G / 5G, LoRa, NB-IoT, etc.).

[0119] The data processing layer in this embodiment includes:

[0120] The data processing center establishment module is used to establish an efficient data processing center. The data processing center receives the collected sensor data and performs pre-processing operations such as data cleaning, denoising, compression and storage on the collected sensor data to ensure the quality and integrity of the data;

[0121] The CIM management platform construction module is used to use CIM technology to build an accurate three-dimensional model of the pipeline based on the information of the pipeline's geographical location, size, material and laying method; among them, the accurate three-dimensional model of the pipeline includes the physical properties of the pipeline and is associated with the real-time operation data of the pipeline to realize the spatial display and analysis of the data.

[0122] The intelligent analysis layer in this embodiment includes:

[0123] The data analysis and mining module is used to use big data analysis and data mining technology to conduct in-depth analysis of the processed pipeline operation data, identify the patterns, trends and anomalies in the data; and predict the future operation status of the pipeline and evaluate potential risks and hidden dangers by establishing mathematical models and algorithms;

[0124] The intelligent early warning module is used to build an intelligent early warning model in combination with a machine learning algorithm. The intelligent early warning model automatically identifies abnormal conditions in pipeline operation, triggers the early warning process according to preset thresholds and rules, and sends early warning information to relevant personnel in a timely manner so that measures can be taken quickly. Abnormal conditions in pipeline operation include abnormal pressure increase, sudden drop in flow rate, and abnormal temperature.

[0125] Embodiment 3:

[0126] This embodiment also provides an electronic device, including: a memory and a processor;

[0127] Wherein, the memory stores computer-executable instructions;

[0128] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the CIM-based intelligent pipeline status monitoring method in any embodiment of the present invention.

[0129] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor may be a microprocessor or any conventional processor, etc.

[0130] The memory can be used to store computer programs and / or modules. The processor realizes various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the terminal, etc. In addition, the memory can also include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SMC), a secure digital (SD) card, a flash memory card, at least one disk storage period, a flash memory device, or other volatile solid-state storage devices.

[0131] Embodiment 4:

[0132] This embodiment also provides a computer-readable storage medium, in which a plurality of instructions are stored, and the instructions are loaded by a processor, so that the processor executes the CIM-based intelligent pipeline status monitoring method in any embodiment of the present invention. Specifically, a system or device equipped with a storage medium can be provided, on which a software program code that implements the functions of any of the above embodiments is stored, and a computer (or CPU or MPU) of the system or device reads and executes the program code stored in the storage medium.

[0133] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.

[0134] The storage medium embodiments for providing the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RYM, DVD-RW, DVD+RW), a magnetic tape, a non-volatile memory card, and a ROM. Alternatively, the program code can be downloaded from a server computer via a communication network.

[0135] In addition, it should be clear that the functions of any of the above embodiments can be implemented not only by executing the program code read by the computer, but also by enabling an operating system operating on the computer to complete part or all of the actual operations based on instructions from the program code.

[0136] In addition, it can be understood that the program code read from the storage medium is written to a memory provided in an expansion board inserted into the computer or written to a memory provided in an expansion unit connected to the computer, and then based on the instructions of the program code, a CPU installed on the expansion board or the expansion unit is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above-mentioned embodiments.

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A CIM-based intelligent pipeline status monitoring method, characterized in that: The method is as follows: Build a data collection and transmission network: Deploy multiple types of sensors along the pipeline to build a data collection and transmission network to obtain and transmit real-time pipeline operation data; Data preprocessing and model building: preprocess the pipeline operation data and use CIM technology to build an accurate three-dimensional model of the pipeline; Intelligent analysis and prediction: Combine big data analysis and data mining technology to achieve in-depth analysis and prediction of pipeline operation data, identify and warn of potential risks.

2. The CIM-based intelligent pipeline status monitoring method according to claim 1 is characterized in that: The details of building a data collection and transmission network are as follows: Sensor network deployment: Various sensors are deployed at key locations along the underground pipeline to fully cover and monitor various operating data of the pipeline in real time; the sensors include temperature sensors, pressure sensors, flow sensors and vibration sensors; Data collection and transmission: Each sensor is connected to the data collection terminal via wired or wireless means. The data collection terminal is used to collect sensor data, perform preliminary processing and packaging on the collected sensor data, and then transmit it to the data processing center in real time via the communication network.

3. The CIM-based intelligent pipeline status monitoring method according to claim 1 or 2, characterized in that: The data preprocessing and model construction are as follows: Data processing center: Establish an efficient data processing center, which receives the collected sensor data and performs pre-processing operations such as data cleaning, denoising, compression and storage on the collected sensor data to ensure the quality and integrity of the data; Build a CIM management platform: Use CIM technology to build an accurate three-dimensional model of the pipeline based on the information of the pipeline's geographical location, size, material and laying method; the accurate three-dimensional model of the pipeline includes the physical properties of the pipeline and is associated with the real-time operation data of the pipeline to achieve spatial display and analysis of the data.

4. The CIM-based intelligent pipeline status monitoring method according to claim 3 is characterized in that: The specific intelligent analysis and prediction are as follows: Data analysis and mining: Use big data analysis and data mining technology to conduct in-depth analysis of the processed pipeline operation data to identify the patterns, trends and anomalies in the data; and establish mathematical models and algorithms to predict the future operation status of the pipeline and assess potential risks and hidden dangers; Intelligent early warning: Combine machine learning algorithms to build an intelligent early warning model; the intelligent early warning model automatically identifies abnormal conditions in pipeline operation, triggers the early warning process according to preset thresholds and rules, and sends early warning information to relevant personnel in a timely manner so that measures can be taken quickly; abnormal conditions in pipeline operation include abnormal pressure increase, sudden drop in flow rate and abnormal temperature.

5. The CIM-based intelligent pipeline status monitoring method according to claim 4 is characterized in that: The method also deploys data monitoring software, pipeline management software, and mobile client applications; The data monitoring software has the following specific functions: ① Real-time data display: Display various operating parameters of the pipeline in real time in the form of charts and curves; the various operating parameters of the pipeline include temperature, pressure and flow; ② Historical data query: Supports querying historical data by time period and parameter type conditions, which is convenient for trend analysis and troubleshooting; ③Alarm and notification: When an abnormal situation is detected, the alarm mechanism is automatically triggered and relevant personnel are notified through sound and pop-up windows; The pipeline management software has the following functions: ①Maintenance task management: According to the operation status and early warning information of the pipeline, a maintenance task list is automatically generated and assigned to relevant personnel for execution; ②Task tracking and feedback: Track the execution of maintenance tasks, collect task execution results and feedback, and form a closed-loop management; ③Statistical analysis report: regularly generate statistical analysis reports on pipeline operation status; The mobile client application has the following specific functions: ① Remote monitoring: remotely view the operation status and real-time data of the pipeline via mobile phone or tablet; ②Task processing: Receive and process maintenance tasks assigned to you, including task review, execution records and result feedback; ③Message notification: Receive message notifications from the system, including warning information and task assignment, to ensure timely communication of information.

6. A CIM-based intelligent pipeline status monitoring system, characterized in that: The system includes: The data collection layer is used to build a data collection and transmission network by deploying multiple types of sensors along the pipeline to obtain and transmit real-time pipeline operation data; Data processing layer: used to pre-process pipeline operation data and build accurate 3D models of pipelines using CIM technology; The intelligent analysis layer is used to combine big data analysis and data mining technology to achieve in-depth analysis and prediction of pipeline operation data, and identify and warn of potential risks.

7. The CIM-based intelligent pipeline status monitoring system according to claim 6 is characterized in that: The system also includes data monitoring software, pipeline management software, and mobile client applications; The data monitoring software has the following specific functions: ① Real-time data display: Display various operating parameters of the pipeline in real time in the form of charts and curves; the various operating parameters of the pipeline include temperature, pressure and flow; ② Historical data query: Supports querying historical data by time period and parameter type conditions, which is convenient for trend analysis and troubleshooting; ③Alarm and notification: When an abnormal situation is detected, the alarm mechanism is automatically triggered and relevant personnel are notified through sound and pop-up windows; The pipeline management software has the following functions: ①Maintenance task management: According to the operation status and early warning information of the pipeline, a maintenance task list is automatically generated and assigned to relevant personnel for execution; ②Task tracking and feedback: Track the execution of maintenance tasks, collect task execution results and feedback, and form a closed-loop management; ③Statistical analysis report: regularly generate statistical analysis reports on pipeline operation status; The mobile client application has the following specific functions: ① Remote monitoring: remotely view the operation status and real-time data of the pipeline via mobile phone or tablet; ②Task processing: Receive and process maintenance tasks assigned to you, including task review, execution records and result feedback; ③Message notification: Receive message notifications from the system, including warning information and task assignment, to ensure timely communication of information.

8. The CIM-based intelligent pipeline status monitoring system according to claim 6 or 7, characterized in that: The data collection layer includes: The sensor network deployment module is used to deploy various sensors at key locations along the underground pipeline to fully cover and monitor various operating data of the pipeline in real time; the sensors include temperature sensors, pressure sensors, flow sensors and vibration sensors; The data acquisition and transmission module is used to connect each sensor to the data acquisition terminal by wire or wireless means. The data acquisition terminal is used to collect sensor data, perform preliminary processing and packaging on the collected sensor data, and then transmit it to the data processing center in real time through the communication network; The data processing layer includes: The data processing center establishment module is used to establish an efficient data processing center. The data processing center receives the collected sensor data and performs pre-processing operations such as data cleaning, denoising, compression and storage on the collected sensor data to ensure the quality and integrity of the data; The CIM management platform construction module is used to build an accurate three-dimensional model of the pipeline based on the geographical location, size, material and laying method of the pipeline using CIM technology. The accurate three-dimensional model of the pipeline includes the physical properties of the pipeline and is associated with the real-time operation data of the pipeline to realize the spatial display and analysis of the data; The intelligent analysis layer includes: The data analysis and mining module is used to use big data analysis and data mining technology to conduct in-depth analysis of the processed pipeline operation data, identify the patterns, trends and anomalies in the data; and predict the future operation status of the pipeline and evaluate potential risks and hidden dangers by establishing mathematical models and algorithms; The intelligent early warning module is used to build an intelligent early warning model in combination with a machine learning algorithm. The intelligent early warning model automatically identifies abnormal conditions in pipeline operation, triggers the early warning process according to preset thresholds and rules, and sends early warning information to relevant personnel in a timely manner so that measures can be taken quickly. Abnormal conditions in pipeline operation include abnormal pressure increase, sudden drop in flow rate, and abnormal temperature.

9. An electronic device, characterized in that: include: memory and at least one processor; Wherein, the memory stores a computer program; The at least one processor executes the computer program stored in the memory, so that the at least one processor executes the CIM-based intelligent pipeline status monitoring method according to any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which can be executed by a processor to implement the CIM-based intelligent pipeline status monitoring method as described in any one of claims 1 to 5.

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