A gas turbine operation and maintenance visualization platform based on digital twinning and a construction method thereof

Abstract

This invention provides a digital twin-based visualization platform and construction method for gas turbine operation and maintenance. It establishes a 3D digital twin model of the gas turbine, while the gas turbine sensors upload real-time operational data to a server. The server and the digital twin 3D model enable real-time 3D visualization. This invention rapidly enables comparative analysis of real-time gas turbine operational data, achieving the goal of refined data usage and control in operation and maintenance, and improving the intelligence level of remote operation and maintenance systems. Through terminal devices and the fusion of physical and digital space data, it displays gas turbine attribute data and operational status, performs operational status analysis and fault diagnosis and prediction, and provides contingency plans and risk assessments through an expert knowledge base, reducing human error while improving work safety and timeliness.

Description

Technical Field

[0001] This invention belongs to the field of computer-aided design, specifically relating to a digital twin-based visualization platform for the operation and maintenance of gas turbines and its construction method. Background Technology

[0002] With the continuous development of gas turbine research and development technology in my country, enterprises have put forward higher requirements for the digital management of gas turbines. Digital twin technology can effectively help enterprises achieve digital upgrades in production, management and other aspects, and reduce operation and maintenance costs.

[0003] Currently, most gas turbines are maintained by equipment manufacturers or third-party professional organizations, primarily through restorative and periodic maintenance. However, once a gas turbine malfunctions or shuts down, maintenance personnel often find it difficult to reach the work site quickly, resulting in excessively long downtime and high maintenance costs. There is an urgent need to introduce new technologies and methods to shift from traditional maintenance to predictive maintenance.

[0004] In gas turbine operation and maintenance, numerous information silos often exist due to the involvement of multiple systems, various devices, and the collaborative relationships between these systems. In traditional gas turbine operation and maintenance models, data collection and monitoring were mostly conducted manually, which not only increased labor and time costs but also made it difficult to monitor the gas turbine's operating status and fault information in real time. Summary of the Invention

[0005] The purpose of this invention is to provide a digital twin-based gas turbine operation and maintenance visualization platform and its construction method. By constructing a fault knowledge base after processing discrete fault information, it provides intelligent diagnostic strategies for remote operation and maintenance, thereby improving the efficiency of fracturing equipment operation and maintenance.

[0006] A digital twin-based visualization platform for gas turbine operation and maintenance includes: Model layer: A static 3D model is built based on the modeling data of the gas turbine; Twin layer: Connects to the modeling layer, uses software to simulate and render the digital twin model of the gas turbine, and interacts with the server in real time; Data layer: Gas turbine sensors collect real-time operating parameters of the gas turbine, process, analyze, store and classify the collected real-time data, and upload it to the server in a unified manner; The intelligent operation and maintenance platform includes a 3D visualization real-time display module, an operation status analysis module, a fault diagnosis and prediction module, an expert knowledge base module, and a contingency plan and risk assessment module. The 3D visualization real-time display is achieved through real-time interaction between the gas turbine digital twin model and processed data. The operation status analysis module evaluates and analyzes the gas turbine's operation status based on real-time data in the data layer. The fault diagnosis and prediction module comprehensively evaluates the gas turbine based on historical data in the database, identifies abnormal data, and, if a fault occurs, sends an alarm message to the terminal device via a pop-up window. The expert knowledge base module stores diagnostic solutions for various faults. The contingency plan and risk assessment module compares the solutions provided by the expert knowledge base with the actual problem, recommends the best solution, and sends this solution along with key fault information requiring maintenance to the terminal device.

[0007] Furthermore, the modeling data in the model layer includes gas turbine design drawings and equipment drawings, gas turbine modeling data, and gas turbine 3D model.

[0008] Furthermore, the data in the twin layer includes gas turbine attribute data and a digital twin model of the gas turbine.

[0009] Furthermore, the gas turbine sensors include vibration sensors, speed sensors, pressure sensors, temperature sensors, displacement sensors, magnetic speed sensors, and acceleration sensors; the data collected by the sensors includes: vibration data, speed data, pressure data, temperature data, displacement data, and real-time sound signal data.

[0010] Furthermore, the underlying state data of various parts of the gas turbine collected by the sensors are preprocessed, classified, and redundancy cleaned, including: a. Perform data compression and filtering; b. Divide the collected data into real-time data and historical data, and store them accordingly; c. Clean up redundant data; Real-time data is used to monitor the operating status of the gas turbine in real time and diagnose faults; historical data includes basic information data of the gas turbine, operating status data, and maintenance record data, and its function is to obtain the comprehensive evaluation curve of the gas turbine based on historical data.

[0011] Furthermore, the data uses OPC UA for secure transmission of underlying data: the collected data is standardized into a uniform format, the underlying multi-source heterogeneous data is aggregated, and the data is uploaded to the server.

[0012] Furthermore, the real-time 3D visualization incorporates virtual reality and augmented reality methods to intuitively demonstrate gas turbine operation and maintenance.

[0013] Furthermore, the terminal device can be a PC or a mobile terminal device.

[0014] A method for constructing a gas turbine operation and maintenance visualization platform based on digital twins, based on the gas turbine operation and maintenance visualization platform based on digital twins as described in claim 1, includes the following steps: S1. Based on the design drawings and equipment drawings of the gas turbine, use 3D modeling software to create the corresponding 3D model and ensure the accuracy of some device models; S2. Obtain gas turbine attribute data; add the gas turbine attribute data to the gas turbine 3D model; use Maya for modeling and Unreal Engine for rendering; construct a digital twin model of the gas turbine. S3. Collect the underlying status data of each part of the gas turbine structure through sensors; preprocess, analyze and clean up redundancy of the collected data; divide the preprocessed data into real-time data and historical data and store them in two different databases, and upload them to the server to obtain the real-time status of gas turbine operation and maintenance. The S4 intelligent operation and maintenance platform includes a 3D visualization real-time display module, an operation status analysis module, an expert knowledge base module, a fault diagnosis and prediction module, and a contingency plan and risk assessment module. Based on the data in the server and combined with the digital twin model of the gas turbine, the module displays the gas turbine attribute data and operation and maintenance status in real time, performs operation status analysis and fault diagnosis and prediction, and retrieves the corresponding maintenance strategies and plans from the expert knowledge base to feed back to the terminal equipment.

[0015] The beneficial effects of this invention are as follows: (1) Establish a digital twin three-dimensional data model of the gas turbine, comprehensively monitor and analyze the operating parameters of the gas turbine, and display the operation and maintenance status of the gas turbine in real time through three-dimensional visualization, thereby improving the intelligence level of the remote operation and maintenance system.

[0016] (2) After processing, heterogeneous data from multiple sensors are connected to the same server to achieve multi-data information sharing and make it more convenient to perform real-time big data analysis and processing of gas turbines.

[0017] (3) By using a remote operation and maintenance system, risks can be predicted in advance, decisions can be made in a timely manner, potential risks can be eliminated, equipment failure downtime rate can be reduced, and maintenance costs can be reduced.

[0018] (4) Display the operating status of fracturing field equipment through the terminal device client, and provide corresponding maintenance strategies and plans through the expert knowledge base to the terminal device, thereby reducing human error and improving work safety and timeliness. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the structure of the present invention; Figure 2 This is a flowchart of the present invention. Detailed Implementation

[0020] The present invention will now be further described with reference to the accompanying drawings.

[0021] like Figures 1-2 As shown, a digital twin-based gas turbine operation and maintenance visualization platform includes: Model layer: A static 3D model is built based on the modeling data of the gas turbine; Modeling data includes gas turbine design drawings and equipment drawings, gas turbine modeling data, and gas turbine 3D model; Twin layer: Connects to the modeling layer, uses software to simulate and render the digital twin model of the gas turbine, and interacts with the server in real time; The data includes gas turbine attribute data and a digital twin model of the gas turbine; Data layer: Gas turbine sensors collect real-time operating parameters of the gas turbine, process, analyze, store and classify the collected real-time data, and upload it to the server in a unified manner; Gas turbine sensors include vibration sensors, speed sensors, pressure sensors, temperature sensors, displacement sensors, magnetic speed sensors, and acceleration sensors; the data collected by the sensors includes: vibration data, speed data, pressure data, temperature data, displacement data, and real-time sound signal data; Vibration data, such as vibration velocities in the vertical and horizontal directions, are used to assess the health of machinery. Rotational speed data: including the rotational speeds of the low-pressure compressor, high-pressure compressor, and power turbine rotor; Pressure data: such as dynamic pressure pulsation in the combustion chamber, to monitor combustion stability; Temperature data: such as the temperature of key components like turbine blades and combustion chambers; Displacement data: the relative displacement between the journal and the bearing, used to assess mechanical wear; Sound signals: The operating status of the gas turbine is analyzed through sound signal acquisition; The underlying state data of various parts of the gas turbine collected by sensors are preprocessed, classified, and redundancy removed, including: a. Perform data compression and filtering; b. Divide the collected data into real-time data and historical data, and store them accordingly; c. Clean up redundant data; Real-time data is used to monitor the operating status of the gas turbine and diagnose faults in real time; historical data includes basic information data of the gas turbine, operating status data, and maintenance record data, and its function is to obtain the comprehensive evaluation curve of the gas turbine based on historical data. The intelligent operation and maintenance platform includes a 3D visualization real-time display module, an operation status analysis module, a fault diagnosis and prediction module, an expert knowledge base module, and a contingency plan and risk assessment module. The 3D visualization real-time display is achieved through real-time interaction between the gas turbine digital twin model and processed data. The operation status analysis module evaluates and analyzes the gas turbine's operation status based on real-time data in the data layer. The fault diagnosis and prediction module comprehensively evaluates the gas turbine based on historical data in the database, identifies abnormal data, and, if a fault occurs, sends an alarm message to the terminal device via a pop-up window. The expert knowledge base module stores diagnostic solutions for various faults. The contingency plan and risk assessment module compares the solutions provided by the expert knowledge base with the actual problem, recommends the best solution, and sends this solution along with key fault information requiring maintenance to the terminal device.

[0022] The data uses OPC UA for secure transmission of underlying data: the collected data is standardized into a uniform format, the underlying multi-source heterogeneous data is aggregated, and the data is uploaded to the server.

[0023] The 3D visualization real-time display incorporates virtual reality and augmented reality methods to intuitively demonstrate the operation and maintenance of gas turbines.

[0024] The terminal devices include PCs and mobile devices.

[0025] A method for constructing a gas turbine operation and maintenance visualization platform based on digital twins includes the following steps: S1. Based on the design drawings and equipment drawings of the gas turbine, use 3D modeling software to create the corresponding 3D model and ensure the accuracy of some device models; S2. Obtain gas turbine attribute data; add the gas turbine attribute data to the gas turbine 3D model; use Maya for modeling and Unreal Engine for rendering; construct a digital twin model of the gas turbine. S3. Collect the underlying status data of each part of the gas turbine structure through sensors; preprocess, analyze and clean up redundancy of the collected data; divide the preprocessed data into real-time data and historical data and store them in two different databases, and upload them to the server to obtain the real-time status of gas turbine operation and maintenance. The S4 intelligent operation and maintenance platform includes a 3D visualization real-time display module, an operation status analysis module, an expert knowledge base module, a fault diagnosis and prediction module, and a contingency plan and risk assessment module. Based on the data in the server and combined with the digital twin model of the gas turbine, the module displays the gas turbine attribute data and operation and maintenance status in real time, performs operation status analysis and fault diagnosis and prediction, and retrieves the corresponding maintenance strategies and plans from the expert knowledge base to feed back to the terminal equipment.

[0026] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A gas turbine operation and maintenance visualization platform based on digital twinning, characterized in that, include: Model layer: A static 3D model is built based on the modeling data of the gas turbine; Twin layer: Connects to the modeling layer, uses software to simulate and render the digital twin model of the gas turbine, and interacts with the server in real time; Data layer: Gas turbine sensors collect real-time operating parameters of the gas turbine, process, analyze, store and classify the collected real-time data, and upload it to the server in a unified manner; Intelligent operation and maintenance platform: includes a 3D visualization real-time display module, an operation status analysis module, a fault diagnosis and prediction module, an expert knowledge base module, and a contingency plan and risk assessment module; The 3D visualization real-time display is achieved through real-time interaction between the gas turbine digital twin model and the processed data; the operation status analysis module evaluates and analyzes the operation status of the gas turbine based on real-time data in the data layer; the fault diagnosis and prediction module comprehensively evaluates the gas turbine based on historical data in the database, judges abnormal data, and if a fault occurs, the alarm information is fed back to the terminal device in the form of a pop-up window. The expert knowledge base module stores diagnostic solutions for various faults; The contingency plan and risk assessment module compares the solutions provided by the expert knowledge base with the actual problems, recommends the best solution, and feeds back the solution and key fault information that needs to be repaired to the terminal equipment.

2. The gas turbine operation and maintenance visualized platform based on digital twinning of claim 1, wherein, The modeling data in the model layer includes gas turbine design drawings and equipment drawings, gas turbine modeling data, and gas turbine 3D model.

3. The gas turbine operation and maintenance visualized platform based on digital twinning of claim 1, wherein, The data in the twin layer includes gas turbine attribute data and a digital twin model of the gas turbine.

4. The gas turbine operation and maintenance visualization platform based on digital twin as described in claim 1, characterized in that, The gas turbine sensors include vibration sensors, speed sensors, pressure sensors, temperature sensors, displacement sensors, magnetic speed sensors, and acceleration sensors; the data collected by the sensors includes vibration data, speed data, pressure data, temperature data, displacement data, and real-time sound signal data.

5. The gas turbine operation and maintenance visualization platform based on digital twin as described in claim 1, characterized in that, The underlying state data of various parts of the gas turbine collected by sensors are preprocessed, classified, and redundancy removed, including: a. Perform data compression and filtering; b. Divide the collected data into real-time data and historical data, and store them accordingly; c. Clean up redundant data; Real-time data is used to monitor the operating status of the gas turbine in real time and diagnose faults; historical data includes basic information data of the gas turbine, operating status data, and maintenance record data, and its function is to obtain the comprehensive evaluation curve of the gas turbine based on historical data.

6. A gas turbine operation and maintenance visualization platform based on digital twins according to claim 5, characterized in that, The data is transmitted securely using OPC UA at the underlying level: the collected data is standardized into a uniform format, the underlying multi-source heterogeneous data is aggregated, and the data is uploaded to the server.

7. The gas turbine operation and maintenance visualization platform based on digital twin as described in claim 1, characterized in that, The real-time 3D visualization incorporates virtual reality and augmented reality methods to intuitively demonstrate gas turbine operation and maintenance.

8. A gas turbine operation and maintenance visualization platform based on digital twins according to claim 1, characterized in that, The terminal devices mentioned include PC-based and mobile terminal devices.

9. A method for constructing a gas turbine operation and maintenance visualization platform based on digital twins, based on the gas turbine operation and maintenance visualization platform based on digital twins as described in claim 1, characterized in that, Includes the following steps: S1. Based on the design drawings and equipment drawings of the gas turbine, use 3D modeling software to create the corresponding 3D model and ensure the accuracy of some device models; S2. Obtain gas turbine attribute data; add the gas turbine attribute data to the gas turbine 3D model; use Maya for modeling and Unreal Engine for rendering; construct a digital twin model of the gas turbine. S3. Collect the underlying status data of each part of the gas turbine structure through sensors; preprocess, analyze and clean up redundancy of the collected data; divide the preprocessed data into real-time data and historical data and store them in two different databases, and upload them to the server to obtain the real-time status of gas turbine operation and maintenance. The S4 intelligent operation and maintenance platform includes a 3D visualization real-time display module, an operation status analysis module, an expert knowledge base module, a fault diagnosis and prediction module, and a contingency plan and risk assessment module. Based on the data in the server and combined with the digital twin model of the gas turbine, the module displays the gas turbine attribute data and operation and maintenance status in real time, performs operation status analysis and fault diagnosis and prediction, and retrieves the corresponding maintenance strategies and plans from the expert knowledge base to feed back to the terminal equipment.

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