Reciprocating compressor remote operation and maintenance system based on digital twinning

Abstract

The utility model discloses a reciprocating compressor remote operation and maintenance system based on digital twinning, and the system comprises a reciprocating compressor which is provided with a control system and a monitoring system which are matched with each other, and the monitoring system is used for obtaining the operation environment data of the reciprocating compressor and is connected with the control system; the remote operation and maintenance upper computer is connected with the control system through a data transmission module, a virtual model platform and a data analysis platform are carried in the remote operation and maintenance upper computer, and a digital twin model of the reciprocating compressor is built in the virtual model platform; and the data analysis platform is connected with the virtual model platform and is provided with a fault prediction model of the reciprocating compressor. According to the utility model, the digital twin technology and the remote operation and maintenance technology are organically combined, the functions of remote monitoring, fault diagnosis, predictive maintenance and the like of the reciprocating compressor are realized, and potential faults of equipment operation can be found in advance, so that the production efficiency and the equipment reliability are ensured, and the production cost of enterprises is reduced.

Description

Technical Field

[0001] This utility model relates to the field of compressor technology. More specifically, this utility model relates to a remote operation and maintenance system for reciprocating compressors based on digital twins. Background Technology

[0002] Reciprocating compressors are core equipment in the petrochemical industry and are also widely used in other fields. Their working principle is to convert the electrical or thermal energy of the drive motor into the pressure energy of the gas through changes in volume. They are mainly used for oil and gas production, transportation or storage in petrochemical plants and gas storage facilities. Their performance and efficiency directly affect the production of enterprises.

[0003] Because reciprocating compressors have a precise internal structure with numerous moving parts and vulnerable components, and their operating conditions vary widely, unstable operation or malfunctions can cause significant economic losses to enterprises. Traditional operation and maintenance systems suffer from heavy reliance on technical personnel, high time costs, and low efficiency, which hinders stable and efficient production.

[0004] To address the aforementioned issues, a remote operation and maintenance system for reciprocating compressors based on digital twins needs to be designed to ensure efficient and stable operation and maintenance while reducing maintenance costs. Utility Model Content

[0005] The purpose of this invention is to provide a remote operation and maintenance system for reciprocating compressors based on digital twins. This system organically combines digital twin technology with remote operation and maintenance technology to achieve remote monitoring, fault diagnosis, and predictive maintenance of reciprocating compressors. It helps to detect potential equipment failures in advance, thereby ensuring production efficiency and equipment reliability, and reducing enterprise production costs.

[0006] To achieve these objectives and other advantages according to this utility model, a remote operation and maintenance system for reciprocating compressors based on digital twins is provided, comprising:

[0007] A reciprocating compressor is provided with a matching control system and a monitoring system. The monitoring system is configured to acquire the operating environment data of the reciprocating compressor and connect to the control system.

[0008] The remote operation and maintenance host computer is connected to the control system through a data transmission module. The remote operation and maintenance host computer is equipped with a virtual model platform and a data analysis platform. The virtual model platform has a digital twin model of the reciprocating compressor. The data analysis platform is connected to the virtual model platform and has a fault prediction model of the reciprocating compressor.

[0009] Preferably, in the remote operation and maintenance system for reciprocating compressors based on digital twins, the data transmission module is configured to enable bidirectional information transmission between the reciprocating compressor and the remote operation and maintenance host computer.

[0010] Preferably, the remote operation and maintenance system for reciprocating compressors based on digital twins includes a virtual model platform comprising a data acquisition module configured to collect information on each component of the reciprocating compressor unit, including size information, color information, and material information; and a modeling module connected to the data acquisition module and configured to establish a digital twin model of the reciprocating compressor.

[0011] Preferably, the remote operation and maintenance system for reciprocating compressors based on digital twins includes a digital twin model comprising a visual 3D model and a dynamic simulation model.

[0012] Preferably, the remote operation and maintenance system for reciprocating compressors based on digital twins includes a data analysis platform comprising a data storage module configured to store real-time and historical operating data of the reciprocating compressor and establish a database; a data processing module connected to the data storage module and configured to establish a fault prediction model for the reciprocating compressor based on its operating data; and a fault diagnosis module connected to the data storage module and the data processing module, configured to analyze the real-time operating data of the reciprocating compressor based on its fault prediction model and output predicted fault diagnosis results.

[0013] Preferably, the remote operation and maintenance system for reciprocating compressors based on digital twins further includes a display device electrically connected to the remote operation and maintenance host computer, the display device being configured to receive and display data from the virtual model platform and the data analysis platform; and an input device electrically connected to the remote operation and maintenance host computer, the input device being configured to transmit control commands from the outside to the remote operation and maintenance host computer.

[0014] Preferably, the remote operation and maintenance system for reciprocating compressors based on digital twins includes the following architecture:

[0015] The equipment layer includes the hardware structures of the reciprocating compressor, the control system, and the monitoring system;

[0016] An intermediate layer, which is connected to the device layer, is configured to store real-time and historical data from the device layer and to build a digital twin model of the reciprocating compressor;

[0017] An application layer, which is connected to the middle layer, is configured to output a digital twin model of the reciprocating compressor and provide fault diagnosis and predictive services.

[0018] This utility model has at least the following beneficial effects:

[0019] This invention organically combines digital twin technology with remote operation and maintenance technology, and designs a remote operation and maintenance system for reciprocating compressors based on digital twin technology. By using digital twin technology to perform predictive maintenance on compressor equipment, it realizes equipment status monitoring and predictive maintenance, effectively improves the accuracy of remote operation and maintenance, helps to detect potential faults in the compressor operation process in advance, better ensures the efficient and stable operation of the unit, thereby improving production efficiency and equipment reliability, reducing maintenance costs, and solving the problems of insufficient intelligence and low efficiency in traditional operation and maintenance.

[0020] Other advantages, objectives and features of this invention will be partly apparent from the following description, and partly understood by those skilled in the art through study and practice of this invention. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the structure of a remote operation and maintenance system for a reciprocating compressor based on digital twin, according to one embodiment of the present invention.

[0022] Figure 2 This is an architecture diagram of the remote operation and maintenance system for reciprocating compressors based on digital twins described in the above embodiments;

[0023] Figure 3 This is a flowchart illustrating the modeling process of the visualized 3D model described in the above embodiments;

[0024] Figure 4 This is a flowchart of the data analysis platform described in the above embodiments. Detailed Implementation

[0025] The present invention will now be described in further detail with reference to the accompanying drawings, so that those skilled in the art can implement it based on the description.

[0026] It should be noted that, unless otherwise specified, the experimental methods described in the following embodiments are all conventional methods, and the reagents and materials described are all commercially available unless otherwise specified. In the description of this utility model, the terms "lateral", "longitudinal", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this utility model and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this utility model.

[0027] like Figure 1-4 As shown, this utility model provides a remote operation and maintenance system for reciprocating compressors based on digital twins, including:

[0028] A reciprocating compressor is provided with a matching control system and a monitoring system. The monitoring system is configured to acquire the operating environment data of the reciprocating compressor and connect to the control system.

[0029] The remote operation and maintenance host computer is connected to the control system through a data transmission module. The remote operation and maintenance host computer is equipped with a virtual model platform and a data analysis platform. The virtual model platform has a digital twin model of the reciprocating compressor. The data analysis platform is connected to the virtual model platform and has a fault prediction model of the reciprocating compressor.

[0030] In the above technical solution, the reciprocating compressor represents the local end of the digital twin-based remote operation and maintenance system for the reciprocating compressor, and the remote operation and maintenance host computer represents the remote operation and maintenance end of the same system. The local end and the remote operation and maintenance end establish a connection through the data transmission module to achieve remote data transmission. Both the control system and the monitoring system are located at the local end. The monitoring system and the reciprocating compressor are electrically connected to the control system. The control system can centrally control the hardware devices at the local end, including acquiring the operating data (operating parameters) of the reciprocating compressor and adjusting its operating status, and controlling the monitoring system to monitor the compressor's operating environment. The operating environment data of the reciprocating compressor includes internal and external data. Internal data includes compressor operating temperature, operating pressure, lubricating oil status, etc., while external data includes ambient temperature, humidity, noise, vibration, etc. The control system can use conventional control equipment (controllers, etc.), and the monitoring system can use a combination of various sensors, including but not limited to temperature sensors, humidity sensors, sound sensors, vibration sensors, pressure sensors, etc. Each sensor is correspondingly deployed at a suitable reciprocating compressor component to detect the corresponding data. The remote operation and maintenance (O&M) terminal is equipped with a virtual model platform and a data analysis platform. These two platforms can be implemented as software or clients within the remote O&M host computer and receive operating data and environmental data from the reciprocating compressor. The virtual model platform, based on digital twin technology, constructs a mapping model of the reciprocating compressor itself at the remote O&M terminal. This model includes a digital simulation of the compressor's geometry and operating process. The simulation results can be displayed at the remote O&M terminal (remote O&M host computer), enabling remote, real-time monitoring of the reciprocating compressor's operating status. The data analysis platform simultaneously receives operating and environmental data from the reciprocating compressor and digital twin model data generated by the virtual model platform. The platform processes the collected raw data, filtering out data from normal compressor operation and data from faulty operation. Based on the LVQ neural network algorithm, it establishes a reciprocating compressor fault prediction model. This model allows for analysis of the reciprocating compressor's real-time operating data, yielding fault prediction results. This enables functions such as fault diagnosis and predictive maintenance, facilitating the early detection of potential faults in the reciprocating compressor's operation and ensuring production efficiency and equipment reliability. The connections between various systems, modules, and platforms are signal connections, used to achieve one-way or two-way data transmission according to design requirements.

[0031] Digital twins enable real-time monitoring, predictive analysis, and optimization decision-making for physical entities, providing new ideas and methods for remote operation and maintenance of large equipment as an emerging technology. This invention organically combines digital twin technology with remote operation and maintenance technology to achieve remote monitoring, fault diagnosis, and predictive maintenance of reciprocating compressors. This facilitates the early detection of potential equipment failures, thereby ensuring production efficiency and equipment reliability, and significantly contributing to reducing enterprise production costs.

[0032] In another technical solution, the remote operation and maintenance system for reciprocating compressors based on digital twins includes a data transmission module configured to enable bidirectional information transmission between the reciprocating compressor and the remote operation and maintenance host computer. Specifically, the data transmission module can transmit the operating data and operating environment data of the reciprocating compressor to the remote operation and maintenance host computer, and can also transmit control commands from the remote operation and maintenance end to the reciprocating compressor hardware (local end) for execution by the control system. Specifically, the data transmission module connects the remote operation and maintenance host computer and the control system (lower-level machine) through communication interfaces such as networks, serial ports, or USB ports, enabling communication between the remote operation and maintenance end and the local end.

[0033] In another technical solution, the remote operation and maintenance system for reciprocating compressors based on digital twins includes a virtual model platform comprising a data acquisition module configured to collect information on various components of the reciprocating compressor unit, including dimensional, color, and material information; and a modeling module connected to the data acquisition module and configured to create a digital twin model of the reciprocating compressor. The modeling platform can perform three-dimensional modeling of the reciprocating compressor based on the information from the data acquisition module. Simultaneously, in addition to the data acquisition module, the modeling module also receives data from the control system, namely, the operating data and operating environment data of the reciprocating compressor transmitted to the remote operation and maintenance host computer by the data transmission module. Therefore, the modeling platform can also simulate the reciprocating compressor from the perspective of its operation process.

[0034] In another technical solution, the remote operation and maintenance system for reciprocating compressors based on digital twins includes a digital twin model comprising a visualized 3D model and a dynamic simulation model. In this solution, the dynamic simulation model can be built using Matlab / Simulink to simulate the operation of the reciprocating compressor on a remote operation and maintenance host computer. The visualized 3D model can be created using 3ds Max software to map the geometry of the reciprocating compressor onto the remote operation and maintenance host computer. Specifically, the modeling steps for the visualized 3D model include:

[0035] S1. Data acquisition complete, compressor white model:

[0036] Information on each component of the reciprocating compressor unit (crankcase, lubrication station, air cooler, cooling water pump, main drive motor, valves, control cabinet) is collected at the reciprocating compressor factory or on-site. Using 3ds Max software, polygon modeling is used to model the reciprocating compressor's shape, piping, main unit, and mechanical power parts to complete the production of the reciprocating compressor white model.

[0037] S2. Create texture images for each component:

[0038] Based on the material information of each component of the reciprocating compressor, the Vary renderer in 3ds Max was used to add materials to each component, export graphics, and add colors. Finally, based on the color information of each component, Photoshop was used to draw the texture of each device, thus completing the production of texture images of each component of the reciprocating compressor.

[0039] S3. Model Establishment:

[0040] The completed textures are added to each component of the reciprocating compressor. The textures and lighting in the scene are then baked and rendered. Finally, based on the position information of each component of the reciprocating compressor, the assembly of the reciprocating compressor's visualized 3D model is completed.

[0041] In another technical solution, the remote operation and maintenance system for reciprocating compressors based on digital twins includes a data analysis platform comprising a data storage module for storing real-time and historical operating data of the reciprocating compressor and establishing a database; a data processing module connected to the data storage module for establishing a fault prediction model for the reciprocating compressor based on its operating data; and a fault diagnosis module connected to the data storage module and the data processing module, configured to analyze the real-time operating data of the reciprocating compressor based on its fault prediction model and output predicted fault diagnosis results. The real-time / historical operating data of the reciprocating compressor includes its working data and operating environment data. Specifically, the data processing module processes the operating data of the reciprocating compressor, filters out data during normal operation and data during faults, and then establishes a fault prediction model for the reciprocating compressor based on the LVQ neural network algorithm (based on historical operating data of the reciprocating compressor). The fault diagnosis module can analyze the real-time operating data of the reciprocating compressor based on the fault prediction model of the reciprocating compressor and obtain fault diagnosis results, thereby realizing functions such as fault diagnosis and predictive services. It is worth noting that during operation and maintenance, the data processing module can also continuously use the reciprocating compressor operating data updated in the data storage module to train and optimize the reciprocating compressor fault prediction model to ensure the accuracy, authenticity and reliability of the fault prediction results.

[0042] In another technical solution, the remote operation and maintenance system for reciprocating compressors based on digital twins further includes a display device electrically connected to the remote operation and maintenance host computer. The display device is configured to receive and display data from the virtual model platform and data analysis platform. An input device, also electrically connected to the remote operation and maintenance host computer, is configured to transmit external control commands to the host computer, which then controls the operating status of the reciprocating compressor via a host-slave (control system) architecture. The display device can be a monitor, which integrates data from the virtual model platform and data analysis platform into various operation and maintenance information (dynamic simulation models, fault diagnosis results, prediction results) and outputs it. The input device can be a keyboard or integrated with the display device into a touch screen. The input device can input external control commands into the remote operation and maintenance system and can also invoke different service commands to display the corresponding service (output) results.

[0043] In another technical solution, the remote operation and maintenance system for reciprocating compressors based on digital twins includes the following architecture:

[0044] The equipment layer includes the hardware structures of the reciprocating compressor, the control system, and the monitoring system;

[0045] An intermediate layer, which is connected to the device layer, is configured to store real-time and historical data from the device layer and to build a digital twin model of the reciprocating compressor;

[0046] An application layer, which is connected to the middle layer, is configured to output a digital twin model of the reciprocating compressor and provide fault diagnosis and predictive services.

[0047] In the above technical solution, the equipment layer mainly includes local hardware components such as drive motors, main units and cylinders, lubrication stations, cooling systems, control systems, and monitoring systems. The middleware layer is used to complete the digital twin model of the compressor and perform data optimization processing. The application layer is used to display the dynamic model of the unit and provide fault diagnosis and predictive services.

[0048] Although the embodiments of this utility model have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for this utility model. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, this utility model is not limited to the specific details and the illustrations shown and described herein.

Claims

1. A remote operation and maintenance system for reciprocating compressors based on digital twins, characterized in that, include: A reciprocating compressor is provided with a matching control system and a monitoring system. The monitoring system is configured to acquire the operating environment data of the reciprocating compressor and connect to the control system. The remote operation and maintenance host computer is connected to the control system through a data transmission module. The remote operation and maintenance host computer is equipped with a virtual model platform and a data analysis platform. The virtual model platform has a digital twin model of the reciprocating compressor. The data analysis platform is connected to the virtual model platform and has a fault prediction model of the reciprocating compressor.

2. The remote operation and maintenance system for reciprocating compressors based on digital twins as described in claim 1, characterized in that, The data transmission module is configured to enable bidirectional information transmission between the reciprocating compressor and the remote operation and maintenance host computer.

3. The remote operation and maintenance system for reciprocating compressors based on digital twins as described in claim 1, characterized in that, The virtual model platform includes a data acquisition module, which is configured to collect information on each component of the reciprocating compressor unit, including size information, color information and material information. A modeling module, which is connected to the data acquisition module and configured to build a digital twin model of the reciprocating compressor.

4. The remote operation and maintenance system for reciprocating compressors based on digital twins as described in claim 3, characterized in that, The digital twin model includes a visual 3D model and a dynamic simulation model.

5. The remote operation and maintenance system for reciprocating compressors based on digital twins as described in claim 1, characterized in that, The data analysis platform includes a data storage module, configured to store real-time and historical operating data of the reciprocating compressor and establish a database; a data processing module, connected to the data storage module and configured to establish a fault prediction model for the reciprocating compressor based on its operating data; and a fault diagnosis module, connected to the data storage module and the data processing module, configured to analyze the real-time operating data of the reciprocating compressor based on its fault prediction model and output predicted fault diagnosis results.

6. The remote operation and maintenance system for reciprocating compressors based on digital twins as described in claim 1, characterized in that, It also includes a display device electrically connected to the remote operation and maintenance host computer, the display device being configured to receive and display data from the virtual model platform and the data analysis platform; and an input device electrically connected to the remote operation and maintenance host computer, the input device being configured to transmit control commands from the outside to the remote operation and maintenance host computer.

7. The remote operation and maintenance system for reciprocating compressors based on digital twins as described in claim 1, characterized in that, The architecture of the remote operation and maintenance system for reciprocating compressors based on digital twins includes: The equipment layer includes the hardware structures of the reciprocating compressor, the control system, and the monitoring system; An intermediate layer, which is connected to the device layer, is configured to store real-time and historical data from the device layer and to build a digital twin model of the reciprocating compressor; An application layer, which is connected to the middle layer, is configured to output a digital twin model of the reciprocating compressor and provide fault diagnosis and predictive services.

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