Remote collaborative maintenance and diagnosis method for LNG intelligent control valve

Abstract

The invention discloses an LNG intelligent control valve remote collaborative maintenance and diagnosis method, which belongs to the technical field of liquefied natural gas control, and comprises the following steps: collecting data on an LNG control valve through various sensors; the method has the capability of realizing remote real-time monitoring and maintenance, and by developing a multi-terminal data transmission system and combining an advanced fault diagnosis and prevention and control decision technology, the LNG control valve can quickly judge the fault position and provide a solution when the fault occurs; meanwhile, the method is seamlessly integrated with an STS (safe shutdown system) and an ESD (emergency shutdown system), the safety and the high efficiency of the system are guaranteed, the method is based on the communication technology and the wireless network technology, data can be transmitted in real time, the fault diagnosis and prevention and control decision technology are combined, the fault is rapidly positioned, a solution is automatically generated, seamless integration with the STS and the ESD system is guaranteed, and the system reliability is improved. Therefore, the intelligent management and cooperative maintenance capability of the LNG control valve is improved, and the application effect of the whole method is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of liquefied natural gas control, and in particular relates to a remote collaborative maintenance and diagnosis method for an LNG intelligent control valve. Background Art

[0002] Liquefied natural gas, or LNG for short, is a clean and efficient energy source, mainly composed of methane, and is recognized as one of the cleanest fossil energy sources on Earth. Liquefied natural gas is a cryogenic liquid mixture formed by pre-processing natural gas to remove impurities and then freezing it.

[0003] The control valves of liquefied natural gas (LNG) systems are an important component to ensure the safety of natural gas transportation and storage. However, traditional valve maintenance systems often rely on manual inspection and offline diagnosis, which leads to slow fault location and inefficient troubleshooting, increasing the risk of system downtime and maintenance costs. In order to solve this problem, remote collaborative maintenance and diagnosis methods for LNG intelligent control valves are urgently needed. Summary of the invention

[0004] The purpose of the present invention is to propose a remote collaborative maintenance and diagnosis method for LNG intelligent control valves in order to solve the problem that traditional valve maintenance systems often rely on manual detection and offline diagnosis, resulting in slow fault location, low solution efficiency, and increased system downtime risk and maintenance costs.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: a remote collaborative maintenance and diagnosis method for LNG intelligent control valve, comprising the following steps: S1. Collect data on the LNG control valve through various sensors. Through the IIoT network, the system transmits the data collected by the sensors installed on the LNG control valve to the cloud server and local controller in real time; S2. Collect data and transmit it to the cloud analysis platform. Through the built-in fault diagnosis algorithm, the system can monitor and analyze data fluctuations in real time, determine the fault location, and provide detailed fault information; S3. After diagnosing a fault, the system will automatically generate a maintenance plan, optimize operating parameters based on historical operating data, and provide maintenance recommendations using decision-making models; S4. LNG system operators can view the operating status and fault diagnosis results of the control valve in real time through the remote terminal; S5. After a fault occurs, the system will generate a maintenance plan and push it to the operator's device; S6. When the system detects an extreme abnormal situation, it will implement an emergency plan; S7. Back up historical diagnosis and testing information; S8. Regularly analyze historical related information.

[0006] As a further description of the above technical solution: In S1, the system transmits the data collected by the sensor installed on the LNG control valve in real time to the cloud server and the local controller through the IIoT network. The terminals can communicate with each other through the wireless network to ensure the reliability and low latency of multi-terminal data transmission. The wireless network is one of 5G or LoRa.

[0007] As a further description of the above technical solution: In S2, the collected data is transmitted to the cloud analysis platform. Through the built-in fault diagnosis algorithm, the system can monitor and analyze data fluctuations in real time, determine the fault location, and provide detailed fault information. The collected data includes temperature, pressure, and flow data.

[0008] As a further description of the above technical solution: In S3, after diagnosing a fault, the system will automatically generate a maintenance plan, optimize operating parameters based on historical operating data using a decision model, and provide maintenance recommendations. If the fault is serious, the system will trigger an automatic maintenance function and transmit the maintenance command to the on-site controller or operator via a wireless network. The time it takes for the system to automatically generate a maintenance plan is ≤3 seconds.

[0009] As a further description of the above technical solution: In S4, the operator of the LNG system can view the operating status and fault diagnosis results of the control valve in real time through a remote terminal, and the remote terminal is a mobile phone or a tablet.

[0010] As a further description of the above technical solution: In S5, after a fault occurs, the system will generate a maintenance plan and push it to the operator's device. If an emergency shutdown is required, the system will seamlessly notify the STS and ESD systems to perform relevant operations to avoid delays.

[0011] As a further description of the above technical solution: In S6, when the system detects an extreme abnormal situation, an emergency plan is implemented. Specifically, the system will directly and automatically communicate with the STS and ESD systems to trigger an emergency shutdown or shut down the valve to avoid more serious accidents.

[0012] As a further description of the above technical solution: In S7, the historical diagnosis and detection information is backed up, and the backup information is transmitted to the cloud platform for storage.

[0013] As a further description of the above technical solution: In S8, historical related information is analyzed regularly, and based on the analysis results, 3-5 modification plans for the LNG intelligent control valve are generated, and the modification plans for the LNG intelligent control valve are simulated. After the simulation, evaluation is performed, and the evaluation results are divided into three types: excellent, good and poor. The modification plan with an excellent evaluation result is selected.

[0014] The present invention also discloses a remote collaborative maintenance and diagnosis system for an LNG intelligent control valve, comprising a multidimensional data acquisition module and a real-time data transmission module, wherein the output end of the multidimensional data acquisition module is connected to the input end of the real-time data transmission module, the output end of the real-time data transmission module is connected to the input end of the automatic data analysis module, the output end of the automatic data analysis module is connected to the input end of the remote fault diagnosis module, the output end of the remote fault diagnosis module is connected to the input end of the prevention and control decision module, the output end of the prevention and control decision module is connected to the input end of the STS and ESD system integration module, the output end of the STS and ESD system integration module is connected to the input end of the emergency plan module, the output end of the emergency plan module is connected to the input end of the historical information backup module, and the output end of the historical information backup module is connected to the input end of the historical information analysis module.

[0015] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: In the present invention, the method has the ability to realize remote real-time monitoring and maintenance. By developing a multi-terminal data transmission system and combining advanced fault diagnosis and prevention and control decision-making technology, the LNG control valve can quickly determine the fault location and provide a solution when a fault occurs. At the same time, it is seamlessly integrated with STS (safety shutdown system) and ESD (emergency shutdown system) to ensure the safety and efficiency of the system. The method is based on communication technology and wireless network technology, and can transmit data in real time. Combined with fault diagnosis and prevention and control decision-making technology, it can quickly locate faults and automatically generate solutions, ensuring seamless integration with STS and ESD systems, thereby improving the intelligent management and collaborative maintenance capabilities of the LNG control valve, and greatly improving the application effect of the overall method. The method also subsequently provides a backup and analysis process for historical diagnosis and detection information, and can propose a modification plan for the structure of the LNG intelligent control valve based on historical related information, thereby fundamentally improving the quality of the LNG intelligent control valve, thereby fundamentally reducing the failure rate of the LNG intelligent control valve, and further improving the actual application effect of the method. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Flow chart of the remote collaborative maintenance and diagnosis method for LNG intelligent control valve Figure 2Schematic diagram of the module structure of the remote collaborative maintenance and diagnosis system for LNG intelligent control valves. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Example 1 See also Figure 1 The present invention provides a technical solution: a remote collaborative maintenance and diagnosis method for an LNG intelligent control valve, comprising the following steps: S1. Through the IIoT network, the system transmits the data collected by the sensors installed on the LNG control valve to the cloud server and local controller in real time. The terminals can communicate with each other through the wireless network to ensure the reliability and low latency of multi-terminal data transmission. The wireless network is LoRa. S2. Collect data and transmit it to the cloud analysis platform. Through the built-in fault diagnosis algorithm, the system can monitor and analyze data fluctuations in real time, determine the fault location, and provide detailed fault information. The collected data includes temperature, pressure, and flow data; S3. After diagnosing a fault, the system will automatically generate a maintenance plan, optimize operating parameters based on historical operating data using a decision model, and provide maintenance recommendations. If the fault is serious, the system will trigger the automatic maintenance function and transmit the maintenance command to the on-site controller or operator via the wireless network. The time it takes for the system to automatically generate a maintenance plan is ≤ 3 seconds. S4. The operator of the LNG system can view the operating status and fault diagnosis results of the control valve in real time through the remote terminal, which is a tablet; S5. After a fault occurs, the system will generate a maintenance plan and push it to the operator's device. If an emergency shutdown is required, the system will seamlessly notify the STS and ESD systems to perform relevant operations to avoid delays; S6. When the system detects an extreme abnormal situation, it will implement an emergency plan. Specifically, the system will communicate directly and automatically with the STS and ESD systems to trigger an emergency shutdown or shut down the valve to avoid more serious accidents. S7. Back up historical diagnosis and detection information and transfer the backup information to the cloud platform for storage; S8. Regularly analyze historical related information, generate three transformation plans for LNG intelligent control valves based on the analysis results, and simulate the transformation plans for LNG intelligent control valves. After the simulation, evaluation is performed and the evaluation results are divided into three types: excellent, good and poor. The transformation plan with an excellent evaluation result is selected.

[0019] The present invention also discloses a remote collaborative maintenance and diagnosis system for an LNG intelligent control valve, comprising a multidimensional data acquisition module and a real-time data transmission module, wherein the output end of the multidimensional data acquisition module is connected to the input end of the real-time data transmission module, the output end of the real-time data transmission module is connected to the input end of the automatic data analysis module, the output end of the automatic data analysis module is connected to the input end of the remote fault diagnosis module, the output end of the remote fault diagnosis module is connected to the input end of the prevention and control decision module, the output end of the prevention and control decision module is connected to the input end of the STS and ESD system integration module, the output end of the STS and ESD system integration module is connected to the input end of the emergency plan module, the output end of the emergency plan module is connected to the input end of the historical information backup module, and the output end of the historical information backup module is connected to the input end of the historical information analysis module.

[0020] In this embodiment, the method utilizes a hot pressing process to achieve the adhesion of the copper mesh to the product. By adopting this method, a large amount of spray agent is not required to participate in the operation, so that a large amount of chemical agents will not contact the product surface, thereby effectively improving the service life of the product.

[0021] Example 2 See also Figure 1 The present invention provides a technical solution: a remote collaborative maintenance and diagnosis method for an LNG intelligent control valve, comprising the following steps: S1. Through the IIoT network, the system transmits the data collected by the sensors installed on the LNG control valve to the cloud server and local controller in real time. The terminals can communicate with each other through the wireless network to ensure the reliability and low latency of multi-terminal data transmission. The wireless network is a 5G network. S2. Collect data and transmit it to the cloud analysis platform. Through the built-in fault diagnosis algorithm, the system can monitor and analyze data fluctuations in real time, determine the fault location, and provide detailed fault information. The collected data includes temperature, pressure, and flow data; S3. After diagnosing a fault, the system will automatically generate a maintenance plan, optimize operating parameters based on historical operating data using a decision model, and provide maintenance recommendations. If the fault is serious, the system will trigger the automatic maintenance function and transmit the maintenance command to the on-site controller or operator via the wireless network. The time it takes for the system to automatically generate a maintenance plan is ≤ 3 seconds. S4. The operator of the LNG system can view the operating status and fault diagnosis results of the control valve in real time through the remote terminal, which is a tablet; S5. After a fault occurs, the system will generate a maintenance plan and push it to the operator's device. If an emergency shutdown is required, the system will seamlessly notify the STS and ESD systems to perform relevant operations to avoid delays; S6. When the system detects an extreme abnormal situation, it will implement an emergency plan. Specifically, the system will communicate directly and automatically with the STS and ESD systems to trigger an emergency shutdown or shut down the valve to avoid more serious accidents. S7. Back up historical diagnosis and detection information and transfer the backup information to the cloud platform for storage; S8. Regularly analyze historical related information, generate 4 transformation plans for LNG intelligent control valves based on the analysis results, and simulate the transformation plans for LNG intelligent control valves. After the simulation, evaluation is performed and the evaluation results are divided into three types: excellent, good and poor. The transformation plan with an excellent evaluation result is selected.

[0022] The present invention also discloses a remote collaborative maintenance and diagnosis system for an LNG intelligent control valve, comprising a multidimensional data acquisition module and a real-time data transmission module, wherein the output end of the multidimensional data acquisition module is connected to the input end of the real-time data transmission module, the output end of the real-time data transmission module is connected to the input end of the automatic data analysis module, the output end of the automatic data analysis module is connected to the input end of the remote fault diagnosis module, the output end of the remote fault diagnosis module is connected to the input end of the prevention and control decision module, the output end of the prevention and control decision module is connected to the input end of the STS and ESD system integration module, the output end of the STS and ESD system integration module is connected to the input end of the emergency plan module, the output end of the emergency plan module is connected to the input end of the historical information backup module, and the output end of the historical information backup module is connected to the input end of the historical information analysis module.

[0023] In this embodiment, the method adds a step of re-attaching a layer of rubber protective layer to the surface of the copper mesh. After the product reaches the end of its service life, because the surface of the copper mesh is protected by a layer of rubber, even if the internal copper mesh is damaged during use, it will not scratch the operator during disassembly, thereby improving the safety of the overall product.

[0024] Example 3 See also Figure 1 The present invention provides a technical solution: a remote collaborative maintenance and diagnosis method for an LNG intelligent control valve, comprising the following steps: S1. Through the IIoT network, the system transmits the data collected by the sensors installed on the LNG control valve to the cloud server and local controller in real time. The terminals can communicate with each other through the wireless network to ensure the reliability and low latency of multi-terminal data transmission. The wireless network is a 5G network. S2. Collect data and transmit it to the cloud analysis platform. Through the built-in fault diagnosis algorithm, the system can monitor and analyze data fluctuations in real time, determine the fault location, and provide detailed fault information. The collected data includes temperature, pressure, and flow data; S3. After diagnosing a fault, the system will automatically generate a maintenance plan, optimize operating parameters based on historical operating data using a decision model, and provide maintenance recommendations. If the fault is serious, the system will trigger the automatic maintenance function and transmit the maintenance command to the on-site controller or operator via the wireless network. The time it takes for the system to automatically generate a maintenance plan is ≤ 3 seconds. S4. The operator of the LNG system can view the operating status and fault diagnosis results of the control valve in real time through the remote terminal, which is a mobile phone; S5. After a fault occurs, the system will generate a maintenance plan and push it to the operator's device. If an emergency shutdown is required, the system will seamlessly notify the STS and ESD systems to perform relevant operations to avoid delays; S6. When the system detects an extreme abnormal situation, it will implement an emergency plan. Specifically, the system will communicate directly and automatically with the STS and ESD systems to trigger an emergency shutdown or shut down the valve to avoid more serious accidents. S7. Back up historical diagnosis and detection information and transfer the backup information to the cloud platform for storage; S8. Regularly analyze historical related information, generate 5 modification plans for LNG intelligent control valves based on the analysis results, and simulate the modification plans for LNG intelligent control valves. After the simulation, evaluation is performed and the evaluation results are divided into three types: excellent, good and poor. The modification plan with an excellent evaluation result is selected.

[0025] The present invention also discloses a remote collaborative maintenance and diagnosis system for an LNG intelligent control valve, comprising a multidimensional data acquisition module and a real-time data transmission module, wherein the output end of the multidimensional data acquisition module is connected to the input end of the real-time data transmission module, the output end of the real-time data transmission module is connected to the input end of the automatic data analysis module, the output end of the automatic data analysis module is connected to the input end of the remote fault diagnosis module, the output end of the remote fault diagnosis module is connected to the input end of the prevention and control decision module, the output end of the prevention and control decision module is connected to the input end of the STS and ESD system integration module, the output end of the STS and ESD system integration module is connected to the input end of the emergency plan module, the output end of the emergency plan module is connected to the input end of the historical information backup module, and the output end of the historical information backup module is connected to the input end of the historical information analysis module.

[0026] In this embodiment, the method uses environmentally friendly glue when processing the rubber protective layer, which can effectively improve environmental protection while protecting the product itself, and optimizes the problem of difficult trimming of the flash of the product on the surface of the previous product copper mesh during the rubber production process.

[0027] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. LNG intelligent control valve remote collaborative maintenance and diagnosis method, characterized by: The steps include: S1. Collect data on the LNG control valve through various sensors. Through the IIoT network, the system transmits the data collected by the sensors installed on the LNG control valve to the cloud server and local controller in real time; S2. Collect data and transmit it to the cloud analysis platform. Through the built-in fault diagnosis algorithm, the system can monitor and analyze data fluctuations in real time, determine the fault location, and provide detailed fault information; S3. After diagnosing a fault, the system will automatically generate a maintenance plan, optimize operating parameters based on historical operating data, and provide maintenance recommendations using decision-making models; S4. LNG system operators can view the operating status and fault diagnosis results of the control valve in real time through the remote terminal; S5. After a fault occurs, the system will generate a maintenance plan and push it to the operator's device; S6. When the system detects an extreme abnormal situation, it will implement an emergency plan; S7. Back up historical diagnosis and testing information; S8. Regularly analyze historical related information.

2. The remote collaborative maintenance and diagnosis method for LNG intelligent control valve according to claim 1 is characterized in that: In S1, the system transmits the data collected by the sensor installed on the LNG control valve in real time to the cloud server and the local controller through the IIoT network. The terminals can communicate with each other through the wireless network to ensure the reliability and low latency of multi-terminal data transmission. The wireless network is one of 5G or LoRa.

3. The remote collaborative maintenance and diagnosis method for LNG intelligent control valve according to claim 1 is characterized in that: In S2, the collected data is transmitted to the cloud analysis platform. Through the built-in fault diagnosis algorithm, the system can monitor and analyze data fluctuations in real time, determine the fault location, and provide detailed fault information. The collected data includes temperature, pressure, and flow data.

4. The remote collaborative maintenance and diagnosis method for LNG intelligent control valve according to claim 1 is characterized in that: In S3, after diagnosing a fault, the system will automatically generate a maintenance plan, optimize operating parameters based on historical operating data using a decision model, and provide maintenance recommendations. If the fault is serious, the system will trigger an automatic maintenance function and transmit the maintenance command to the on-site controller or operator via a wireless network. The time it takes for the system to automatically generate a maintenance plan is ≤3 seconds.

5. The remote collaborative maintenance and diagnosis method for LNG intelligent control valve according to claim 1 is characterized in that: In S4, the operator of the LNG system can view the operating status and fault diagnosis results of the control valve in real time through a remote terminal, and the remote terminal is a mobile phone or a tablet.

6. The remote collaborative maintenance and diagnosis method for LNG intelligent control valve according to claim 1 is characterized in that: In S5, after a fault occurs, the system will generate a maintenance plan and push it to the operator's device. If an emergency shutdown is required, the system will seamlessly notify the STS and ESD systems to perform relevant operations to avoid delays.

7. The remote collaborative maintenance and diagnosis method for LNG intelligent control valve according to claim 1 is characterized in that: In S6, when the system detects an extreme abnormal situation, an emergency plan is implemented. Specifically, the system will directly and automatically communicate with the STS and ESD systems to trigger an emergency shutdown or shut down the valve to avoid more serious accidents.

8. The remote collaborative maintenance and diagnosis method for LNG intelligent control valve according to claim 1 is characterized in that: In S7, the historical diagnosis and detection information is backed up, and the backup information is transmitted to the cloud platform for storage.

9. The remote collaborative maintenance and diagnosis method for LNG intelligent control valve according to claim 1 is characterized in that: In S8, historical related information is analyzed regularly, and based on the analysis results, 3-5 modification plans for the LNG intelligent control valve are generated, and the modification plans for the LNG intelligent control valve are simulated. After the simulation, evaluation is performed, and the evaluation results are divided into three types: excellent, good and poor. The modification plan with an excellent evaluation result is selected. 10.LNG intelligent control valve remote collaborative maintenance and diagnosis system, characterized by: It includes a multidimensional data acquisition module and a real-time data transmission module, the output end of the multidimensional data acquisition module is connected to the input end of the real-time data transmission module, the output end of the real-time data transmission module is connected to the input end of the automatic data analysis module, the output end of the automatic data analysis module is connected to the input end of the remote fault diagnosis module, the output end of the remote fault diagnosis module is connected to the input end of the prevention and control decision module, the output end of the prevention and control decision module is connected to the input end of the STS and ESD system integration module, the output end of the STS and ESD system integration module is connected to the input end of the emergency plan module, the output end of the emergency plan module is connected to the input end of the historical information backup module, and the output end of the historical information backup module is connected to the input end of the historical information analysis module.

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