Intelligent maintenance system for rail transit vehicle

Abstract

The invention relates to the technical field of rail transit, in particular to a rail transit vehicle intelligent maintenance system, which comprises a database storage module, a data acquisition module, a fault diagnosis module and a data touch module, and is characterized in that the database storage module comprises a rail transit vehicle fault database and a rail transit vehicle fault data entry system; the data acquisition module comprises a machine vision fault monitoring and acquisition system, a sensor data monitoring and acquisition system, a wired data transmission system, a wireless data transmission system and an electronic work order import and input system; the fault diagnosis module comprises a fault diagnosis model based on fault big data and machine learning, and an intelligent decision-making model based on rail transit vehicle fault maintenance big data and machine learning. Through the rail transit vehicle maintenance system, maintenance data accumulated for many years of lines can be combined with artificial intelligence, and a traditional maintenance mode completely relying on experience of a maintainer is converted into AI intelligent maintenance and AI fault diagnosis.

Description

Technical Field

[0001] The present invention relates to the technical field of rail transit systems, and in particular to an intelligent maintenance system for rail transit vehicles. Background Art

[0002] The increasing complexity of the rail transit system and the increasing requirements for passenger timeliness have put forward new requirements for the maintenance process, which are accurate, fast and reliable. With the acceleration of urbanization, the importance of the rail transit system has become increasingly prominent. However, the traditional rail transit vehicle maintenance method has many shortcomings, such as reliance on manual experience, low efficiency, and high misjudgment rate. The rail transit vehicle intelligent maintenance system came into being to solve these problems. By integrating technologies such as big data analysis and artificial intelligence, the rail transit vehicle maintenance process is comprehensively upgraded to improve maintenance efficiency and accuracy and ensure the safe operation of the vehicle. This project focuses on using massive maintenance data, exploring the hidden value behind it, exploring a new data-driven productivity model, and realizing the transformation from traditional maintenance methods to intelligent and efficient ones. By building an intelligent fault diagnosis and maintenance intelligent decision-making system, the "rail transit vehicle intelligent maintenance system" can not only assist technicians to accurately locate the source of the fault and reduce the misjudgment rate, but also significantly shorten the maintenance time to ensure the safe and reliable operation of the train. This innovative invention aims to create a comprehensive solution that integrates data analysis and intelligent diagnosis technology, effectively improve the overall maintenance efficiency of subway operators, and provide employees with a more scientific and reasonable working environment to promote the effective allocation of human resources. This system assists maintenance engineers in performing maintenance operations in multiple dimensions, including professional skills operation, fault diagnosis and maintenance, team division of labor, professional quality, and innovation ability. The efficient and innovative human-machine collaborative operation method strives to better serve the overall development of urban transportation through continuous technological innovation and service optimization, and contribute to the construction of the national intelligent transportation system. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent maintenance system for rail transit vehicles to solve the many shortcomings of the traditional rail transit vehicle maintenance method proposed in the above background technology, such as reliance on manual experience, low efficiency, high misjudgment rate and other problems.

[0004] To achieve the above-mentioned objectives, the present invention provides the following technical solutions: an intelligent maintenance system for rail transit vehicles, comprising a database storage module, a data acquisition module, a fault diagnosis module, and a data access module, wherein the database storage module is used to store rail transit vehicle fault data and related files, the data acquisition module is responsible for collecting various types of data, the fault diagnosis module uses advanced algorithms to perform fault diagnosis, and the data access module ensures that relevant information can be communicated to relevant personnel or systems in a timely and accurate manner.

[0005] Preferably, the database storage module further includes a rail transit vehicle fault database, a file service system, and a rail transit vehicle fault data entry system, which can efficiently manage and utilize historical fault data.

[0006] Preferably, the data acquisition module includes a machine vision fault monitoring and acquisition system, a sensor data monitoring and acquisition system, a wired data transmission system, a wireless data transmission system, and an electronic work order import and entry system, ensuring the comprehensiveness and accuracy of multi-source data.

[0007] Preferably, the fault diagnosis module adopts a fault diagnosis model based on fault big data and machine learning, which improves the accuracy and efficiency of fault diagnosis.

[0008] Preferably, the fault diagnosis module also includes an intelligent decision-making model based on rail transit vehicle fault maintenance big data and machine learning, which can intelligently recommend the optimal maintenance plan based on actual conditions.

[0009] Preferably, the data access module includes a big data information display system, an email notification system, a text message notification system, and an in-system information push system, which ensures the immediacy and effectiveness of information transmission.

[0010] Preferably, the system also has a self-learning function, and can continuously optimize the fault diagnosis model and the intelligent decision-making model according to the newly generated fault data.

[0011] Preferably, the system can be seamlessly connected with the existing rail transit management platform to achieve data sharing and service integration.

[0012] Preferably, the system supports multi-user authority management, ensuring data security while facilitating the usage needs of users at different levels.

[0013] Preferably, the system provides an API interface to facilitate third-party developers to access and expand the functions and service scope of the system.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] The present invention firstly improves the maintenance efficiency. Through intelligent data analysis and fault diagnosis, the system can greatly reduce the time of manual judgment, thereby significantly improving the maintenance efficiency. Secondly, it reduces the misjudgment rate. By using advanced algorithms and technologies, the system can perform fault diagnosis more accurately, effectively reducing the occurrence of misjudgment. In addition, it ensures vehicle safety. The system can promptly detect and handle potential faults, ensure the safe and reliable operation of the vehicle, and provide passengers with a more secure travel experience. At the same time, it optimizes resource allocation. By intelligently recommending the optimal maintenance plan, the system can reasonably allocate human resources and further improve work efficiency. Finally, it improves the management level. The system is seamlessly connected with the existing management platform to realize data sharing, which helps to improve the overall management level and promote the intelligence and efficiency of rail transit operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is the architecture diagram of the rail transit vehicle intelligent maintenance system of the present invention;

[0017] Figure 2 This is a diagram of the intelligent maintenance model architecture based on fault maintenance big data of the present invention;

[0018] Figure 3 It is the intelligent maintenance workflow diagram of the present invention;

[0019] Figure 4 This is a traditional maintenance workflow diagram. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0021] See also Figure 1-3 An embodiment of the present invention is as follows: a rail transit vehicle intelligent maintenance system, comprising a database storage module, a data acquisition module, a fault diagnosis module, and a data access module, wherein the database storage module is used to store rail transit vehicle fault data and related files, the data acquisition module is responsible for collecting various types of data, the fault diagnosis module uses advanced algorithms to perform fault diagnosis, and the data access module ensures that relevant information can be conveyed to relevant personnel or systems in a timely and accurate manner.

[0022] Furthermore, the database storage module further includes a rail transit vehicle fault database, a file service system, and a rail transit vehicle fault data entry system, which can efficiently manage and utilize historical fault data. The rail transit vehicle fault database: stores historical fault records and their processing solutions; the file service system: manages documents related to faults; the fault data entry system: supports manual and automatic entry of fault data.

[0023] Furthermore, the data acquisition module includes a machine vision fault monitoring and acquisition system, a sensor data monitoring and acquisition system, a wired data transmission system, a wireless data transmission system, and an electronic work order import and entry system, which ensures the comprehensiveness and accuracy of multi-source data. The machine vision fault monitoring and acquisition system: uses cameras and other equipment to visually inspect the vehicle and identify potential faults; the sensor data monitoring and acquisition system: collects vehicle operating status data through various sensors; the wired data transmission system: supports data transmission through wired connections; the wireless data transmission system: supports data transmission through wireless networks; the electronic work order import and entry system: supports the import and manual entry of electronic work orders.

[0024] Furthermore, the fault diagnosis module adopts a fault diagnosis model based on fault big data and machine learning, which improves the accuracy and efficiency of fault diagnosis. The fault diagnosis model based on fault big data and machine learning: uses deep learning algorithms to analyze the collected data and diagnose potential faults.

[0025] Furthermore, the fault diagnosis module also includes an intelligent decision-making model based on rail transit vehicle fault maintenance big data and machine learning, which can intelligently recommend the optimal maintenance plan based on actual conditions. An intelligent decision-making model based on fault big data and machine learning: Based on historical fault data and current vehicle status, the optimal maintenance plan is intelligently recommended.

[0026] Furthermore, the data access module includes a big data information display system, an email notification system, a text message notification system, and an in-system information push system, which ensures the immediacy and effectiveness of information transmission. The big data information display system: displays fault data and analysis results through a visual interface; the email notification system: sends fault warnings and maintenance suggestions via email; the text message notification system: sends emergency fault information via text messages; the in-system information push system: sends notifications through the internal message system.

[0027] Furthermore, the system has the ability of self-learning, and can continuously optimize the fault diagnosis model and intelligent decision-making model according to the newly generated fault data, thereby improving the accuracy and efficiency of diagnosis.

[0028] Furthermore, the system can be seamlessly connected with the existing rail transit management platform to achieve data sharing and service integration, thereby improving overall management efficiency.

[0029] Furthermore, the system supports multi-user authority management, ensuring data security while facilitating the usage needs of users at different levels.

[0030] Furthermore, the system provides an API interface to facilitate third-party developers to access and expand the system's functions and service scope.

[0031] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

Claims

1. A rail transit vehicle intelligent maintenance system, characterized in that: It includes database storage module, data acquisition module, fault diagnosis module and data access module. The database storage module is used to store rail transit vehicle fault data and related files. The data acquisition module is responsible for collecting various types of data. The fault diagnosis module uses advanced algorithms to perform fault diagnosis. The data access module ensures that relevant information can be conveyed to relevant personnel or systems in a timely and accurate manner.

2. The intelligent maintenance system for rail transit vehicles according to claim 1 is characterized in that: The database storage module further includes a rail transit vehicle fault database, a file service system, and a rail transit vehicle fault data entry system, which can efficiently manage and utilize historical fault data.

3. The intelligent maintenance system for rail transit vehicles according to claim 1 is characterized in that: The data acquisition module includes a machine vision fault monitoring and acquisition system, a sensor data monitoring and acquisition system, a wired data transmission system, a wireless data transmission system, and an electronic work order import and entry system, ensuring the comprehensiveness and accuracy of multi-source data.

4. The intelligent maintenance system for rail transit vehicles according to claim 1, characterized in that: The fault diagnosis module adopts a fault diagnosis model based on fault big data and machine learning, which improves the accuracy and efficiency of fault diagnosis.

5. The intelligent maintenance system for rail transit vehicles according to claim 1 is characterized in that: The fault diagnosis module also includes an intelligent decision-making model based on rail transit vehicle fault maintenance big data and machine learning, which can intelligently recommend the optimal maintenance plan based on actual conditions.

6. The intelligent maintenance system for rail transit vehicles according to claim 1, characterized in that: The data access module includes a big data information display system, an email notification system, a text message notification system, and an in-system information push system, which ensures the immediacy and effectiveness of information transmission.

7. The intelligent maintenance system for rail transit vehicles according to any one of claims 1 to 6, characterized in that: The system also has a self-learning function, which can continuously optimize the fault diagnosis model and intelligent decision-making model according to the newly generated fault data.

8. The intelligent maintenance system for rail transit vehicles according to any one of claims 1 to 6, characterized in that: The system can be seamlessly connected with the existing rail transit management platform to achieve data sharing and service integration.

9. The intelligent maintenance system for rail transit vehicles according to any one of claims 1 to 6, characterized in that: The system supports multi-user authority management, ensuring data security while facilitating the usage needs of users at different levels.

10. The intelligent maintenance system for rail transit vehicles according to any one of claims 1 to 6, characterized in that: The system provides an API interface to facilitate third-party developers to access and expand the system's functions and service scope.

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