A real-time fault diagnosis method for urban rail transit vehicles based on working condition detection
A technology for urban rail transit and fault diagnosis, which is applied in the detection of faulty computer hardware and the use of fault dictionaries to detect faulty hardware. , to achieve real-time fault diagnosis, reduce the number of knowledge matching, and improve execution speed.
Active Publication Date: 2020-11-10
HOHAI UNIV
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Problems solved by technology
Since it is impossible to locate which type of knowledge in the knowledge base the collected data is related to, in order to ensure the integrity and accuracy of the fault diagnosis results, the mass data collected can only be matched and judged with a large amount of knowledge in the knowledge base. Reduce the execution speed of the diagnosis system and the accuracy of fault judgment, making it impossible to realize real-time fault diagnosis
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[0030] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention will be further explained below in conjunction with specific embodiments.
[0031] In the present invention, by determining the collected data points that can uniquely identify the characteristics of each operating condition of the train, a character sequence of operating conditions is formed and stored in a database, and the diagnostic knowledge base is divided into blocks according to operating conditions. Then the collected data is matched with the character sequence for similarity, and the character sequence of the working condition with the highest matching degree is the working condition of the current collected data. Finally, the diagnosis knowledge block corresponding to the working condition is judged one by one, which greatly reduces the number of knowledge matching. It not only effectively accelerates the exe...
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The invention discloses a method for real-time fault diagnosis of urban rail transit vehicles based on working condition detection. In the method, a characteristic character sequence database of eachworking condition is established and a fault diagnosis knowledge base is established based on working condition classification; real-time vehicle data are collected and acquired; according to a similarity calculation formula based on time sequences, the similarity between real-time data sequences and characteristic character sequences of working conditions is calculated, the working condition indexes of the vehicle data are determined, and according to the indexes of the diagnosis knowledge base, faults are classified and diagnosed by use of the fault diagnosis knowledge base to obtain diagnosis results. The method greatly reduces the amount of matching of the real-time mass data of vehicles with the knowledge of the fault diagnosis knowledge base, improves the execution speed of a diagnosis system and the accuracy of fault diagnosis, and realizes the real-time fault diagnosis of the urban rail transit vehicles.
Description
Technical field [0001] The invention relates to a real-time fault diagnosis method of urban rail transit vehicles based on working condition detection, and belongs to the technical field of real-time fault diagnosis of urban rail transit vehicles. Background technique [0002] Urban rail transit vehicles include traction, auxiliary, braking, door control, air-conditioning and other subsystems. The logical relationship between the components in each subsystem, the logical relationship between the subsystems and the status of the components in the system constitute the fault diagnosis of the vehicle knowledge base. Therefore, the number of fault diagnosis knowledge bases of a vehicle is very large, and the knowledge required to judge one by one after the collected data is input into the diagnosis system is also very large. In addition, the vehicle fault diagnosis system is faced with a massive influx of hundreds of megabytes of collected data every day. If the traditional vehicle ...
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IPC IPC(8): G06F11/22
CPCG06F11/2252
Inventor 沈洁李臣明王慧斌张丽丽潘朝君
Owner HOHAI UNIV