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Similarity-based fault isolation method of train suspension system

A fault separation and suspension system technology, applied in railway vehicle testing and other directions, can solve problems such as the lack of clear train suspension system status monitoring and fault detection object systems and methods, and achieve the effect of ensuring the safe operation of trains and guiding inspection and maintenance.

Inactive Publication Date: 2013-04-03
BEIJING JIAOTONG UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

In the technical system for the state monitoring of the train running system, the wheels, bearings, bogie frames and other parts are also the main parts, and there are almost no systems and methods that use the train suspension system as the object of state monitoring and fault detection

Method used

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  • Similarity-based fault isolation method of train suspension system
  • Similarity-based fault isolation method of train suspension system
  • Similarity-based fault isolation method of train suspension system

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Embodiment Construction

[0044] The hardware structure, composition and fault isolation method of the present invention will be described below in conjunction with the accompanying drawings.

[0045] 1. System structure framework

[0046] Such as figure 1 Shown is a structural frame diagram of the fault diagnosis system of the present invention, the fault detection system includes: sensors, used to obtain the acceleration information of the train at various positions; a data acquisition unit, responsible for connecting the sensors and the data preprocessing unit, and sending the simulated The signal is converted into a format that can be recognized by the data preprocessing unit, and sent to the data preprocessing unit with a unified communication protocol to realize the collection and conversion of the measurement data of each sensor; the data preprocessing unit is responsible for the data management of each signal collection unit and Vehicle network management, and receive the data sent by the data...

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Abstract

The invention relates to a similarity-based fault isolation method of a train suspension system. The method includes taking the train suspension system as a condition monitoring and fault diagnosis object, obtaining a system output residual through analyzing the motion state during operation of a train and Kalman filtering, obtaining fault signal frequency domain information through performing fast Fourier transform on the system output residual, and calculating a similarity score of a currently detected fault and a typical fault through the Eros algorithm to determine the type and position of the current fault. The method achieves intelligent isolation of train suspension system faults and plays important roles in guaranteeing train safe operation, guiding maintenance and overhauling of the train suspension system and improving the train operating efficiency.

Description

technical field [0001] The invention relates to a similarity-based fault separation method for a train suspension system. Background technique [0002] The train suspension system is located between the train body and the bogie and between the bogie and the wheelset, and consists of a large number of different components, including coil springs, dampers, air springs, etc. The suspension system of a rail vehicle is usually divided into a primary system (located between the wheel set and the bogie) and a secondary system (located between the bogie and the car body), and it is also divided into horizontal and vertical according to its influence on the motion state of the train. system. On the one hand, the suspension system supports the car body and the bogie; on the other hand, the suspension system also plays the role of buffering the wheel-rail force caused by track irregularities, controlling the direction of the train, and maintaining running comfort. [0003] At present...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M17/10
Inventor 魏秀琨贾利民柳海汪煜婷郭淑萍林帅郭昆
Owner BEIJING JIAOTONG UNIV
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