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Wheel service state safety margin estimation and fault diagnosis method

A service state and fault diagnosis technology, applied in the field of traffic safety engineering, can solve problems such as the inability to provide clear policy guidance for vehicle repair and maintenance, and the inability to give the service state of wheels, etc., to achieve high precision, high stability, and convergence speed fast effect

Inactive Publication Date: 2016-12-21
NANJING UNIV OF SCI & TECH
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

Although these methods can realize the identification of wheel defects and faults, they cannot give the specific service status of the wheels, so they cannot provide clear strategic guidance for vehicle repair and maintenance.

Method used

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  • Wheel service state safety margin estimation and fault diagnosis method
  • Wheel service state safety margin estimation and fault diagnosis method
  • Wheel service state safety margin estimation and fault diagnosis method

Examples

Experimental program
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Effect test

Embodiment 1

[0092] Using the vehicle-track vertical coupling dynamics model for simulation, 220 sets of rail vibration signals of normal wheels, 220 sets of rail vibration signals of flat-scar wheels and 220 sets of rail vibration signals of out-of-round wheels are obtained. The vibration signals of each set include 2000 data points. 220 groups of normal wheel signals and 440 groups of faulty wheel signals are decomposed by EMD to obtain each IMF component;

[0093] Calculate the energy moment of each IMF component, and use the calculation result as the state eigenvector of the vibration signal, with figure 2 is the IMF characteristic index value of the normal wheel, since the IMF order decomposed by EMD of each signal is not exactly the same, here we take the least IMF order after decomposing 660 signals as the construction feature vector:

[0094] T=[t 1 t 2 ...t n ]

[0095] In the formula, T is the feature vector constructed by each index, and n is the least IMF order.

[0096]...

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Abstract

The invention discloses a wheel service state safety margin estimation and fault diagnosis method. The wheel service state safety margin estimation and fault diagnosis method comprises the following steps of firstly carrying out feature extraction for a steel rail vibration signal, decomposing the steel rail vibration signal by adopting an EMS (Empirical Mode Decomposition) method, calculating related characteristic indexes of each IMF (Intrinsic Mode Function) to serve as a characteristic vector of a wheel service state; secondly, classifying normal and fault states by utilizing LSSVM based on state characteristic vectors of steel rail vibration signals of a normal wheel and a faulted wheel, obtaining a safety margin of a train wheel and estimating the train wheel service state; and finally, carrying out fault mode identification for a normal wheel, a flat damage wheel and an out-of-round wheel by adopting a PNN (Probabilistic Neural Network), and providing reference basis for a vehicle maintenance department. The wheel service state safety margin estimation and fault diagnosis method has the advantages of high reliability and good engineering feasibility.

Description

technical field [0001] The invention belongs to the technical field of traffic safety engineering, in particular to a method for estimating the safety region of a wheel in service state and diagnosing a fault. Background technique [0002] As one of the most basic and important components of the running system, the train wheel set bears the weight of the entire train and ensures the normal operation of the train on the track. It is the key detection object in the safety inspection of the running system. During the operation of the train, the wheelset and the rail are constantly rubbing against each other, and the state of the tread of the wheel set is also constantly changing. When the contact relationship between the wheel and the rail is not good, faults such as abrasion and peeling of the tread are prone to occur, which will affect the normal safety of the train. Therefore, it is of great significance to estimate the service state safety region and fault diagnosis of the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G01H17/00
CPCG01H17/00G06F30/15G06F30/20
Inventor 杨静黄瑛杨志邢宗义
Owner NANJING UNIV OF SCI & TECH
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