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Fault detection method for maglev train based on threshold judgment based on ga-bp

A GA-BP and maglev train technology, applied in the field of rail transit fault diagnosis, can solve problems such as inapplicability, many related influencing factors, and complex models

Active Publication Date: 2021-02-02
HANGZHOU DIANZI UNIV
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Problems solved by technology

Since the magnetic levitation has no mechanical contact, the model is relatively complex, and there are too many relevant influencing factors, so the traditional model-based fault diagnosis is not applicable

Method used

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  • Fault detection method for maglev train based on threshold judgment based on ga-bp
  • Fault detection method for maglev train based on threshold judgment based on ga-bp
  • Fault detection method for maglev train based on threshold judgment based on ga-bp

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Embodiment Construction

[0083] The present invention is further analyzed below in conjunction with specific accompanying drawings.

[0084] Such as figure 1 As shown, the GA-BP fault detection method for maglev trains based on threshold judgment, the steps are as follows:

[0085] Step 1. Obtain the required data by installing multiple sets of acceleration, current, and gap sensors on the train, and filter and preprocess the original data. Screen 40,000+ data, select 18,000+ data, and use the five-point average method to process the data for missing detection data and over-detection data for the selected data. Then slice (t time period) for the processed data.

[0086] Step 2, using signal processing technology and statistical learning method to extract the characteristic parameters within the time period t for each type of data processed in step 1. The characteristic parameters include time-domain indicators, frequency-domain indicators and time-frequency features.

[0087] 2.1 Time Domain Index...

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Abstract

The invention discloses a GA-BP maglev train fault detection method based on threshold value judgment. The characteristic parameters of the data obtained by the sensor are normalized as the BP input, and the variance threshold and change rate are used as the output to judge the fault, and the genetic algorithm is used to optimize the optimal network weight and threshold to improve the detection accuracy of the BP neural network. The invention can accurately diagnose whether the magnetic levitation train has a vibration fault, and avoids false alarms.

Description

technical field [0001] The invention relates to rail transit fault diagnosis technology, in particular to a GA-BP maglev train fault detection method based on threshold value judgment. Background technique [0002] my country's railways have developed rapidly over the years. By the end of 2017, the operating mileage of railways had reached 127,000 kilometers, including 25,000 kilometers of high-speed rail, ranking first in the world. Magnetic levitation has also ushered in rapid development since the 21st century. It satisfies the diverse travel modes of the people. With the improvement of people's living standards, the comfort of the riding experience is also constantly improving. [0003] The safety and reliability of vehicle operation and ride comfort are all very important indicators of ride. Fault diagnosis technology can improve the safety and reliability of train operation and ride comfort by judging the abnormal state caused by the vibration of the train in operat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M17/08G01R31/00G06N3/12
CPCG01M17/08G01R31/005G06N3/126
Inventor 汪俊杰游科友彭冬亮王引苗
Owner HANGZHOU DIANZI UNIV
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