Train bogie fault identification method based on biological information characteristics

A bogie and genetic feature technology, applied in the field of fault identification, can solve problems such as not advocating universal use, easy to break the running-in state, etc., to speed up information exchange, reduce blindness in maintenance and improvement, and lower personnel threshold.

Active Publication Date: 2019-09-13
CENT SOUTH UNIV
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Problems solved by technology

This is a relatively high-tech fault detection method in addition to visual inspection. The result is very intuitive

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  • Train bogie fault identification method based on biological information characteristics
  • Train bogie fault identification method based on biological information characteristics
  • Train bogie fault identification method based on biological information characteristics

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Embodiment Construction

[0085] The following is a detailed description of the embodiments of the present invention. This embodiment is carried out based on the technical solution of the present invention, and provides detailed implementation methods and specific operation processes to further explain the technical solution of the present invention.

[0086] Such as figure 1 As shown, the train bogie fault identification method based on biological information features provided by the present invention comprises the following steps:

[0087] Step 1, constructing a corresponding DNA sequence set for each fault type;

[0088] Step A1, collect the historical vibration signal of the train bogie through the vibration acquisition instrument; then perform wavelet threshold filtering on the historical vibration signal to eliminate the interference noise in the historical vibration signal; then perform PCA dimension reduction processing on the vibration signal after the interference noise is eliminated , to ob...

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Abstract

The invention discloses a train bogie fault identification method based on biological information characteristics, which comprises the following steps: obtaining a historical vibration signal of a train bogie, and preprocessing and converting the historical vibration signal into an artificial DNA sequence; obtaining all window sequences through a sliding window method, and selecting a feature sequence meeting a preset requirement from the window sequences; taking the contents of four bases in the artificial DNA sequence, the sequence length and the number of the characteristic sequences as gene characteristic vectors of the artificial DNA sequence; constructing a training sample by using the gene feature vector of the artificial DNA sequence, and training a corresponding LPBoost binary classifier for each fault type; therefore, during fault detection, inputting the corresponding gene feature vector into each LPBoost binary classifier, and determining the fault type of the train bogie to be detected through a voting method. According to the invention, the feature sequence causing each fault type is mined, so that accurate identification and classification of various fault types arerealized.

Description

technical field [0001] The invention relates to the field of fault identification, in particular to a method for identifying a train bogie fault based on biological information features. Background technique [0002] In recent years, with the rapid development of rail transportation technology such as high-speed railways, subways, and maglev trains, railway transportation has become the main mode of transportation for people in our country. Just because the status of railways in the national economy is so important, its safety has naturally become a major concern of the people. This issue is particularly important today as trains continue to increase rapidly. People pay more and more attention to the safety of train operation. In many rail vehicle systems, the bogie (running part) is one of the most core parts, and the monitoring of the running turntable of the bogie is the key point to ensure the safe operation of the train. In recent years, some train safety accidents c...

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Application Information

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IPC IPC(8): G06K9/62G06N3/12G01M17/08
CPCG06N3/123G01M17/08G06F18/2135G06F18/2411G06F18/214
Inventor 刘辉杨睿
Owner CENT SOUTH UNIV
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