The Research on Diagnosis Technology of High-speed Train Power Chain Based on Electrical Signal
Transmission machineries such as traction motors, couplings and gears are widely used in rail transit vehicles,which are regarded as important parts of the power chain of high-speed trains. Due to the long-term operation in complex and harsh environment, the influence of wide speed range, heavy load...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Electric Drive for Locomotives
2021-01-01
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| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2021.01.001 |
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| Summary: | Transmission machineries such as traction motors, couplings and gears are widely used in rail transit vehicles,which are regarded as important parts of the power chain of high-speed trains. Due to the long-term operation in complex and harsh environment, the influence of wide speed range, heavy load conditions and rail surface impact, the transmission components are easy to cause faults, which will affect the normal operation of vehicles and traffic order. Therefore, warning potential faults timely is of great significance to guarantee the normal operation and traffic order of rail transit vehicles. Because the diagnosis method based on electrical signal has the advantages of easy signal acquisition, high signal reliability and accuracy, non-embedded monitoring of object equipment,it has gradually become a research hotspot in the field of rail transit diagnosis. The fault mechanism of key components in rail transit vehicles power chain was first described. Taking the diagnosis method based on electrical signal as the breakthrough point, the existing diagnosis methods and research findings in this field was sorted out and analyzed. Then, based on the theory of multi-feature fusion and machine learning, a new electrical signal diagnosis method was proposed. The data of each electrical signal was obtained, the wavelet de-noising was performed first, and the signal-to-noise ratio was improved through signal decomposition and reconstruction, then different fault features were extracted based on the reconstructed signals, and finally the decision tree to integrate the fault features for diagnosis was used. The verification test and actual application results showed that the electrical signal diagnosis method proposed in this research can effectively detect and identify power chain faults, realize early fault warning, which can ensure the driving safety of vehicles. |
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| ISSN: | 1000-128X |