Journal
ELECTRONICS LETTERS
Volume 52, Issue 10, Pages 818-819Publisher
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/el.2016.0206
Keywords
fault diagnosis; condition monitoring; railway electrification; fault diagnosis; railway point machines; dynamic time warping; condition monitoring method; in-field failure data; railway train operations; RPM movement; abnormal electric-current shape detection; training-based methods
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Funding
- project Small & Medium Business Administration [S2312692]
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A practical condition monitoring method is proposed for the fault diagnosis of railway point machines (RPMs) by considering the difficulty of obtaining in-field failure data. Failures in RPMs have a significant effect on railway train operations, and it is very crucial to detect abnormal conditions in RPMs. However, it is generally difficult to obtain in-field failure data for a classifier training step. A diagnosis method using dynamic time warping is proposed to manage the variation in durations of RPM movement without a training step. On the basis of the experimental results with RPMs operated in Korea, it is believed that the proposed method without a training step can detect abnormal electric-current shapes more accurately than previous training-based methods.
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