Real‐Time Crossing‐Gate Rod Breakage Detection Based on Sequential‐Dataset Classification for the Railway‐Telemeter System

Author:

Kashiwao Tomoaki1,Kawakami Kota1,Ikoma Takeshi2,Takagi Kazuhiko2,Tanaka Daisuke3,Ikeda Kenji4

Affiliation:

1. Graduate School of Science and Engineering Kindai University, 3–4–1 Kowakae, Higashi‐osaka Osaka 577–8502 Japan

2. Engineering Department Shikoku Railway Company, 8–33 Hamano‐cho Takamatsu Kagawa 760–8580 Japan

3. Department of Mechanical Engineering National Institute of Technology, Niihama College, 7–1 Yagumo‐cho Niihama Ehime 792–8580 Japan

4. Graduate School of Technology, Industrial and Social Sciences Tokushima University, 2–1 Minamijosanjima‐cho Tokushima 770–8506 Japan

Abstract

In our previous studies, we proposed crossing‐gate rod breakage detection methods based on machine learning techniques for the telemeter system installed by the Shikoku Railway Company (JR Shikoku) on railway lines in the Shikoku area to collect real‐time equipment data. However, these methods involve batch processing of many training data over several days, making them unsuitable for real‐time detection because of the long computation time. Therefore, this study improves these methods by performing sequential processing for real‐time detection for installation in the railway field. A one‐class support vector machine‐based detection method was applied to sequential processing to perform detection at each sampling period every few seconds. The proposed method is evaluated and its effectiveness is demonstrated in two representative cases of crossing‐gate rod breakage. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Publisher

Wiley

Subject

Electrical and Electronic Engineering

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