A One‐Class <scp>SVM</scp>‐Based Approach for Crossing‐Gate Rod Breakage Detection in a Railway Telemeter System-Reference-Cited by-同舟云学术

A One‐Class SVM‐Based Approach for Crossing‐Gate Rod Breakage Detection in a Railway Telemeter System

Published:2023-01-14 Issue:4 Volume:18 Page:648-650
ISSN:1931-4973
Container-title:IEEJ Transactions on Electrical and Electronic Engineering
language:en
Short-container-title:IEEJ Transactions Elec Engng

Author:

Kashiwao Tomoaki¹,Tanoue Hiroya¹,Shiraishi Noriyuki²,Misaki Yuki²,Ando Takashi²,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

AbstractShikoku Railway Company (JR Shikoku) has installed a telemeter system network across all railway lines in the Shikoku area for collecting real‐time equipment data. In a previous study, we proposed a supervised machine learning‐based method to detect crossing‐gate rod breakages from the big data collected by the telemeter system. However, this method requires past data, including breakage cases of each crossing‐gate rod, for training. To avoid the past‐data problem, we propose a method that applies a one‐class support vector machine (SVM) with unsupervised learning to the rod breakage detection. The detection results were evaluated based on performance on real‐word railway data. © 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Publisher

Wiley

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/tee.23762

Reference3 articles.

1. TanakaD IshiokaH MisakiY TamehiroS IkedaK KashiwaoT.Big‐data analysis of railway‐telemeter system. Proc. of SAMCON 2019 SS1–5 Chiba Univ. Japan 2019; 1–4.

2. TanoueH KashiwaoT MisakiY AndoT IkedaK TanakaD.A machine‐learning based detection method of crossing‐gate rod breakage in a railway telemeter system Proc. of SAMCON 2021 pp. 278–279 Univ. of Tokyo Japan 2021.

3. Crossing‐Gate Rod Breakage Detection in a Railway Telemeter System Using Machine Learning

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