Crossing-Gate Rod Breakage Detection in a Railway Telemeter System Using Machine Learning

被引：4

作者：

Kashiwao, Tomoaki ^{[1
]}

Tanoue, Hiroya ^{[1
]}

Shiraishi, Noriyuki ^{[2
]}

Misaki, Yuki ^{[2
]}

Ando, Takashi ^{[2
]}

Ikeda, Kenji ^{[3
]}

Tanaka, Daisuke ^{[4
]}

机构：

[1] Kindai Univ, Grad Sch Sci & Engn, 3-4-1 Kowakae, Higashi Osaka, Osaka 5778502, Japan

[2] Shikoku Railway Co, Engn Dept, 8-33 Hamano Cho, Takamatsu, Kagawa 7608580, Japan

[3] Tokushima Univ, Grad Sch Technol Ind & Social Sci, 2-1 Minamijosanjima Cho, Tokushima 7708506, Japan

[4] Niihama Coll, Dept Mech Engn, Natl Inst Technol, 7-1 Yagumo Cho, Niihiuna, Ehime 7928580, Japan

来源：

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING | 2023年 / 18卷 / 01期

关键词：

railway; telemeter system; machine learning; random forest; support vector machine; failure detection;

D O I：

10.1002/tee.23710

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Shikoku Railway Company (JR Shikoku) has installed a telemeter system whose network spreads across all the railway lines in the Shikoku area. The telemeter system monitors and collects real-time data, e.g. current, voltage, and relay signals of railway equipment. We propose a method of detecting the breakage of a crossing-gate rod based on big data using representative machine-learning techniques, namely, random forest and support vector machine. Moreover, we evaluate the proposed method for rod breakage cases at seven locations and demonstrate its effectiveness and versatility. (c) 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

引用

页码：156 / 158

页数：3

共 3 条

[1]

Tanaka D., 2019, P 23 C CULT HER NEW, VSS1-5, P1

[2]

Tanoue H., 2021, P SAMCON 2021, P278

[3] Prediction of accelerator operation using machine learning [J].

Yamanokuchi, Tomoya ;

Ando, Shin ;

Kinoshita, Koji ;

Bahadori, Alireza ;

Kashiwao, Tomoaki .

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2018, 13 (04) :656-657

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