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

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 invol...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEJ transactions on electrical and electronic engineering 2023-07, Vol.18 (7), p.1211-1213
Hauptverfasser: Kashiwao, Tomoaki, Kawakami, Kota, Ikoma, Takeshi, Takagi, Kazuhiko, Tanaka, Daisuke, Ikeda, Kenji
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
ISSN:1931-4973
1931-4981
DOI:10.1002/tee.23830