ニューラルネットワークによる列車走行音からの線路内異常検知手法

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2022/10/01

タイトル(英語): Detection of Abnormalities on Railway Track Based on Running Sound of Trains with Neural Network

著者名: 吉川　岳（公益財団法人 鉄道総合技術研究所）

著者名(英語): Gaku Yoshikawa (Railway Technical Research Institute)

キーワード: 無人運転，異音検知，ニューラルネットワーク_x000D_　　driverless trains，abnormal-sound detection，neural network

要約(英語): In the case of driverless trains, the ability of abnormal-sound detection which traditionally has been based on crew's ears will be lost. To make up this, this paper proposes an abnormal-noise detection system using microphones under trains. The feature of the system is to determine the abnormalities on railway track not only based on the sound but also the velocity and the position of the train. To accomplish that, the system uses neural network which is able to predict normal sound level based on the velocity and the position.In the system, when the running sound is extremely larger than the predicted normal sound, it would be determined as abnormal sound. To verify the effectiveness of the system, test running is conducted where the test train passes on a stone located on the rail. Through the test running, we have confirmed that the system would be able to detect the abnormal sound due to the stone in case the train passes on the stone at over 20km/h.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.142 No.10 （2022）

本誌掲載ページ: 752-761 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejias/142/10/142_752/_article/-char/ja/