Paper Abstract and Keywords |
Presentation |
2019-12-20 15:40
Study on Condition-Based Maintenance of Railway Signal Equipment using the Machine Learning Hiroshi Shida (JR West), Akihiro Tamura, Takashi Ninomiya, Hiroshi Takahashi (Ehime Univ) DC2019-83 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Dependable systems are required high safety and reliability. Recently, condition-based maintenance(CBM) is expected to maintain high reliability. We think that "the data measurement, collection, the analysis" are necessary factors for realization of CBM. And we think that the problems of the data measurement and collection are solved by the progress of the Iot technology. In this paper, we focus that the method of analysis for realization of CBM. We have analyzed the maintenance data of railway signaling equipment in machine learning. And we show an example of the consideration for maintenance timing. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Railway signaling / Condition based maintenance / Mahalanobis distance / Neural network / Railway signaling equipment / Track circuit / Electric point machine / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 351, DC2019-83, pp. 25-30, Dec. 2019. |
Paper # |
DC2019-83 |
Date of Issue |
2019-12-13 (DC) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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DC2019-83 |
Conference Information |
Committee |
DC |
Conference Date |
2019-12-20 - 2019-12-20 |
Place (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
DC |
Conference Code |
2019-12-DC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Study on Condition-Based Maintenance of Railway Signal Equipment using the Machine Learning |
Sub Title (in English) |
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Keyword(1) |
Railway signaling |
Keyword(2) |
Condition based maintenance |
Keyword(3) |
Mahalanobis distance |
Keyword(4) |
Neural network |
Keyword(5) |
Railway signaling equipment |
Keyword(6) |
Track circuit |
Keyword(7) |
Electric point machine |
Keyword(8) |
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1st Author's Name |
Hiroshi Shida |
1st Author's Affiliation |
West Japan Railway Company (JR West) |
2nd Author's Name |
Akihiro Tamura |
2nd Author's Affiliation |
Ehime University (Ehime Univ) |
3rd Author's Name |
Takashi Ninomiya |
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Ehime University (Ehime Univ) |
4th Author's Name |
Hiroshi Takahashi |
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Ehime University (Ehime Univ) |
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Speaker |
Author-1 |
Date Time |
2019-12-20 15:40:00 |
Presentation Time |
25 minutes |
Registration for |
DC |
Paper # |
DC2019-83 |
Volume (vol) |
vol.119 |
Number (no) |
no.351 |
Page |
pp.25-30 |
#Pages |
6 |
Date of Issue |
2019-12-13 (DC) |
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