Paper Abstract and Keywords |
Presentation |
2018-12-14 14:25
Prosal of Practical Method of track condition monitoring compact device using machine learning Shohei Wakai, Tetsuya Takata (Kyosan Electric Manufacturing), Takeshi Mizuma (Tokyo Univ.), Hitoshi Tsunashima, Akira Matsumoto, Yuichi Hayashida, Ryota Hirose (Nihon Univ.) DC2018-62 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In local railway, there are few railway operators who chan conduct sufficient inspection of track condition due to cost etc.
In response to this problem, track condition monitoring compact device by simple method was developed to local railway.
There is a possibility to utilize measurement data by using machine learning.
In this research, we propose practical method of track condition monitoring compact device using machine learning. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Railway / Condition monitoring / Machine learning / Big data analysis / Track / Maintenance / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 364, DC2018-62, pp. 25-28, Dec. 2018. |
Paper # |
DC2018-62 |
Date of Issue |
2018-12-07 (DC) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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DC2018-62 |
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