| Issue |
MATEC Web Conf.
Volume 336, 2021
2020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|
|
|---|---|---|
| Article Number | 02017 | |
| Number of page(s) | 6 | |
| Section | Industrial Design and Engineering Technology | |
| DOI | https://doi.org/10.1051/matecconf/202133602017 | |
| Published online | 15 February 2021 | |
Health assessment for railway switch systems
State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
* Corresponding author: thxu@bjtu.edu.cn
Because of the heavy workload and high failure rate of railway switch system (RSS), the traditional scheduled maintenance can not meet the actual operation needs of the railway. Therefore condition-based maintenance (CBM) and prognostic and health management(PHM), which have been mature in other fields should be introduced into RSS. Health assessment is of a great concern among all the technologies. This paper presents a novel method which can be utilized on the health status evaluation of RSS. First of all, RSS is briefly introduced and the connotation of PHM for RSS is analyzed. Secondly, health indicators (HIs) are extracted by different time domain features, and the best indicators are selected to establish the degradation model. By using clustering algorithm, the change point of state is detected which can be used as an instruction of advance maintenance. Finally, a ZYJ7 RSS is selected to test and verify the proposed method. Result indicates that the algorithm can be effectively applied to health assessment of RSS.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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