Dutta, S. orcid.org/0000-0002-9906-6477, Ambur, R., Olaby, O. et al. (3 more authors) (2022) Continuous Time Parameter Estimation Method for a Railway Track Switch Actuator. In: Proceedings of 2022 UKACC 13th International Conference on Control (CONTROL). 2022 UKACC 13th International Conference on Control (CONTROL), 20-22 Apr 2022, Plymouth, United Kingdom. IEEE , pp. 56-59. ISBN 9781665452007
Abstract
The scheduled maintenance procedure required for the safe running of a switch system is costly and often involves large time. In the changing rail network, the scheduled maintenance process is needed to be replaced with advanced condition monitoring approaches which can predict and detect degradation in the system performance and notify the operator. The present research addresses the challenge to detect any degradation or change of performance of the switch actuation system using continuous time parameter estimation method. A switch system with an electro-mechanical actuator has been considered and the developed technique is tested with changing switch parameters. A new switch actuator is now built and validated and installed in a working test switch system. The method will be tested for different unhealthy/fault scenarios with the working actuator connected to a working switch system.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Condition monitoring; Continuous time parameter estimation; Refined instrumental variable method; Railway track switch |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Jan 2024 12:11 |
Last Modified: | 10 Jan 2024 09:19 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/control55989.2022.9781437 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:207294 |