Replacement Condition Detection of Railway Point Machines Using an Electric Current Sensor
- Authors
- Sa, Jaewon; Choi, Younchang; Chung, Yongwha; Kim, Hee-Young; Park, Daihee; Yoon, Sukhan
- Issue Date
- 2월-2017
- Publisher
- MDPI
- Keywords
- maintenance engineering; railway pointmachine; electric current shape analysis; replacement condition monitoring
- Citation
- SENSORS, v.17, no.2
- Indexed
- SCIE
SCOPUS
- Journal Title
- SENSORS
- Volume
- 17
- Number
- 2
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/84841
- DOI
- 10.3390/s17020263
- ISSN
- 1424-8220
- Abstract
- Detecting replacement conditions of railway point machines is important to simultaneously satisfy the budget-limit and train-safety requirements. In this study, we consider classification of the subtle differences in the aging effect-using electric current shape analysis-for the purpose of replacement condition detection of railway point machines. After analyzing the shapes of after-replacement data and then labeling the shapes of each before-replacement data, we can derive the criteria that can handle the subtle differences between "does-not-need-to-be-replaced" and "needs-to-be-replaced" shapes. On the basis of the experimental results with in-field replacement data, we confirmed that the proposed method could detect the replacement conditions with acceptable accuracy, as well as provide visual interpretability of the criteria used for the time-series classification.
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- Appears in
Collections - Graduate School > Department of Computer and Information Science > 1. Journal Articles
- College of Public Policy > Division of Big Data Science > 1. Journal Articles
- College of Science and Technology > Department of Computer Convergence Software > 1. Journal Articles
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