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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제22권 제6호
- 발행연도
- 2020.1
- 수록면
- 2,225 - 2,235 (11page)
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초록· 키워드
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With the tremendous deployment of different kinds of sensors and actuators, the Internet of Things (IoT) emerges as an advanced method to connect devices and collect the status data. Aided by the use of a large amount of operation data, the data-driven fault diagnosis is considered as a modern technique in Industry 4.0 and has become a research hotspot in recent years. In the area of urban rail transit, the point machine is a critical component that is used to safely switch the train direction. In this article, we propose a novel fault diagnosis scheme for railway point machines (RPMs) using electrical signals. RPMs are devices that move a switch blade from its current position to the opposite position to offer different routes to trains. RPMs failures often lead to service delays or dangerous situations; therefore, detecting early signs of their deteriorating condition is essential. We present a powerful and interpretable method that relies on the construction of the smoothed periodogram, which are estimator of spectral density. Experimental results demonstrate the efficacy of the proposed method.
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참고문헌 (24)
참고문헌 신청
Alagon, J. / 1989 / Spectral discrimination for two groups of time series / Journal of Time Series Analysis 10:203~214
Asada, T. / 2013 / An algorithm for improved performance of railway condition monitoring equipment : alternating-current point machine case study / Transportation Research Part C 30:81~92
Barbella, D. / 2009 / Understanding support vector machine classifications via a recommender system-like approach / International Conference on Data Mining (DMIN)
Brusco, M. J. / 2011 / Extract and approximate algorithms for variable selection in linear discriminant analysis / Computational Statistical and Data Analysis 55(1):123~131
Brockwell, P. J. / 1991 / Time Series: Theory and Methods / Springer
Asada, T. / 2013 / An algorithm for improved performance of railway condition monitoring equipment : alternating-current point machine case study / Transportation Research Part C 30:81~92
Barbella, D. / 2009 / Understanding support vector machine classifications via a recommender system-like approach / International Conference on Data Mining (DMIN)
Brusco, M. J. / 2011 / Extract and approximate algorithms for variable selection in linear discriminant analysis / Computational Statistical and Data Analysis 55(1):123~131
Brockwell, P. J. / 1991 / Time Series: Theory and Methods / Springer
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