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ÇѱÛÁ¦¸ñ(Korean Title) |
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¿µ¹®Á¦¸ñ(English Title) |
Stress Detection of Railway Point Machine Using Sound Analysis |
ÀúÀÚ(Author) |
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Yongju Choi
Jonguk Lee
Daihee Park
Jonghyun Lee
Yongwha Chung
Hee-Young Kim
Sukhan Yoon
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¿ø¹®¼ö·Ïó(Citation) |
VOL 05 NO. 09 PP. 0433 ~ 0440 (2016. 09) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
Railway point machines act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Since point failure can significantly affect railway operations with potentially disastrous consequences, early stress detection of point machine is critical for monitoring and managing the condition of rail infrastructure. In this paper, we propose a stress detection method for point machine in railway condition monitoring systems using sound data. The system enables extracting sound feature vector subset from audio data with reduced feature dimensions using feature subset selection, and employs support vector machines (SVMs) for early detection of stress anomalies. Experimental results show that the system enables cost-effective detection of stress using a low-cost microphone, with accuracy exceeding 98£¥.
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Å°¿öµå(Keyword) |
öµµ ¼±·ÎÀüȯ±â
½ºÆ®·¹½º ŽÁö
¼Ò¸® ºÐ¼®
SVM
Railway Point Machine
Stress Detection
Sound Analysis
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