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Journal Article
고속 열차 고장 발생 예측을 위한 연관 규칙 마이닝의 적용
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- Authors
- 김철홍, 김영덕, 염병수, 박정희
- Issue Date
- 2016-03
- Citation
- 대한설비관리학회지, v.21, no.1, pp.59-65
- ISSN
- 1598-2475
- Publisher
- 대한설비관리학회
- Language
- Korean
- Type
- Journal Article
- Abstract
- It may occur in the high-speed train many different types of failures such as support fixture crack, engine fault, composite train’s division/connection abnormality, axle’s rust, and shaking of its body. Such failures can threaten safe and reliable train operation. Sometimes some failure can cause failure of the other, and therefore discovering the association rules between various failures can help preventing the occurrence of related failures. In this paper, we propose to apply association rule mining for failure record data from a high-speed train.
- KSP Keywords
- Association rule mining, Engine fault, Support fixture, Train operation, high speed train