Tool wear monitoring using acoustic emissions by dominant-feature identification

Tool wear monitoring using acoustic emissions by dominant-feature identification

10.1109/TIM.2010.2050974

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書目詳細資料
Main Authors:	Zhou, J.-H., Pang, C.K., Zhong, Z.-W., Lewis, F.L.
其他作者:	ELECTRICAL & COMPUTER ENGINEERING
格式:	Article
出版:	2014
主題:	Auto-Regressive Moving Average with eXogenous inputs (ARMAX) model least squares error (LSE) principal component analysis (PCA) principal feature analysis (PFA) singular value decomposition (SVD) tool condition monitoring (TCM)
在線閱讀:	http://scholarbank.nus.edu.sg/handle/10635/57682
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	National University of Singapore

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