Tool wear forecast using Dominant Feature Identification of acoustic emissions

• Main Authors: Pang, C.K., Zhou, J.-H., Zhong, Z.-W., Lewis, F.L.
• Other Authors: ELECTRICAL & COMPUTER ENGINEERING
• Format: Conference or Workshop Item
• Published: 2014
• Subjects: ARMAX model; Least square error (LSE); Principal component analysis (PCA); Principal feature analysis (PFA); Singular value decomposition (SVD); Tool condition monitoring (TCM)
• Online Access: http://scholarbank.nus.edu.sg/handle/10635/72037
• Institution: National University of Singapore

10.1109/CCA.2010.5611259