Intelligent Diagnosis and Prognosis of Tool Wear Using Dominant Feature Identification

• Main Authors: Zhou, J.-H., Pang, C.K., Lewis, F.L., Zhong, Z.-W.
• Other Authors: ELECTRICAL & COMPUTER ENGINEERING
• Format: Article
• Published: 2014
• Subjects: Least square error (LSE); Principal component analysis (PCA); Principal feature analysis (PFA); Recursive least squares (RLS); Singular value decomposition (SVD)
• Online Access: http://scholarbank.nus.edu.sg/handle/10635/56357
• Institution: National University of Singapore

10.1109/TII.2009.2023318