Adaptive sparse principal component analysis for enhanced process monitoring and fault isolation

• Published in: Chemometrics and intelligent laboratory systems Vol. 146; pp. 426 - 436
• Main Authors: Liu, Kangling, Fei, Zhengshun, Yue, Boxuan, Liang, Jun, Lin, Hai
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.08.2015
• Subjects: Adaptive; Fault isolation; Principal component analysis; Process monitoring; Sparse; Process monitoring; Fault isolation; Sparse; Adaptive; Principal component analysis

Principal component analysis (PCA) has been widely applied for process monitoring and fault isolation. However, PCA lacks physical interpretation of principal components (PCs) since each PC is a linear combination of all variables, which makes the fault detection difficult. Moreover, since the PCA m...