Research article Open access
Efficient Fault Detection in Nonlinear Industrial Processes: A Reduced Kernel PCA-Based Spectral Clustering Approach
Kernel Principal Component Analysis (KPCA) is a powerful tool for nonlinear process monitoring, yet its quadratic computational complexity (O( N2 )) and high memory demands limit its applicability to large-scale industrial systems. This paper proposes a novel Reduced Kernel Principal Component Analysis based on Spectra …