Fault detection and diagnosis of non-linear non-Gaussian dynamic processes using kernel dynamic independent component analysis
Kernel dynamic ICA (KDICA) is proposed for non-linear non-Gaussian dynamic processes. Its main idea is applying ICA in kernel space of augmented measurement matrix. Non-linear contribution plot of KDICA is developed for fault diagnosis. KDICA is compared with conventional methods on Tennessee Eastman (TE) process.
non-linear non-gaussian dynamic processes independent component analysis non-linear contribution plot te process