Gap-MK-DCCA-Based Intelligent Fault Diagnosis for Nonlinear Dynamic Systems
Junzhou Wu,
Mei Zhang,
Lingxiao Chen
Abstract:In intelligent process monitoring and fault detection of the modern process industry, conventional methods mostly consider singular characteristics of systems. To tackle the problem of suboptimal incipient fault detection in nonlinear dynamic systems with non-Gaussian distributed data, this paper proposes a methodology named Gap-Mixed Kernel-Dynamic Canonical Correlation Analysis. Initially, the Gap metric is employed for data preprocessing, followed by fault detection utilizing the Mixed Kernel-Dynamic Canoni… Show more
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