TL;DR
A multi-batch differentiation transformation fault detection method based on Kernel Canonical Correlation Analysis (KCCA), referred to as MDT-KCCA, which maintains high detection accuracy and stability even under stochastic operating conditions, with overall performance outperforming several existing mainstream fault detection methods.
The growing complexity and prevalence of non-linear systems and processes, especially in industrial settings, have driven a significant increase in academic interest in developing advanced and more accurate techniques for Dynamic Systems Identification. Among these techniques, local modeling stands out due to its abili...
The results show that the method reduces the interference of operating-condition-induced normal-pattern drift with anomaly determination and improves the accuracy of fault warning within the range of the operating conditions covered in this study.
To address the problem of balancing sensitivity and robustness in incipient fault detection (IFD) for large‐scale processes, a distributed monitoring framework based on causal‐oriented kernel regularized canonical variate analysis (CO‐KRCVA) is proposed. The framework divides operational units into sub‐blocks accordi...
Reliable fault detection in nonlinear process systems requires both accurate classification and interpretable analysis of faults with weak or near-normal signatures. This study develops an explainable, data-driven, and temporally informed multiclass framework for the Tennessee Eastman Process (TEP), retaining all 21 op...
Normal temporal dependencies in multichannel industrial measurements vary across operating conditions and may contain recurring lag structures caused by delayed process dynamics. A state-invariant current association and a mainly local temporal reference may therefore confound normal regime variation with anomaly-relat...
A comprehensive analysis of six CUSUM approaches applied across four datasets and in both application modes, highlighting the strengths and limitations of each method and offering practical guidance for deployment in quality and reliability monitoring systems.
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