A Common and Individual Feature Extraction-Based Multimode Process Monitoring Method With Application to the Finishing Mill Process

摘要: This paper proposes a common and individual (CnI) feature extraction-based process monitoring (PM) method for tracking the operating performance product quality of processes with multiple modes. Different from traditional methods that separately develop PM models concerning only each mode data, new seeks to build model simultaneously all including acquire subspace captures behind different modes, reflects unique mode. The newly proposed framework is achieved using conventional principal component analysis (PCA) partial least squares (PLS) based methods. resulting CnI-PCA-based CnI-PLS-based are applied typical multimode finishing mill (FMP) where configuration steel products setting existing. Finally, practical application result shows can be preferable detect identify faults in FMP.