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Moving window PCA have gain more attentions for its adaptive ability in monitoring industrial process. A new contribution chart is proposed for fault diagnosis when an abnormal behavior is indicated by MWPCA. The contributions of individual process variables to the process behavior changes and the PCA model coefficients can be illustrated in a 3-dimensional chart, which provides more information in...
A flexible principle component analysis method for adaptive process monitoring based on moving window principle component analysis is presented to make a compromise between the sensitivity to fault detection and the robustness to process changes. A flexibility factor is introduced in the new method to put more emphasis on more recent data in the moving window. The feasibility and advantages of the...
A new fault diagnosis method is proposed, which combines negative selection algorithm and conventional classification algorithm. All the available training samples, including normal samples and known anomaly, are treated as positive samples (self). The real-valued negative selection algorithm is adopted to generate the negative samples (non-self), which distribute among the rest of the detected space...
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