Evaluation of PCA methods with improved fault isolation capabilities on a paper machine simulator

The work presented in this paper addresses the issues of fault detection and isolation properties of the partial PCA method and the isolation-enhanced PCA method. In order to increase the sensitivity of the residuals with respect to various faults, the structured residuals generated from both partial PCA and isolation-enhanced PCA are optimized. For the residual evaluation, the bootstrap technique is combined with the CUSUM method to achieve fast and robust detection. Three sensor faults and three actuator faults were studied using simulations employing a rigorous, first principles based, paper machine simulator. All the faults were correctly detected and isolated with both studied methods, and the results are compared with the classical T2 and SPE contribution plot methods.