Fault Detection of Chemical Processes Using KPCA-Based GLRT Technique
Additional Document Info
2017 IEEE. In this paper, we address the problem of nonlinear fault detection of chemical processes. The objective is to extend our previous work  to provide a better performance in terms of fault detection accuracies by developing a pre-image kernel PCA (KPCA)-based Generalized Likelihood Ratio Test (GLRT) technique. The benefit of the pre-image kPCA technique lies in its ability to compute the residual in the original space using the KPCA from the feature space. In addition, GLRT provides more accurate results in terms of fault detection. The performance of the developed pre-image KPCA-based GLRT fault detection technique is evaluated using simulated continuously stirred tank reactor (CSTR) model.
name of conference
2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)