Integrated intelligent fault diagnosis approach to TE Process

An integrated algorithm based on lifting wavelets and probabilistic neural network (LWPNN) for classifying the industrial system faults was presented in this paper. Firstly the data were preprocessed to remove noise by lifting scheme wavelets, which were faster than first generation wavelets, and then PNN was used to diagnose faults. To validate the performance and effectiveness of the proposed scheme, LWPNN was applied to diagnose the faults in TE Process. Simulation studies showed that the proposed algorithm not only provided an accepted degree of accuracy in fault classification under different fault conditions, but also was reliable, fast and computationally efficient tool.