Unsteady Fault Diagnosis Based on Wavelet-Networks

In order to improve the performance of fault diagnosis systems based on BP networks, a new method based on wavelet networks is presented which incorporated an algorithm of varying scal for training networks so as to accelerate the training process. Simulation research on its application to unsteady fault diagnosis of a CSTR process has proved that it performs more effectively than that based on BP networks.