Fault detection and diagnosis using PDF for stochastic distribution systems

With the rapid advances in sensor technology, image manipulation and data processing, the feedback measurement information is the stochastic distribution of the system output rather than its value. In this paper, based on the output probability density functions (PDFs) and neural networks, a new fault detection and diagnosis strategy is studied by designing an adaptive observer. The designed observer can not only detect the fault, but also realize the fault diagnosis. Computer simulations are given to demonstrate the efficiency of the proposed approach.