There are different methods for detecting digital faults in electronic and computer systems. But for analog faults, there are some problems. This kind of faults consist of many different and parametric faults, which can not be detected by digital fault detection methods. One of the proposed methods for analog fault detection, is neural networks. Fault detection is actually a pattern recognition task. Faulty and fault free data are different patterns which must be recognized. In this paper we use a probabilistic neural network for fault detection in MEMS. A fuzzy system is used to improve performance of the network. Finally different network results are compared.