Genetic programming with Probabilistic Model for fault detection

In this paper a new method is presented to solve a series of fault detection problems using Probabilistic Model (PM) in Genetic Programming (GP). Fault detection can be seen as a problem of multi-class classification. GP methods used to solve problems have a great advantage in their power to represent solutions to complex problems, and this advantage remains true in the domain of fault detection. Moreover, diagnosis accuracy can be improved by using PM. In the end of this paper, we use this method to solve the fault detection of electro-mechanical device. The results show that the method uses GP with PM to solve fault detection of electro-mechanical device outperforms the artificial neural network (ANN).