Recently, neural networks have emerged as potential tools in the area of fault detection and diagnosis. This paper deals with multi neural network based fault detection and diagnosis approach. The architecture adopted is a Radial Basis function neural network (RBF). The approach is applied for detection and diagnosis of suitable parameters failures on a DC-motor based on the patterns of parameters changes. The simulation results illustrated that after training the neural networks, the system is able to detect the different motor failures.