Abstract: Recently, neural networks have emerged as potential tools in the area of fault detection and diagnosis. This study explores a multi neural network based fault detection and diagnosis approach. The network architecture adopted is an RBF. The approach has been applied for detection and diagnosis of suitable parameters failures on a dc motor. The simulation results illustrated that after training of the neural networks, the system is able to detect the different failures.