This paper presents a fault monitoring of DC motors. A neural network is prepared to processes the inputs parameters “motor speed and current” collected from sensors and delivers condition states of the DC motors “good, fair or bad”. FPGA Spartan 3 kit board is used to implement the proposed monitoring network and the circuits are designed for data acquisition to makes an interface between motors analog collected data and FPGAs digitals inputs ports. The designed circuits are intended to gather analogs readings from the target motor and converting them into digitals to be compatibles with FPGAs inputs ports specifications. The neural networks which are designed based on backs propagation trainings are implemented using Xilinx Spartan-3A Starter FPGAs Kits boards.