This paper presents a diagnosis method for AC motors using a linear residual generator and neural networks. The residual generator is obtained from an identified model of the motor. The residuals are classified with a SOM neural network that allows an easy representation of the state of the motor and the evolution of the faults. Finally, this system is validated with an experimental work on a real AC motor and a real-time implementation.