Induction Motor's Electric Fault Identification And Diagnosis

For the convenience that is widely use with the electric energy, the electric motor equipment has already widely used in each industrial field. The electric motor plays an important role in the whole mechanical systems. It will influence the normal running of the whole system if the electric motor has fault, even threaten the security of the person. So it is very important to carry on trouble diagnosis for electric motor.On the basis of analysing the common electric trouble mechanism of induction motor, the paper proposes making use of stator current law to diagnose the induction motor's electric fault. Furthermore it gives the priority research to the airgap eccentricity and turn-to-turn short circuit fault with high incidence rate.Because the coupled electric circuit and magnetic circuit exist in the induction motor, there are many factors of the motor fault. Accordingly, the range of the induction motor trouble diagnosis technology is more widely than the general mechanical equipment technology. The complexity of induction motor also represents the implicity of the fault characteristics, plurality between the cause and sign of the fault. That is to say, a trouble may present many kinds of trouble signs while different troubles may present the same trouble sign. Aimed to the characteristics of the trouble of the induction motor, this paper puts forward the method that the wavelet combines with neural network, and picks up the character vector by using the wavelet packet and energy method as the ANN input neural vector. The ANN is trained by teacher using LM algorithm. Not having to establish the model structure of the system, this method makes use of energy change of the frequency composition to discern different modes.Because it is inaccurate to measure the stator current of induction motor by the current transformer, the stator current data gets through measuring the voltage of wire from Power to induction motor. The current of the wire and the stator current are the same electric current, so the stator current is gotten by measuring the wire current. The experiment testifies that it is feasibility that applying the wavelet packet and neural network to the electric fault diagnosis of the induction motor.At last, the paper uses the strong function of Graphical User Interfaces of MATLAB to combine the signal processing and neural network technology. It is convenience to the users analyzing the signal.