Study On Fault Detection Methods And Diagnosis Technology Of Electric Machines Rotor

The quality of motor directly influence the competition position of motor manufacturing enterprise in market, but armature is the main component of motor, and its faults are the main faults in the process of motor running. If the motor is often damaged and destructed, the system will not work in order and get in trouble. It will also affect the rapid economic development, causing serious economic losses and adverse social impact. Rotor is the moving parts of the motor, motor often suffered axial electromagnetic force, centrifugal force and hot bending flexibility in the running process, so the rotor fault is the major fault. The detection method and fault diagnosis technology of rotor is researched by several aspects in this article; the research results can improve the quality of the motor and extend the life of the motor. The motor can be analyzed operating state in the pre-fault early warning.Rotors are subjected many factors in manufacturing process, including the coil tap to the conversion to film a particularly serious problem, which is uually caused quality problems in the production process and it is difficult to find. This testing system could experimentize and determinate to the basic electrical performance of motor armature, for instance, welding resistance, bar to bar resistance, leap resistance, industrial frequency withstand voltage, inter-turn withstand voltage, dc voltage withstand and so on. The paper designs the rotor DC resistance measuring circuit and diagnostic intelligence test rotor system. Rotor will have a full electrical performance test before the motor factory and prevent defective products from entering the market; it will improve the quality of the motor factory and extend the motor life.The rotor winding inter turn short circuit fault is one of the common faults, which is of destruction to the machines. The paper analyze the rotor winding inter turn short circuit fault mechanism and design high speed data processing system based on DSP. The system can collect the air gap EMF signal. Wavelet transform can remove the main magnetic flux interference signals from the air gap EMF signal, the normal and fault signals have 4 layers wavelet packet transform to extract the reconstructed energy feature information. After the wavelet packet transform, we get 16 energy feature information as the neural network the input vector for the establishment of artificial intelligence to provide data to support fault detection. Wavelet packet decomposition of the energy information extracted value as neural network input vector, fault type as the network output vector, and then establish a motor fault diagnosis system. In the diagnostic process, different data were used to train and test the network to achieve the rotor winding inter turn short circuit fault diagnosis.Rotor fault analysis, that is the motor rotor bar fault, is one of the common faults. This paper analyzes broken bar of the motor fault diagnosis mechanism, which is based on wavelet packet analysis. Use the wavelet packet to simulate of the signal rotor broken bars and determine the fault feature information.Use the nodes of FFT transform coefficients to reconstruct the spectrum analysis, then we can get the characteristic frequency of fault signal. Use wavelet analysis to determine fault specific time with broken bar of induction motor. The simulated experimental results show that the diagnosis method, a quicker diagnosis and a higher accuracy, is feasible.