Incipient Inter-turn Fault Detection For PMSM Based On Wavelet Analysis

With the rapid development of the economy,energy shortage and environmental pollution are becoming increasingly prominent.Therefore,building a clean,low-carbon,safe and efficient energy system has aroused people's wide concern.As a low-pollution,high efficiency,economic and environmental protection power equipment,the motor has been widely used in industrial production and daily life.The Permanent Magnet Synchronous Machine(PMSM)has many advantages,such as high power density,high efficiency,high torque density and so on,which attracts more and more attention.However,when the PMSM works,especially applied in the new energy vehicle,various faults may occur due to the narrow working environment,high temperature,high humidity,poor cooling conditions,as well as the mechanical and electrical factors.The inter-turn fault is one of the most common fault,which is destructive and easy to cause other faults.If the inter-turn fault is not detected in time and corresponding measures are not taken at the incipient stage,it will eventually lead to serious consequences.For the safety and the reliability of PMSM,it is very important to implement the fault detection technique of PMSM.However,at the incipient stage the fault characteristic is very small and apt to be hidden in the harmonic components and the noise,so it is difficult to detect the fault.In this thesis,the inter-turn fault detection technique of PMSM is investigated,and the change of the relevant signals of the PMSM under the fault condition is analyzed.The inter-turn fault detection methods based on the zero sequence voltage component(ZSVC)are proposed,and the fault characteristic is extracted by discrete wavelet transform(DWT)and empirical wavelet transform(EWT)after removing the interference of the harmonic components and the noise.An inter-turn fault degree detection method is proposed which is based on EWT energy distribution and Support Vector Machine(SVM).The effectiveness of the methods are verified by the simulations and experiments.The main research contents of this thesis are as follows:1.The basic working principle of PMSM is introduced.The simulation platform of PMSM is established based on MATLAB/Simulink,which lays a foundation for simulationresearch on inter-turn fault diagnosis of PMSM.2.The mathematical model of PMSM under the inter-turn fault condition is introduced.The signals of the PMSM under the fault condition and the influence of the fault on ZSVC are analyzed.After analysis and comparison,ZSVC is more sensitive to the incipient inter-turn fault,so the fundamental component of ZSVC is adopted as the fault characteristic.3.An incipient inter-turn fault detection method for PMSM based on Discrete Wavelet Transform(DWT)is proposed.The method removes the harmonic components and the noise by DWT,and then extracts the fault characteristic.The results of the simulation and experiment show the effectiveness of the method.4.An incipient inter-turn fault detection method for PMSM based on EWT is proposed.For the simplicity of the method and the low computational burden,the EWT is improved.The spectrum of ZSVC is segmented according the fault characteristic frequency,and the corresponding wavelet filter bank is built.Then the harmonic components and the noise are removed by the filter bank,and the fault characteristic can be extracted.Both the simulation and the experimental results verify the effectiveness of the method.5.An inter-turn fault degree detection method based on EWT energy distribution and SVM is proposed.The inter-turn fault degree of PMSM is predicted by the energy distribution of each Intrinsic Mode Function(IMF)for ZSVC.The effectiveness of this method is verified by the experiment result.