Researchon Rotor Fult Dagnosisa I Of Built.in Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor has simple structure and strong reliability.Under the background of sustainable development strategy,it is widely used in new energy vehicles and industrial drives.Therefore,the fault diagnosis of permanent magnet synchronous motors is important for the safe operation and development of the entire electric vehicle.Meaning.Using the fault diagnosis method to find the fault of the permanent magnet synchronous motor in advance can not only reduce the damage caused by the fault,but also improve the safety and reliability of the equipment used.First,it analyzes the current development of the application status of permanent magnet synchronous motors,and summarizes the research background and significance of this article.The common faults and fault diagnosis status of permanent magnet synchronous motors are analyzed.The structure and working principle of permanent magnet synchronous motors are analyzed.The mathematical model of permanent magnet synchronous motors is studied.The static model and the coordinate transformation are analyzed.The mathematical model of the synchronous motor is nonlinear according to the mathematical model of the synchronous motor.Based on its multi-variable,strong coupling,nonlinear,and high-order characteristics,the coordinate conversion mathematical model of the synchronous motor is established,and the voltage of the model is made by the method of coordinate change.The analysis of equations,flux equations,torque equations and motion equations summarized the common faults of permanent magnet synchronous motors,including inter-turn short-circuit faults,loss of magnetization faults and eccentricity faults.Secondly,the turn-to-turn short-circuit fault,loss-of-excitation fault and eccentric fault of permanent magnet synchronous motor have been emphatically studied,the fault characteristic value is analyzed,and the fault radar chart is drawn in combination with the characteristics of different faults.Using the turn-to-turn fault as an example,the equivalent circuit of the fault and the concentrated parameters of the diagnosis model are analyzed respectively.Combining the characteristics of the faults,the diagnosis models for turn-to-turn short-circuit faults,loss of field faults and eccentric faults are established,and the diagnosis methods are introduced.Different fault characteristics and frequency spectrum characteristics can be used for diagnosis.Finally,the wavelet transform and particle swarm algorithm are studied,and based on the characteristics of the two algorithms,a joint fault diagnosis method of complex translation Morlet wavelet and improved particle swarm is designed.The complex translation Morlet wavelet calculation method is studied,and the improved envelope analysis algorithm based on spectral kurtosis is introduced.The advantages of the particle swarm algorithm are analyzed,and the traditional particles are also pointed out.Group algorithms are prone to fall into local optimal solutions.In order to optimize the traditional particle swarm algorithm,the two strategies of adaptive inertia weight and worst particle elimination have been added,which has improved the convergence of the algorithm and enhanced the ability of local search.The hardware module circuit mainly realized by the hardware structure of the diagnostic system is designed and implemented.According to the core function of the STM32F107 controller in the system,the minimum system circuit,drive and protection circuit,voltage and current sampling circuit of the main control module are designed.