Research On The Control Strategy Of Motor Operating Mechanism Of Vacuum Circuit Breaker

High voltage circuit breaker is an important switch equipment in power system,which is of great significance to the safe operation of power system,in recent years,china's smart grid has been rapid development,put forward the urgent requirement of intelligent power system of high voltage switchgear.In order to improve the accuracy of the drive motor commutation,the commutation method based on winding current is proposed,according to the equivalent mathematical model of the permanent magnet brushless DC motor,the rotor position is calculated by combining the winding current value and trapezoidal quadrature method,to realize the commutation operation based on winding current.In order to improve the operation level of intelligent motor operating mechanism,with the circuit breaker drive motor as the research object,combining fuzzy theory and neural network control theory,a fuzzy neural network PID algorithm is established to realize the speed control of the drive motor.In this thesis,from the mathematical model of the drive motor,control system development,the respect such as circuit breaker operation experiment research,the main research work is as follows:(1)Study on vacuum circuit breaker motor operating mechanism on the motion characteristics,combined with the drive motor electromagnetic and mechanical coupling field,establish the mathematical model of the brushless DC motor,calculate the motor output torque and winding voltage of the motor,combined with the kinetic equation of relationship between motor winding voltage and dynamic contact speed,realize adjusting drive motor input to control the speed of the contact voltage.(2)Analysis of the theory of fuzzy control and neural network control,combined with the traditional PID control method of motor speed,put forward a kind of applied to the circuit breaker on the drive motor of the fuzzy neural network PID control algorithm,the input error two times as the performance index,the gradient descent method for self-learning method,using fuzzy controller to improve neural network self-learning knowledge ability.Build a motor control system simulation model,using computer language to write control algorithm S function module,the traditional PID and fuzzy neural network PID speed simulation experiments are carried out,the experimental data are compared and analyzed to verify the validity of the fuzzy neural network PID algorithm.(3)In this thesis a motor winding current value for commutation is proposed,according to the equivalent mathematical model of permanent magnet brushless DC motor,combined with the winding current value and trapezoidal quadrature method to calculate the rotor position,in order to achieve the commutation operation which based on winding.The experiment of the motor operating mechanism of the circuit breaker is carried out.the method can realize the phase change operation of the drive motor,and the angle error between the motor commutation position and the hall plate of commutation position is less than 1 degrees.(4)Aiming at the nonlinear object,large inertia,instantaneous starting,high current characteristics,the control system of motor operating mechanism based on digital signal processor(DSP)is developed,control system design method and design theory is given,set up the experimental platform for the circuit breaker drive motor speed control experiment,the fuzzy neural network PID algorithm is used to make the maximum error of speed tracking not more than 0.4m/s.