Stator Resistance Identification Based On Biogeography Optimization Algorithm

High speed machining technology can realize the two aspects unified of processing quality and machining efficiency,which is one of modern advanced manufacturing techniques.For high speed and high precision grinding machining,one of the main factors influencing the precision of grinding machining is the operation characteristics of spindle.The operation characteristics of the electric spindle mainly include speed and torque,which is decided on the control system?In the direct torque control system of the electric spindle based on the traditional u-i magnetic chain observation model,stator resistance is the main factor affecting control performance.The dynamic changing of the stator resistance can affect the performance of the direct torque control system.Therefore,this thesis carry out the following research focuses on the electrical spindle stator resistance identification technology:(1)Based on the research of principle of direct torque control system,the simulink model of direct torque control was founded.Through the study of different magnetic chain models,the stator resistance is the main factor affecting the direct torque control system under the u-i magnetic chain observation model.(2)The main factors influencing the stator resistance of electric spindle was analyzed.Based on the 150MD18Z9 motorized spindle,the influence of stator current and shell temperature on stator resistance was studied?(3)For the problem of easy getting local optimal solution and low recognition accuracy of BP neural network,the model of MLBBO-BP stator resistance identification algorithm was constructed.To verify the effectiveness of the improved algorithm,the conventional BP neural network was used to identify the stator resistance of the experiment and get the identification results and identification accuracy.Using the MLBBO-BP stator resistance identification algorithm model,the stator resistance was also identified,get the identification results and identification accuracy and compare the advantages and disadvantages of the two methods,the results showed that the accuracy of the stator resistance identification using the MLBBO-BP algorithm,can be up to or minus 0.3%,far below the identification accuracy using the traditional BP neural network.It can be seen that the ability of stator resistance identification using MLBBO-BP algorithm is better.(4)Introduce the MLBBO-BP stator resistance identification algorithm into the direct torque control system.The direct torque control system was modeled based on the model design method,and embedded code was generated.