| Abstract:With the high-speed, precision CNC machine tools being widely used, processing object has transformed from simple curve to complex surface. So CNC machine tools must meet the requirements of fast, stable and accurate processing. As a new drive technology that directly combined motor and execution parts, direct drive is widely used in modern precision CNC machine tools. However, when direct drive is used, CNC system can’t meet the requirements of processing high-precision complex surface products when it uses invariable PID control parameters when load changes on the load-side, the control parameters of system servo need real-time optimization. The currently CNC systems, including the Fanuc CNC system, Siemens CNC system and domestic "Huazhong" CNC system, do not have the function of online and real-time optimization of control parameters. Therefore, it is of great significance to study the optimization methods of precise CNC machine tools control parameters of system servo.Based on the analysis of control principle and structure of CNC machine tools feed drive system, the open-loop transfer functions of current loop, speed loop and position-loop of the full closed-loop servo control are analyzed. The optimization methods of the control parameters of the three loops from the time domain response and frequency-domain response of system are introduced. The optimization methods and its shortcomings of the control parameters of system servo are discussed, from the time domain response and frequency-domain response.The paper presents an optimization method of control parameter of servo drive system based on Bayesian classifier. It extracts the control parameters of servo system of NC machine tool to be training sample of Bayesian classifier, obtains the prior probability of Bayesian classifier, and gets the optimized control parameters database. In the subsequent parts of processing, it uses Bayesian classifier to classify the optimized control parameters of current loop, speed loop, position-loop of the servo system according to the data characteristics of the load-side. Because the subclass characteristic and the father class characteristic maintained consistently in the probability in greatest degree, subclass optimized control parameters of servo system inherited the good servo strategy of father’s class and the servo drive system has good system performance and dynamic response. Simultaneously, feed speed of the servo drive system of every axis is dynamic coordinated to guarantee the accuracy and surface smoothness of processing components to meet the requests of precise processing.Finally, the proposed methods are verified by using double-spindle direct drive NC bevel gear grinding machine as experimental training object. By collecting the optimal control parameters of the drive system in different batches of gears grinding experiments, the control parameters are optimized based on proposed methods. The results showed that the requirements of the accuracy and the surface smoothness can be met well. |
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