摘要
磨削过程中尺寸补调值的设定对批量工件的加工精度具有至关重要的作用。通过对外圆磨削过程的深入分析,研究磨削加工过程中的补调值预测算法,提出基于模糊物元分析的PSO-LSSVM补调值精确预测模型。通过模糊物元分析迅速准确地获得最佳工艺参数,并将对应的参数作为输入,以此训练出PSO-LSSVM预测模型。通过PSO优化LSSVM模型参数,提高了模型的预测精度。当预测值大于理论边界时,对尺寸误差进行补调,及时调整工艺参数以提高加工精度。通过磨削加工在线测量实验验证,模型平均绝对误差为0.05257μm,均方根误差为0.06533μm;采用所得模型对试样外磨削工件加工时的补调值进行预测可得平均绝对误差0.09625μm,均方根误差0.13412μm,达到补调值预测的精度要求。通过批量工件的加工测试,得出批量工件加工精度较未使用补调值预测补偿控制前显著提高。将提出的补调值预测方法应用于磨加工主动测量控制仪中,控制仪实现了自动补调并与机床形成反馈控制,提高了磨削加工工件的精度与磨加工系统智能化程度。
The setting of the size compensation value during the grinding process plays a vital role in the machining accuracy of batch workpieces.Through the in-depth analysis of the cylindrical grinding process,the compensation value prediction algorithm in the grinding process was studied,and the PSO-LSSVM compensation value accurate prediction model based on fuzzy matter element analysis was proposed.Through fuzzy matter-element analysis,the optimal process parameters were quickly and accurately obtained,and the corresponding parameters were input to train the PSO-LSSVM prediction model.The parameters of the LSSVM model were optimized by PSO to improve the prediction accuracy of the model.When the predicted value was greater than the theoretical boundary,the size error was compensated,and the processing accuracy was improved by adjusting the process parameters in time.The average absolute error of the model is 0.05257μm and the root mean square error is 0.06533μm verified by online measurement and grinding processing experiments.Using the obtained model to predict the compensation value during the grinding of the workpiece outside the specimen,the average absolute error of the model is 0.09625μm and the root mean square error is 0.13412μm,which meets the accuracy requirements of the compensation value prediction.Through the processing test of batch workpieces,it is concluded that the processing accuracy of batch workpieces is significantly improved compared with that before the compensation value prediction compensation control is not use.The proposed method of compensation value prediction was applied to the grinding processing active measurement control instrument.The control instrument can realize automatic compensation adjustment and form feedback control with the machine tool,which improves the accuracy of grinding workpieces and the intelligence of the grinding processing system.
作者
张志永
郑鹏
ZHANG Zhiyong;ZHENG Peng(College of Mechanical Engineering,Zhengzhou University of Science and Technology,Zhengzhou Henan 450064,China;School of Mechanical and Power Engineering,Zhengzhou University,Zhengzhou Henan 450001,China)
出处
《机床与液压》
北大核心
2022年第19期20-26,共7页
Machine Tool & Hydraulics
基金
国家自然科学基金面上项目(51775515)
河南省高等学校重点科研项目(22B460027)。
作者简介
张志永(1990—),男,硕士,讲师,研究方向为精密工程、数字化仪器与技术。E-mail:zky_zzy1990@163.com;通信作者:郑鹏(1976—),男,博士,教授,研究方向为传感检测技术、GPS及其应用技术。E-mail:zpzzu@163.com。
