摘要
针对自动校直机在工件弯曲量测量过程中的测量误差问题,提出一种基于支持向量机(SVM)的校直机工件弯曲量测量误差补偿方法。在试验过程中,利用偏摆检测仪将校直机测得的工件弯曲量进行标定,进而获取建模数据。模型训练过程运用交叉验证法对SVM的惩罚参数、核函数参数进行优化选择,构建SVM优化模型。利用SVM优化模型对不同工件同一测量位置的弯曲量测量误差进行预测补偿,通过对比预测补偿效果,SVM模型的补偿效果明显,具有工程应用价值。
A measurement error compensation method of straightening machine workpiece curvature based on support vector machine( SVM) was presented to solve the workpiece curvature measurement error of automatic straightening machine. In the process of test,the deflection detector was used to calibrate the workpiece curvature measured by straightening machine and the modeling data were obtained. During the modeling process,the optimized parameters of SVM were chosen by cross-validation method. With these optimized parameters,the established model could be used to predict the workpiece curvature measurement error accurately. The SVM model was respectively used to predict the curvature measurement error of different workpiece and the same position. With the prediction results comparison,the compensation effect of SVM model is obvious. Therefore,it is valuable for engineering application.
作者
石钧仁
郝建军
刘子涛
SHI Junren;HAO Jianjun;LIU Zitao(Chongqing University of Technology,Chongqing 400054,China;Chongqing College of Electronic Engineering,Chongqing 401331,China;Chongqing Zhiheng Precise Machine Technology Co.,Ltd.,Chongqing 401123,China)
出处
《机床与液压》
北大核心
2018年第14期111-114,共4页
Machine Tool & Hydraulics
基金
重庆市教委资助项目(KJZH17127)
重庆市科委资助项目(cstc2014pt-gc60003)
关键词
支持向量机
校直机
误差补偿
弯曲量
Support vector machine
Straightening machine
Error compensation
Curvature