学报(中文)

曲线磨削砂轮廓形的原位视觉检测和误差补偿

展开
  • 上海交通大学 机械与动力工程学院, 上海 200240
胡一星(1993-),男,安徽省合肥市人,硕士生,目前主要从事精密磨削控制技术研究.

网络出版日期: 2019-07-23

基金资助

国家自然科学基金(51575350)

In-Situ Vision Detection and Compensation of Wheel Profile Error in Profile Grinding

Expand
  • School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Online published: 2019-07-23

摘要

为了精确测量砂轮轮廓,分析了一种曲线磨削砂轮廓形快速原位视觉检测的工作原理,设计了砂轮廓形原位视觉检测系统,提出了砂轮廓形精度的测量和量化评定方法.基于自主研发的曲线磨削平台,通过实验验证了砂轮廓形原位视觉检测系统的测量精度.同时,为了提高工件的加工精度,进一步提出了一种砂轮廓形误差的分段量化表征和误差补偿方法,并进行了实验研究.结果表明,所提出的方法能够实时在线补偿砂轮廓形误差,有效提高零件加工轮廓的形状和尺寸精度.

本文引用格式

胡一星,许黎明,范帆,张哲 . 曲线磨削砂轮廓形的原位视觉检测和误差补偿[J]. 上海交通大学学报, 2019 , 53(6) : 654 -659 . DOI: 10.16183/j.cnki.jsjtu.2019.06.003

Abstract

This study introduced a method for a rapid vision detection of edge profile of grinding wheel based on a self-developed profile grinding machine. The in-situ vision detection of wheel profile was designed. The accuracy measurement and quantitative assessment of wheel profile were presented. The feasibility and measurement accuracy were experimentally testified. Finally, a segmented quantitative characterization of wheel profile error and error compensation method were proposed for grinding of contour surfaces. Experiments were designed and conducted. The experimental results indicated that the method can online compensate wheel profile error and effectively improve the shape and size precision of profile of machined component.

参考文献

[1]解斌, 许黎明, 杨子琦, 等. 曲线磨削无干涉的近似法向跟踪算法[J]. 上海交通大学学报, 2014, 48(5): 589-593. XIE Bin, XU Liming, YANG Ziqi, et al. Normal tracking algorithm for avoiding interference in NC profile grinding [J]. Journal of Shanghai Jiao Tong University, 2014, 48(5): 589-593. [2]王洪雨, 姚振强, 许胜. 基于声发射技术的砂轮磨损实验研究[J]. 组合机床与自动化加工技术, 2018(8): 33-37. WANG Hongyu, YAO Zhenqiang, XU Sheng. Experimental study of grinding wheel wear process based on acoustic emission technology [J]. Modular Machine Tool & Automatic Manufacturing Technique, 2018(8): 33-37. [3]YANG Z, YU Z. Grinding wheel wear monitoring based on wavelet analysis and support vector machine[J]. International Journal of Advanced Manufacturing Technology, 2012, 62(1/2/3/4): 107-121. [4]XU L M, XU K Z, CHAI Y D. Identification of grinding wheel wear signature by a wavelet packet decomposition method[J]. Journal of Shanghai Jiao Tong University, 2010, 15(3): 323-328. [5]袁勃, 张桂香, 陈根余, 等. 基于CCD传感器的砂轮轮廓测量系统设计[J]. 传感器与微系统, 2014, 33(1): 101-104. YUAN Bo, ZHANG Guixiang, CHEN Genyu, et al. Design of grinding wheel profile measuring system based on CCD sensor [J]. Transducer and Microsystem Technologies, 2014, 33(1): 101-104. [6]LACHANCE S, BAUER R, WARKENTIN A. Application of region growing method to evaluate the surface condition of grinding wheels[J]. International Journal of Machine Tools & Manufacture, 2004, 44(7/8): 823-829. [7]SU J C, TANG Y S. Measuring wear of the grinding wheel using machine vision[J]. International Journal of Advanced Manufacturing Technology, 2006, 31(1/2): 50-60. [8]DENG C X, WANG G B, YANG X R. Image edge detection algorithm based on improved canny operator[C]//International Conference on Wavelet Analysis and Pattern Recognition. Tianjin, China: IEEE, 2013: 168-172.
文章导航

/