• CN:11-2187/TH
  • ISSN:0577-6686

›› 2007, Vol. 43 ›› Issue (2): 186-190.

• 论文 • 上一篇    下一篇

基于力觉遥示教焊缝辨识信号数值滤波技术

刘立君;高洪明;张广军;吴林   

  1. 哈尔滨工业大学现代焊接生产技术国家重点实验室;哈尔滨理工大学材料科学与工程学院
  • 发布日期:2007-02-15

DIGITAL FILTER OF IDENTIFYING SIGNAL OF WELDING SEAM BASED ON FORCE SENSING IN REMOTE TEACHING

LIU Lijun;GAO Hongming;ZHANG Guangjun;WU Lin   

  1. State Key Laboratory of Advanced Welding Production Technology, Harbin Institute of Technology School of Materials Science & Engineering, Harbin University of Science and Technology
  • Published:2007-02-15

摘要: 在基于力觉的遥示教过程中,为克服由于机器人的振动、焊缝表面粗糙不平和焊机电磁场干扰等因素造成焊缝的辨识力信号不稳,基于受力信号变化焊缝辨识模型分析,提出用卡尔曼滤波递推方法对焊缝辨识受力信号进行的滤波处理,建立焊缝受力信号滤波数学模型。通过模型的状态方程、观测方程、状态预报滤波、滤波增益矩阵和预报状态的协方差矩阵,完成对下一时刻受力信号准确预报。试验表明,卡尔曼滤波使焊缝受力信号状态估计的误差变小,增加焊缝辨识受力信号检测精度,进而可以提高遥控焊接遥示教焊缝辨识精度。

关键词: 焊缝辨识, 卡尔曼滤波, 力觉, 遥控焊接, 遥示教

Abstract: For reasons of the vibration of robot, the rough weld seam and electromagnetic disturbance of welding machine, the identifying force signals of welding seam(IFSWS) become unstable. By analyzing the model of IFSWS, the Kalman is used to filter the IFSWS in remote teaching. The next IFSWS is accurately predicted according to the equation of the state, the equation of the observation, the filtering of the state predicting, gain matrix of the filtering and the covariance matrix of the predicting state in Kalman filter. The experimental results show, by Kalman filtering, that the predicting error of the IFSWS is the smallest, the detecting precision of the IFSWS is increased, and the precision of welding seam identifying is improved in remote teaching.

Key words: Force sensing, Kalman filtering, Remote teaching, Remote welding, Welding seam identifying

中图分类号: