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哈尔滨工业大学 电气工程及自动化学院, 哈尔滨 黑龙江 150001
[ "林苍现(1979-), 男, 朝鲜平壤人, 博士研究生, 2002年于朝鲜金策工业综合大学获得学士学位, 2007年于金策工业综合大学获得硕士学位, 主要从事机械工程、精密仪器设计、误差理论方面的研究。E-mail:15BF01029@hit.edu.cn" ]
陈刚(1971-), 男, 黑龙江哈尔滨人, 博士, 副教授, 1999年、2006年于哈尔滨工业大学分别获得硕士、博士学位, 主要从事计算机视觉、精密机械设计和几何参数测量系统的研究。E-mail:chenganghit@hit.edu.cn CHEN Gang, E-mail:chenganghit@hit.edu.cn
收稿日期:2017-12-25,
录用日期:2018-2-22,
纸质出版日期:2018-08-25
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林苍现, 林哲民, 陈刚, 等. 多关节测量臂的小生境混沌优化校准[J]. 光学 精密工程, 2018,26(8):2048-2056.
Chang-Hyon RIM, Chol-Min RIM, Gang CHEN, et al. Calibration method of PCMA by using niching chaos optimization algorithm[J]. Optics and precision engineering, 2018, 26(8): 2048-2056.
林苍现, 林哲民, 陈刚, 等. 多关节测量臂的小生境混沌优化校准[J]. 光学 精密工程, 2018,26(8):2048-2056. DOI: 10.3788/OPE.20182608.2048.
Chang-Hyon RIM, Chol-Min RIM, Gang CHEN, et al. Calibration method of PCMA by using niching chaos optimization algorithm[J]. Optics and precision engineering, 2018, 26(8): 2048-2056. DOI: 10.3788/OPE.20182608.2048.
多关节测量臂是一种便携式的坐标测量设备,它由一系列的旋转关节组成。为了提高多关节测量臂的测量精度和可重复性水平,必须对其运动学参数进行校准。首先,利用小生境的混沌优化算法提出了一种新的运动学校准方法以及一种混合目标的运动学校准函数,它考虑了诸如单点测量实验、容积性测量实验等多种性能测量实验的实验结果,然后,采用Levenberg Marquardt(L-M)算法和小生境混沌优化算法应用于运动学参数校准。小生境混沌优化算法显示出了优于L-M算法的性能。实验结果表明:使用NCOA算法校准后,测量误差的标准差始终优于LMA算法,并且校准前后多关节测量臂的测量精度提高了40倍。采用L-M算法和小生境混沌优化算法应用于运动学参数校准。小生境混沌优化算法显示出了优于L-M算法的性能。
A portable coordinate measuring arm (PCMA) was a piece of portable coordinate measuring equipment that employs a series of rotating joints. In order to improve the measuring accuracy and repeatability of a PCMA
it was essential to calibrate its kinematic parameters. First
a new kinematic calibration approach for PCMAs by using a niching chaos optimization algorithm (NCOA) was proposed. A hybrid objective function for kinematic calibration was proposed that reflects the various performance tests
including the single-point articulation performance test and volumetric performance test. Then a Levenberg-Marquardt (L-M) algorithm and an NCOA are employed for calibrating the kinematic parameters. The NCOA exhibits a competitive calibration performance compared to the L-M algorithm. Experimental results show that the standard deviation of the measurement after NCOA calibration is always better than that of the L-M algorithm
and the measurement precision after calibration is improved by 40 times. An L-M algorithm and a NCOA are employed for calibrating the kinematic parameters of a PCMA. The NCOA shows better performance than the L-M algorithm.
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