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针对平面三自由度冗余驱动并联机床,提出基于最少参数线性组合理论的分步自标定方法。根据误差模型输出和机构自由度,给出工程中所有常用的测量方式;然后逐一进行辨识性分析,得到各测量方式下可辨识的不同最少参数线性组合;在兼顾辨识完整性和参数辨识性能的条件下,确定出包含分步测量、分步参数辨识、分步误差补偿的分步自标定方法。仿真结果表明:该方法可完全屏蔽掉不影响终端精度的无关参数,并可提高每步中参数辨识的准确性。最终参数辨识结果与设定值基本相同,验证了该方法的可行性。
Aiming at the planar three degrees of freedom redundant drive parallel machine tool, a stepwise self-calibration method based on the least parameter linear combination theory is proposed. According to the output of the error model and the degree of freedom of the mechanism, all the commonly used measurement methods in engineering are given. Then the discriminant analysis is carried out one by one to obtain the linear combination of different minimum parameters which can be identified in each measurement mode. In consideration of the recognition integrity and parameter identification performance Under the conditions, step-by-step self-calibration method including step measurement, step parameter identification and step error compensation is determined. The simulation results show that this method can completely shield irrelevant parameters that do not affect the terminal accuracy and improve the accuracy of parameter identification in each step. The final parameter identification result is basically the same as the set value, which verifies the feasibility of the method.