基于EEMD-BPF的工业机器人铣扩孔模态耦合颤振信号提取方法

A signal extraction method for mode coupling chatter of industrial robot milling and reaming based on EEMD-BPF

  • 摘要: 工业机器人铣扩孔作为一种精细扩孔方法,旨在消除孔内外缺陷,改善机器人的制孔精度。但由于机器人的刚度缺陷,加工过程易出现与本体固有特性相关的模态耦合颤振。针对工业机器人铣扩孔模态耦合颤振信号有效提取的问题,文章提出一种基于集合经验模态分解(ensemble empirical mode decomposition,EEMD)和带通滤波(band-pass filter,BPF)的颤振信号提取方法。通过EEMD对加工信号的预处理确定出以耦合颤振频率为主激振频率的本征模态,利用单边趋势判别法改善EEMD中极值计算的效率。通过选取能量熵值比和相关系数为特征并结合BPF提取本征模态中的颤振信息,重构模态耦合颤振信号。实验表明,EEMD较经验模态分解EMD有一定的模态混叠抑制作用。主轴转速1 800 r/min、径向切削厚度0.6 mm下的实验结果显示,EEMD-BPF较EMD-BPF超前0.31 s识别出颤振。

     

    Abstract: As a fine reaming method in through hole, industrial robot is designed to eliminate the defects inside and outside the hole and improve the accuracy of robot hole making. However, due to the stiffness defects of the robot, the mode coupling chatter related to the intrinsic modes is easy to occur during milling and reaming. Aiming at solving the problem of effective signals extraction of mode coupling chatter in the process of milling and reaming of industrial robots, a method based on EEMD (ensemble empirical mode decomposition) and BPF (band-pass filtering) was proposed in this paper. The eigenmodes with mode coupling chatter frequency as the excitation frequency were determined by EEMD, and the unilateral trend discrimination was introduced to improve the efficiency of extreme value calculation in EEMD. By selecting the energy entropy ratio and correlation coefficient, and combining with BPF, the mode coupling chatter information in the intrinsic mode was extracted, and finally the mode coupling chatter signal was reconstructed. Experimental results showed that EEMD has a certain mode aliasing inhibition effect compared with EMD. The experimental result of spindle speed 1 800 r/min and radial cutting thickness 0.6 mm showed that EEMD-BPF is 0.31 s ahead of EMD-BPF in detecting chatter.

     

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