基于切削力分形分析的智能鲁棒铣刀磨损监测

Tongshun Liu, K. Zhu
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引用次数: 1

摘要

刀具磨损智能监测对提高铣削精度和效率具有重要意义。在传统的智能刀具磨损监测方法中,用来表示刀具磨损的特征总是随着切削条件的变化而变化,因此不适用于切削条件变化的情况。提出了一种切削工况下铣刀磨损监测方法。该方法通过分形维数测量切削力的不规则性,并以此来指示刀具的磨损程度。针对高速数控加工进行了刀具磨损监测实验。仿真结果表明,所提出的切削力分形维数能够反映刀具的磨损程度,对切削工况具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent robust milling tool wear monitoring via fractal analysis of cutting force
The intelligent tool wear monitoring is of great importance to improve the milling precision and efficiency. In traditional intelligent tool wear monitoring methods, features used to indicate tool wear always vary with cutting conditions and hence not applicable in cutting condition-varying cases. In this paper, a cutting condition robust milling tool wear monitoring method is proposed. In the method, the irregularity of cutting force is measured by fractal dimension and then utilized to indicate the tool wear level. Experiments of tool wear monitoring are conducted for high speed CNC manufacturing. The simulation results show that the proposed fractal dimension of cutting force is capable to indicate tool wear level and robust to cutting conditions.
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