对铣床主轴总成的切削力信号进行识别，用于监测设备磨损情况

2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI:10.1109/DCNA56428.2022.9923162

M. Brovkova, O. Torgashova, O. V. Ushakova, V. Martynov, M. A. Solomin

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引用次数: 0

摘要

本文提出了利用铁木辛科梁的数学模型来评估设备磨损监测中的切削力。提出了一种基于卡尔曼滤波的切削力识别算法。识别出的信号用于应用刀具磨损评估准则。

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The cutting force signal identification of the milling machine spindle assembly for monitoring equipment wear

The work proposes to use a mathematical model of the Timoshenko beam to evaluate the cutting force in monitoring equipment wear. It is proposed to use the Kalman filtering procedure as a cutting force identification algorithm. The identified signal is used to apply tool wear evaluation criteria.

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2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)

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