Prediction Method for Roundness Error of Machined Deep-hole Based on Vibration Behaviors of Cutting Tools

doi:10.3969/j.issn.1000-1093.2018.02.020

Abstract

Abstract: On the basis of feature of machined deep hole, an intelligent recognition method is proposed to predict the roundness error of machined hole by using the time-frequency domain information of machining tool cutting vibration. In order to establish the relationship of tool cutting vibration and roundness error, the partitioning problem of the fuzzy input-space of vibration mode is converted into the initial value of input space by introducing the modified fuzzy clustering algorithm into support vector machine, so that the higher accuracy and generalization ability of the proposed method are guaranteed simultaneously. On this basis, a prediction model for roundness error of machined deep-hole is built. A series of experiments were conducted with different cutting parameters and electric currents acting on vibration suppression instrument. The experimental results show that the proposed method is effective and feasible.Key

Key words: deep-holedrilling, roundnesserror, toolcuttingvibration, predictionmethod

CLC Number:

O322

LI Chao, KONG Ling-fei, LIANG Yan-ming, JIANG He-ling, YAN Dong. Prediction Method for Roundness Error of Machined Deep-hole Based on Vibration Behaviors of Cutting Tools[J]. Acta Armamentarii, 2018, 39(2): 364-372.

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第39卷
第2期2018 年2月兵工学报ACTA
ARMAMENTARIIVol.39No.2Feb.2018