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Modeling and drilling parameters optimization on burr height using harmony search algorithm in low-frequency vibration-assisted drilling

机译:低频振动辅助钻探中和谐搜索算法的毛刺高度建模与钻探参数优化

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摘要

Increasing demands call for the burr-free workpiece in precision manufacturing. Low-frequency vibration-assisted drilling (LFVAD) has been applied to improve the fabrication process. Prediction and minimization of burr size are one of the major research topics in precision machining. In this paper, an LFVAD parameters optimization model was proposed including harmony search (HS) algorithm and a modified LFVAD burr height analytical model. The burr height model of LFVAD was developed using existing analytical burr height model for conventional drilling (CD) and vibration-assisted drilling (VAD). The developed burr height models were then employed with HS algorithm, which is a new meta-heuristic optimization method based on the imitation of music improvisation process, to determine the optimal machining parameters for a given twist drill that results in minimum exit burr height. Experimental results show that the burr height of the optimized LFVAD decreased by 52.75% compared with the CD, and decreased by 17.59% compared with the un-optimized LFVAD. The simulation and experimental results demonstrate that under suitable LFVAD parameters, the burr height could be reduced.
机译:越来越多的需求要求在精密制造中呼吁无毛刺工件。已经应用低频振动辅助钻孔(LFVAD)来改善制造过程。预测和最小化毛刺尺寸是精密加工的主要研究主题之一。本文提出了一种LFVAD参数优化模型,包括和声搜索(HS)算法和修改的LFVAD毛刺高度分析模型。利用现有的分析毛刺高度模型为常规钻孔(CD)和振动辅助钻孔(VAD)开发了LFVAD的BURR高度模型。然后使用HS算法采用开发的毛刺高度模型,该HS算法是基于音乐即兴过程模仿的新的元启发式优化方法,以确定给定的扭转钻的最佳加工参数,从而导致最小出口毛刺高度。实验结果表明,与CD相比,优化的LFVAD的毛刺高度降低了52.75%,与未经优化的LFVAD相比减少了17.59%。模拟和实验结果表明,在合适的LFVAD参数下,可以降低毛刺高度。

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