Cutting stress modeling and parameter identification for fine drilling process based on various cutting mechanisms

IF 2.9 3区 工程技术 Q2 AUTOMATION & CONTROL SYSTEMS
Kuikui Feng, Faping Zhang, Wuhong Wang, Zhenhe Wu, Mengdi Zhang, Biao Wang
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引用次数: 0

Abstract

The superposition effect of various cutting mechanisms (CM) in the fine drilling process brings great challenges to the accurate characterization of the cutting stress field of the workpiece. To solve the above problem, the cutting stress characterization modeling and parameter identification for the fine drilling process with multiple cutting mechanisms is studied in this paper. Firstly, two cutting mechanisms (shear-slip and plough-slip) are distinguished according to the relative tool sharpness (RTS) which is determined by the cutting tool radius and cutting depth, and the fine characterization model for drilling stress of the workpiece is constructed by considering the two cutting mechanisms. Then, in order to overcome the problem that model parameters are difficult to be accurately determined, the sub-interval decomposition optimization method (SDOM) and the improved particle swarm optimization (PSO) are employed to identify parameters in the model. Finally, the proposed method is verified by comparing the single cutting mechanism model, the multiple cutting mechanisms model, and the actual characterization parameter model.

Abstract Image

基于各种切削机制的精钻加工切削应力建模和参数识别
精钻过程中各种切削机构(CM)的叠加效应给工件切削应力场的精确表征带来了巨大挑战。为解决上述问题,本文研究了多切削机制精钻过程的切削应力表征建模和参数识别。首先,根据由切削刀具半径和切削深度决定的相对刀具锋利度(RTS)来区分两种切削机制(剪切-滑移和犁-滑移),并通过考虑两种切削机制来构建工件钻孔应力的精细表征模型。然后,为了克服模型参数难以精确确定的问题,采用了子区间分解优化法(SDOM)和改进的粒子群优化法(PSO)来确定模型中的参数。最后,通过比较单切削机构模型、多切削机构模型和实际特征参数模型,验证了所提出的方法。
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来源期刊
CiteScore
5.70
自引率
17.60%
发文量
2008
审稿时长
62 days
期刊介绍: The International Journal of Advanced Manufacturing Technology bridges the gap between pure research journals and the more practical publications on advanced manufacturing and systems. It therefore provides an outstanding forum for papers covering applications-based research topics relevant to manufacturing processes, machines and process integration.
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