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Estimation of stable cutting zone in turning based on empirical mode decomposition and statistical approach

机译:基于经验模态分解和统计方法的车削稳定切削区估计

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摘要

Analysis and suppression of tool chatter are essential for maintaining the high-performance level and enhancing the useful life of machinery. Despite the immense work done within this domain, still many aspects related to regenerative chatter remain unexplored. Researchers had suggested various techniques to explore the chatter mechanism based on feature extraction of experimentally recorded chatter signals. However, the effect of background noise and other disturbances on chatter signals has been overlooked by these researchers. To obtain the exact effect of cutting parameters on chatter signals, it is essential to sieve out the noise contents from these signals. This aforesaid fact motivated the present research work. In the present study, acoustic chatter signals have been recorded using a microphone, by performing experiments on CNC trainer lathe. The recorded chatter signals have been pre-processed using empirical mode decomposition technique. Thereafter, the obtained intrinsic mode functions have been subsequently analyzed to identify the most dominating mode that is pertaining to tool chatter. Further, a new parameter named as chatter index and material removal rate (MRR) have been evaluated as responses to estimate the stable cutting zone at different cutting conditions. Moreover, mathematical models have been developed using response surface methodology, in order to establish the dependency of tool chatter and MRR on machining parameters.
机译:分析和抑制刀具颤动对于保持高性能水平和提高机械的使用寿命至关重要。尽管在这一领域做了大量的工作,但与再生喋喋不休相关的许多方面仍未得到探索。研究人员提出了各种技术来探索基于实验记录的颤动信号的特征提取的颤动机制。然而,这些研究人员忽略了背景噪声和其他干扰对喋喋不休信号的影响。为了获得切割参数对颤振信号的确切影响,必须从这些信号中筛选出噪声内容。上述事实激发了本研究工作。在本研究中,通过在数控训练机车床上进行实验,使用麦克风记录了声学颤动信号。记录的颤振信号已使用经验模式分解技术进行预处理。此后,对获得的固有模式函数进行了分析,以确定与工具颤动相关的最主要模式。此外,还评估了一个名为颤振指数和材料去除率 (MRR) 的新参数作为响应,以估计不同切削条件下的稳定切削区。此外,还使用响应面方法开发了数学模型,以确定刀具颤动和 MRR 对加工参数的依赖性。

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