A comparative study of EMD and EEMD approaches for identifying chatter frequency in CNC turning
A comparative study of EMD and EEMD approaches for identifying chatter frequency in CNC turning
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DOI：
10.1016/j.euromechsol.2018.10.004
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Y. Shrivastava;Bhagat Singh
中科院分区：
文献类型：
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作者：
Y. Shrivastava;Bhagat Singh
刀具颤振识别是当今研究人员关注的重要问题之一；因为它会对刀具寿命和表面光洁度产生不利影响，从而降低整体生产率。过去，研究人员提出了各种技术来补偿喋喋不休的影响。信号处理就是这样一种新兴技术，它已被证明在研究颤振方面非常有效。在这个领域中有各种各样的方法。Hilbert-Huang变换（HHT）就是其中之一。HHT由经验模态分解（EMD）和经典希尔伯特变换（HT）组成。EMD将几乎任何信号分解成有限的函数集和残差，其希尔伯特变换给出物理瞬时频率。然而，在EMD中存在着模态混合的关键问题。为了克服这一问题，本文对实验获得的原始颤振信号采用了合适的EEMD方法来识别颤振频率，这是前人没有做过的。在目前的工作中，对实验获得的原始颤振信号进行了时频分析，考虑了EMD和EEMD技术，然后比较了它们的结果，以确定每种方法的适用性。从目前的分析中可以推断出，EEMD在车削加工中的颤振检测中具有很高的准确性。
Tool chatter identification is one of the most important issues for today's researchers; as it adversely affects the tool life and surface finish which in turn reduces the overall productivity. In the past, researchers have proposed various techniques to compensate the effect of chatter. Signal processing is one such emerging technique that has proved to be quite efficient in exploring chatter. There are various approaches within this domain. Hilbert-Huang transform (HHT) is one of them. HHT is composed of empirical mode decomposition (EMD) and classical Hilbert transform (HT). EMD decomposes nearly any signal into a finite set of functions and a residue, whose Hilbert transform gives physical instantaneous frequency. However, there is a critical problem of mode mixing in EMD. To overcome this problem, a suitable EEMD approach has been adopted on experimentally acquired raw chatter signals in order to identify chatter frequency which has not been done by the previous researchers. In the present work, time-frequency analysis of experimentally acquired raw chatter signals have been done considering both EMD and EEMD techniques and thereafter their results have been compared to ascertain the suitability of each approach. It has been inferred from the present analysis that EEMD is quite apt in detecting chatter in turning operation with utmost accuracy.