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A Scale Factor-Based Interpolated DFT for Chatter Frequency Estimation | IEEE Journals & Magazine | IEEE Xplore

A Scale Factor-Based Interpolated DFT for Chatter Frequency Estimation


Abstract:

In this paper, a scale factor-based interpolated discrete Fourier transform (IpDFT) algorithm is proposed to estimate the dominant chatter frequency. In practical measure...Show More

Abstract:

In this paper, a scale factor-based interpolated discrete Fourier transform (IpDFT) algorithm is proposed to estimate the dominant chatter frequency. In practical measurement systems of machining processes, the number of acquired sine-wave cycles (NASCs) is small. Therefore, the significant spectral interference from the negative frequency leads to the degradation of conventional IpDFTs that neglect such interference. The proposed IpDFT algorithm overcomes this problem by completely removing the long-range leakage of the negative frequency of the investigated component. We establish statistical properties of the approach contaminated with white noise, including upper and lower bounds of the theoretical variance. The simulation results demonstrate that our IpDFT algorithm outperforms existing IpDFT algorithms, especially when the NASC approaches zero. The proposed IpDFT algorithm has better antinoise capability and computational efficiency than the optimization-based algorithm by Radil. Furthermore, it is illustrated that the simulation results agree well with upper and lower bounds of the theoretical variance. Cutting force signals are collected to evaluate the algorithm experimentally.
Published in: IEEE Transactions on Instrumentation and Measurement ( Volume: 64, Issue: 10, October 2015)
Page(s): 2666 - 2678
Date of Publication: 29 April 2015

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I. Introduction

Chatter is the self-excited high-amplitude vibration in metal cutting. Chatter has been researched for more than a century, and it is still a major problem in machining processes including turning, milling, and drilling [1], [2]. When chatter occurs, it will lead to poor surface quality, excessive noise, accelerating tool wear, and waste of materials. For these reasons, chatter suppression is a topic of enormous interest. Spindle speed variation (SSV) is an active technique for chatter elimination [2]. The regenerative chatter can be suppressed, since after the speed is changed, there is no regenerative feedback loop. This kind of modulating the spindle speed is attracting increasing interest because of its simplicity and effectiveness in chatter suppression. In [3] and [4], the SSV is implemented by online computing the preferred spindle speed. Although these algorithms have different expressions for calculating the preferred spindle speed, the chatter frequency is an essential part, which must be identified before chatter suppression. Al-Regib et al. [5] proposed a programming sinusoidal SSV to suppress chatter with the optimum frequency and amplitude ratio. The spindle speed is varied as a sinusoidal function, which actually disrupts the regenerative chatter. In their algorithm, the chatter frequency and current spindle speed are needed. Therefore, the dominant chatter frequency needs to be estimated from the cutting force or acceleration signal once the onset of chatter has been detected.

References

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