Multi harmonic and random stiffness excitation for milling chatter suppression. (1st April 2019)

• Record Type: Journal Article
• Authors: Wang, Chenxi; Zhang, Xingwu; Liu, Jinxin; Yan, Ruqiang; Cao, Hongrui; Chen, Xuefeng
• Is Part Of: Mechanical systems and signal processing. Volume 120(2019)
• Page Start: 777
• Page End: 792
• Publication Date: 2019-04-01
• Subjects: Multi harmonic stiffness excitation -- Random stiffness excitation -- Parameters optimization -- Milling chatter suppression -- Genetic algorithm -- Random walk methodology; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2018.11.019
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: The milling dynamic model of periodic stiffness excitation with two degrees of freedom is derived. Multi harmonic stiffness excitation and random stiffness excitation are proposed for chatter suppression. The parameters of periodic stiffness excitation are optimized by the genetic algorithm and the random walk methodology. The model and analysis results are verified by a number of milling tests. Abstract: In cutting process, as one of the most unfavorable factors, the regenerative chatter results in serious degradation of the part surface quality, tool life and machining efficiency. According to the previous research, single frequency stiffness excitation (SFSE) is able to suppress chatter vibration effectively, where the stiffness varies in sine, cosine, square and triangle waveforms. However, the real vibrations in milling process are very complex and the SFSE can vary just in simple forms without considering phase variation. In order to mitigate chatter more effectively, this paper proposed multi harmonic stiffness excitation (MHSE) and random stiffness excitation (RSE). Due to the existence of delay item, the stiffness excitation parameters cannot be optimized with analytic methods. Therefore, with regard to MHSE, the Fourier series is used to expand the function of stiffness variation and the genetic algorithm is employed to optimize the frequency, amplitude and phase. From SFSE to MHSE, the stiffness variation can also be extended to RSE, where the variation waveform seems periodic on the whole time domain but stochastic within one period. This function of stiffness excitation cannot be described by specific parameters; thus, the random walk methodology is implemented for random waveforms optimization. The optimized random waveform is used to guide the stiffness variation for increasing the stability lobe diagrams (SLD) and suppressing chatter vibration. The simulation results show that the SLDs with MHSE and RSE are higher than those under SFSE. Finally, the milling experiments are implemented on a three-axis milling machine to validate the optimized parameters on chatter suppression. Under stiffness excitation, the chatter frequency in milling process vanishes, which shows that the proposed method can suppress chatter effectively.