HHT-Based Detection Method of Cutter Abnormal Vibration in Spiral Surface Machining

Abstract

Background:: Cutter abnormal vibration occurs frequently during the spiral surface machining process, and it results in low quality of the finished surface. In order to suppress cutter abnormal vibration effectively, it is necessary to detect abnormal vibration as soon as possible, but the analysis and processing of the cutter abnormal vibration signal in spiral surface machining are difficult because of its complicated components and non-linear non-stationary characteristics. In this paper, a detection method of cutter abnormal vibration signal based on Empirical Mode Decomposition (EMD) and Hilbert–Huang Transform (HHT) is proposed to be applied in spiral surface machining. Method:: First of all, EMD of the cutter vibration signal in the spiral surface machining is performed to obtain a series of Intrinsic Mode Function (IMF) components in different frequency bands. Secondly, the variation in the energy of each IMF component in the frequency domain and the correlation with the original signal are analyzed to obtain the IMF component with the largest amount of information on abnormal vibration symptom. Finally, the Hilbert transform is conducted on the IMF component to extract the symptom features of abnormal vibration. Results:: The Hilbert-Huang spectrogram obtained by Hilbert transform is a two-variable function of time and frequency, from which the frequency information at any time can be obtained, including the magnitude and amplitude of the frequency and the corresponding moments appearing, which can describe the time-frequency characteristics of the non-stationary non-linear signal in detail. Experimental results show that the HHT based method to analyze the cutter vibration signal in the spiral surface machining can extract the symptom of abnormal vibration quickly and effectively, and can detect cutter abnormal vibration rapidly. Conclusion:: The proposed method based on HHT in this paper is fundamentally different from the traditional signal time-frequency analysis methods, and has achieved good results in practical applications. This method could be successfully used in abnormal vibration detection, which could also provide basis and guarantee for the subsequent suppression of abnormal vibration.