Three-dimensional empirical mode decomposition (TEMD): A fast approach motivated by separable filters

2017 ◽  
Vol 131 ◽  
pp. 307-319 ◽  
Author(s):  
Zhi He ◽  
Jun Li ◽  
Lin Liu ◽  
Yi Shen
Keyword(s):  
Empirical Mode Decomposition ◽  
Three Dimensional ◽  
Fast Approach ◽  
Mode Decomposition ◽  
Separable Filters

scholarly journals Chatter Identification of Three-Dimensional Elliptical vibration Cutting Process Based on Empirical Mode Decomposition and Feature Extraction

2018 ◽  
Vol 9 (1) ◽  
pp. 21 ◽  
Author(s):  
Mingming Lu ◽  
Bin Chen ◽  
Dongpo Zhao ◽  
Jiakang Zhou ◽  
Jieqiong Lin ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Empirical Mode Decomposition ◽  
Three Dimensional ◽  
Vibration Signals ◽  
Elliptical Vibration Cutting ◽  
Vibration Cutting ◽  
Chatter Identification ◽  
Elliptical Vibration ◽  
Mode Decomposition ◽  
The Mean

Three-dimensional elliptical vibration cutting (3D-EVC) is one of the machining methods with the most potential in ultra-precision machining; its unique characteristics of intermittent cutting, friction reversal, and ease of chip removal can improve the machinability of materials in the cutting processes. However, there is still not much research about the chattering phenomenon in the 3D-EVC process. Therefore, based on the empirical mode decomposition (EMD) technique and feature extraction, a chatter identification method for 3D-EVC is proposed. In 3D-EVC operations, the vibration signal is collected by the displacement sensors and converted to frequency domain signal by fast Fourier transform (FFT). To identify tool cutting state using the vibration frequency signal, the vibration signals are decomposed using empirical mode decomposition (EMD), a series of intrinsic mode functions (IMFs), so the instantaneous frequency can be reflected by the vibration signals at any point. Then, selecting the primary IMFs which contain rich chatter information as the object in feature extraction identification, and two identification indexes, that is, the mean square frequency and self-correlation coefficient, are calculated for the primary IMFs by MATLAB software, to judge the chatter phenomenon. The experimental results showed that the mean square frequency and self-correlation coefficient of the three cutting states increase with the increase in the instability of the cutting state. The effectiveness of the improved chatter recognition method in 3D-EVC machining is verified.

Three-Dimensional Imaging Lidar Signal Denoising Method Based on Empirical Mode Decomposition

2011 ◽  
Vol 31 (12) ◽  
pp. 1211004
Author(s):  
焦宏伟 Jiao Hongwei ◽  
秦石乔 Qin Shiqiao ◽  
王省书 Wang Xingshu ◽  
胡春生 Hu Chunsheng ◽  
吴伟 Wu Wei
Keyword(s):  
Empirical Mode Decomposition ◽  
Three Dimensional ◽  
Signal Denoising ◽  
Lidar Signal ◽  
Denoising Method ◽  
Three Dimensional Imaging ◽  
Mode Decomposition
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