MATEC Web Conf.
Volume 139, 20172017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|Number of page(s)||7|
|Published online||05 December 2017|
Research of Penetration Overload Signals Processing Method Based on EEMD and WT
1 Faculty of Mechanical and Electrical Engineering, Nanjing College of Information Technology, Jiangsu, 210023, China
2 Faculty of Mechanical and Electrical Engineering, North University of China, Taiyuan, 030051, China
* Corresponding author: firstname.lastname@example.org
Hard Target Penetration is a very complex dynamic problem, and penetration signals contain axial de-acceleration signals, vibration signals and other weakly noise signals. It is difficult to obtain penetration feature signals through some methods filtering unwanted vibration signals and noise signals. As such, we propose a joint filtering method based on EEMD (Ensemble Empirical Mode Decomposition) and WT (Wavelet Transform) to solve this problem. This method consists of four main steps: (a) penetration signals decomposing via EEMD method, this gets the IMF (Intrinsic Mode Function) components, (b)then we calculate the Whole BURG power spectrum of the original signals and each component, after that compare the power spectrum of each component with the original signals, this draws the original signals EEMD decomposition scale, (c) the high-frequency components of IMF filtering based on the WT threshold, (d) signals reconstruct by using low-frequency IMF components which reflect signals characteristic and high-frequency IMF components through wavelet filtered. Experiment show that proposed method can effectively determine the penetration signals decomposition scale, eliminate vibration and noise signals of penetration process, avoid the losing of the high-frequency components when using a single wavelet filtering method. The result of the proposed method can get better SNR than WT, the velocity and depth are in good agreement with the results of experiment.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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