Application of Combined TFPF and EEMD Denoising Method in Gear Fault Diagnosis

被引：0
|
作者：
Ning S. [1 ,2 ]
Han Z. [1 ]
Wu X. [2 ]
Zhao Y. [1 ]
机构：
[1] College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan
[2] College of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan
来源：
Han, Zhennan (zhennan_han@hotmail.com) | 2017年 / Nanjing University of Aeronautics an Astronautics卷 / 37期
关键词：
Denoising; Ensemble empirical mode decomposition (EEMD); Gear root crack; Time-frequency peak filtering (TFPF);
D O I：
10.16450/j.cnki.issn.1004-6801.2017.05.024
中图分类号：
学科分类号：
摘要：
In order to eliminate the influence of noise on fault feature extraction in gear transmission system, a method based on time-frequency peak filtering (TFPF) and ensemble empirical mode decomposition (EEMD) noise reduction method combining is proposed. In view of the TFPF algorithm being restricted in the window length selection problem, the balance in two aspects of the signal noise suppression and signal fidelity is improved by using the EEMD method. When the noisy signal is decomposed by EEMD, a series of intrinsic mode function (IMFs) is obtained, which is arranged from high to low according to frequency components. Through calculating the correlation coefficient between IMFs, the IMFs needed to be filtered is determined. Then, a different window length is chosen to filter different IMFs by using TFPF. At last, a reconstructive signal can be obtained by combining the filtered IMFs and the residual IMFs. The denoising method is applied to simulation signals and measured vibration signals, and the results show that the EEMD+TFPF method can effectively extract crack fault feature from intensive background noise. © 2017, Editorial Department of JVMD. All right reserved.
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页码：1011 / 1017
页数：6
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