Gear Fault Diagnosis Based on EMD and AR Spectrum Analysis

被引：0
|
作者：
Ai, Shufeng [1 ]
Li, Hui [2 ]
Fu, Lihui [2 ]
机构：
[1] Zhejiang Univ Media & Commun, Dept Commun Technol, Hangzhou, Zhejiang, Peoples R China
[2] Shijiazhuang Inst Railway Technol, Dept Electromech Engn, Shijiazhuang, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION, VOL I | 2009年
基金：
中国国家自然科学基金;
关键词：
Vibration; fault diagnosis; gear; empirical mode decomposition; AR Spectrum; HILBERT-HUANG TRANSFORM;
D O I：
10.1109/ICMTMA.2009.430
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A novel method to fault diagnosis of gear crack based on empirical mode decomposition (EMD) and autoregressive (AR) spectrum is presented. This method can carry out empirical mode decomposition and extract feature information of different machine parts in condition monitoring and fault diagnosis of machinery. The main objective of empirical mode decomposition is to separate the time series data into components with different time scale. Then the AR model estimation is applied to I each intrinsic mode function and the AR spectrum is obtained. As an example, the vibration signal of a gearbox is analyzed. The experimental results show that this method based on empirical mode decomposition and autoregressive spectrum can effectively diagnose the crack faults of gear.
引用
收藏
页码：673 / 676
页数：4
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