Roller Bearing Fault Diagnosis Based on Wavelet Packet and BP Neural Network

被引：0
|
作者：
Qiao Wensheng [1 ]
Gu Yuhai
Chen Xinghui [1 ]
Ai Shijuan [1 ]
机构：
[1] Beijing Jinghang Corp, China Acad Launch Vehicle Technol, Beijing 100076, Peoples R China
来源：
PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOL. 3 | 2008年
关键词：
Wavelet packets; neural network; denoise; fault diagnosis;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The bearing is the key accessory of rotary machines and nearly 30 percent of the fault of rotary machines is the bearing fault. So the research for the fault diagnosis of bearing is very important. This paper gives a method for diagnosing the fault of bearing. At first, using wavelet to denoise the vibration signals, then extracting character vector of energy within frequency domain through wavelet packet analysis and utilizes BP neural network to accomplish rolling bearing fault diagnosis. The paper describes the superiority of this analysis method in bearing fault diagnosis, indicates the direction of latest development of the bearing fault diagnosis.
引用
收藏
页码：1670 / 1674
页数：5
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