Bearing Fault Diagnosis Based on Weighted Phase Space Reconstruction

摘要：

The vibration signals are often non-linear and nonstationary when the bearings are in failure. This paper will adopt phase space reconstruction algorithm and make bearing vibration time series extend to high-dimensional phase space. Some characteristics are difficult to identify in one-dimensional time series, but we can transform them into many different attractors in high-dimensional phase space, in this way, the background signal and noise would be decomposed into different sub-space. Through the phase space projection method and after the window operation, the different phase points in phase space could be projected to the one-dimensional space, so it can be effective to separate the background signal and noise components. Weighted combination of noise reduction algorithm for phase space reconstruction and the Hilbert transform to extract the lowfrequency characteristics of the background signal realize bearing fault identification. The experimental data shows that the algorithm has an effective result in bearing fault Identification.

关键词： bearing phase space reconstruction noise reduction fault diagnosis

作者: Lv Yong Zhang Hongwei Li Yourong Xiao Han Wang Zhigang Hou Shuming

作者单位: Wuhan University of Science and Technology, Wuhan, Hubei, 430081, China

会议类型: 国际会议

会议名称: 2010 International Conference on Digital Manufacturing and Automation(2010 数字制造与自动化国际会议 ICDMA 2010)

会议地点: 长沙

会议语种:英文

页码: 315-318

在线出版日期: 2010-12-18（万方平台首次上网日期，不代表论文的发表时间）