Real-time Detection of Defects in Train Bearings Based on Analysis of Signal Characteristics in Time-Frequency Domains

被引：0

作者：

Yong Y. ^{[1
]}

Huang X. ^{[1
]}

Tang Y. ^{[1
]}

机构：

[1] School of Materials Science and Engineering, Southwest Jiaotong University, Chengdu

来源：

Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University | 2017年 / 52卷 / 06期

关键词：

Defect; Real-time detection; Time and frequency domain features; Train bearing;

D O I：

10.3969/j.issn.0258-2724.2017.06.019

中图分类号：

学科分类号：

摘要：

To realize the real-time monitoring and quick diagnosis of defects in rolling trainbearings, an approach is proposed based on the time and frequency analysis of signal characteristics, especially the combination of time-domain characteristics analysis and resonance demodulation based on wavelet transforms. A real-time detection system is set up for detecting train bearing defects including a sensor data acquisition module, a sound diagnostic module, data storage and an output module. The following tests for bearings were conducted for comparison: normal bearings, bearings with inner-ring defects, and bearings with inner-ring and roller defects. The results showed that the analysis of time-domain characteristics can be used to determine bearings were faulty prior to operation. The resonance demodulation based on wavelet transform extracted the inner-ring defect frequency and the roller defect frequency of 35 Hz and 23 Hz, respectively. The stability and reliability of the real-time detection system are verified. © 2017, Editorial Department of Journal of Southwest Jiaotong University. All right reserved.

引用

页码：1182 / 1187

页数：5

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