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- 2017
基于时频域特征分析的列车轴承缺陷实时检测
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Abstract:
为对列车轴承状态的实时监测和缺陷的快速诊断，提出了一种基于时频域特征分析的检测方法.该方法结合时域特征分析和基于小波变换的共振解调法，建立包括传感器数据采集模块、异音诊断模块、数据存储和输出模块的列车轴承缺陷实时检测系统.利用该系统分别对正常轴承、内圈缺陷轴承以及滚子缺陷轴承进行了现场测试.结果表明：时域特征分析可初步诊断出轴承是否存在缺陷；基于小波变换的共振解调方法提取列车轴承其内圈缺陷频率为35 Hz，滚子缺陷频率为23 Hz，验证了该实时检测系统的稳定性和可靠性.
：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 comparisonnormal 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
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