Electrical Department, LTII Laboratory, University of Bejaia, Bejaia 06000, Algeria.
J Acoust Soc Am. 2012 Nov;132(5):EL405-10. doi: 10.1121/1.4758764.
A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.
本文提出了一种基于峭度图分析的实时滚动轴承早期故障检测的信号处理方法。峭度图是一种四阶谱分析工具，用于检测和描述信号中的非平稳性。该技术从对选定频带的共振特征进行研究开始，以提取代表性特征。传统的频谱分析不适用于非平稳振动信号和实时诊断。通过一系列对应于不同轴承状况的实验测试来检验所提出技术的性能。测试结果表明，该信号处理技术是一种有效的滚动轴承故障自动检测方法，为集成感应电机状态监测提供了良好的基础。
