基于谱峰度分析的风电高速轴轴承运行失效分析

L. Saidi, Eric Bechhoefer, Jaouher Ben Ali, M. Benbouzid
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引用次数: 12

摘要

风电齿轮箱的过早失效会增加能源价格,影响其可靠性。大多数齿轮箱故障是由轴承引起的。高速轴承和行星轴承的过早失效率很高。轴承故障诊断的一项关键工作是寻找覆盖故障轴承信号的最佳频段,这在实践中是一项具有挑战性的任务。峰度图是一种用来描述隐藏在信号中的非平稳性的高级技术。因此,允许响应给定的问题。它包括确定中心频率(共振)和适当的带宽,使峰度最大化。本文研究了一种基于平方包络的谱峰度诊断高速轴轴承打滑的方法。我们已经验证了谱峰度诊断策略在单缺陷诊断性能改进方面的潜力,并使用了来自传动系风力涡轮机的实际测量数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wind turbine high-speed shaft bearing degradation analysis for run-to-failure testing using spectral kurtosis
Premature failures of wind turbine gearboxes increase the price of energy and affect their reliability. Most gearbox failures initiate in bearings. High-speed bearings and planetary bearings exhibit a high rate of premature failure. A critical work of bearing fault diagnosis is finding the optimum frequency band that covers faulty bearing signal, which is a challenging task in practice. The kurtogram is a high technic used to characterize non-stationarities hidden in a signal. Thus, allows responding to the given problem. It consists to determine the central frequency (resonance) and the appropriate bandwidth witch maximizes the kurtosis. This paper addresses a squared envelope based spectral kurtosis method diagnosis for skidding in high-speed shaft bearings. We have verified the potential of the spectral kurtosis diagnostic strategy in performance improvements for single-defect diagnosis using real measured data from a drive train wind turbine.
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