Vibration-Based Fault Detection of Sharp Bearing Faults in Helicopters
Vibration-Based Fault Detection of Sharp Bearing Faults in Helicopters
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DOI：
10.3182/20120829-3-mx-2028.00050
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
V. Girondin;Hervé Morel;J. Cassar;K. Pékpé
中科院分区：
文献类型：
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作者：
V. Girondin;Hervé Morel;J. Cassar;K. Pékpé
机械和信号处理团体已经开发了许多信号处理工具，以从振动分析中找到尖锐轴承故障（如局部剥落）的特征症状。然而，直升机的情况下，强加了一个有限的采样频率有关的观察到的现象，许多嘈杂的振动和飞行制度。传统方法的性能在这样的环境中受到限制，主要是在识别故障频率。局部轴承故障引起的时间周期性和脉冲模式，产生冗余的谐波在频谱域。在这篇文章中，提出了四种方法来利用这种冗余。这些方法提供了故障频率的估计器和该估计的质量的指示器。这些指示器用于评估故障的严重性。然后，这四种方法进行了测试的合成和飞行数据，以说明和讨论他们的效率。
Many signal processing tools have been developed by the mechanical and signal processing community to find the characteristic symptoms of sharp bearing faults (like localized spalling) from vibratory analysis. However the context of helicopter imposes a limited sampling frequency regarding the observed phenomena, many noisy vibrations and flight regimes. The performances of the classical methods are limited in such an environment mainly in identifying fault frequencies. Local bearing faults induce temporal periodic and impulsive patterns that produce redundant harmonics in the spectral domain. In this article four methods are proposed to take advantage of that redundancy. These methods provide an estimator of the fault frequency and an indicator of the quality of that estimation. These indicators are used to assess the severity of the fault. The four methods are then tested on synthesized and flight data in order to illustrate and discuss their efficiency.