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Using frequency domain analysis techniques for diagnosis of planetary bearing defect in a CH-46E helicopter aft gearbox

机译:利用频域分析技术在CH-46E直升机AFT齿轮箱中诊断行星轴承缺陷

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摘要

Condition monitoring for helicopters has always been one of the most critical technologies to guarantee the integrity of the rotorcrafts, enhance operational and personnel safety, and reduce the overall maintenance costs. Over the past decades, health and usage monitoring system (HUMS) has been developed and implemented in helicopters to monitor the health status for the main gearbox (MGB) and other key components of the transmission system, improving condition-based maintenance for helicopters. However, many studies have indicated that current HUMS has a limited sensitivity to MGB planetary bearing defects. To enhance HUMS' performance, this paper presents an approach based on frequency domain analysis techniques to diagnose planetary bearing defects using real helicopter data collected from a CH-46E helicopter aft MGB. Vibration data was processed using signal processing techniques including self-adaptive noise cancellation (SANC), discrete-random separation (DRS), cepstrum editing, kurtogram, envelope analysis and iterative envelope cancellation. Processing results conclude that frequency domain analysis techniques can provide distinct and intuitive indications of the seeded defects at both the inner race and the outer race of the faulty planetary bearing.
机译:直升机的状态监测一直是保证旋翼飞行器完整性,增强运营和人才安全的最重要技术之一,并降低整体维护成本。在过去的几十年中,在直升机中开发和实施了健康和使用监控系统(HUMS),以监测主变速箱(MGB)的健康状况和传动系统的其他关键部件,改善直升机的条件维护。然而,许多研究表明,目前的嗡嗡声对MGB行星轴承缺陷具有有限的敏感性。为了提高HUMS的性能,本文提出了一种基于频域分析技术的方法,用于使用从CH-46E直升机AFT MGB收集的真正直升机数据诊断行星轴承缺陷。使用信号处理技术处理振动数据,包括自适应噪声消除(SANC),离散 - 随机分离(DRS),综衣编辑,Kurtogram,信封分析和迭代包络消除。加工结果得出结论,频域分析技术可以在内部血上和故障行星轴承的外圈中提供种子缺陷的不同和直观的指示。

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