Using frequency domain analysis techniques for diagnosis of planetary bearing defect in a CH-46E helicopter aft gearbox. (October 2018)

• Record Type: Journal Article
• Authors: Zhou, L.; Duan, F.; Mba, D.; Wang, W.; Ojolo, S.
• Is Part Of: Engineering failure analysis. Volume 92(2018)
• Page Start: 71
• Page End: 83
• Publication Date: 2018-10
• Subjects: Helicopter MGB -- Planetary bearing fault diagnosis -- Signal processing; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2018.04.051
• Languages: English
• ISSNs: 1350-6307

Abstract

Abstract: 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. Highlights: Vibration dataset collected from real helicopter main gearbox is analysed. Seeded helicopter planetary bearing defects are successfully diagnosed. Various of signal processing techniques are validated and evaluated. A deterministic cancellation technique based on envelope calculation has been employed and compared with kurtogram.