Fatigue crack detection in planetary gears: Insights from the HUMS2023 data challenge

Research output: Contribution to journalArticlepeer-review


Employed extensively in industry, planetary gears offer a high power density and high efficiency. However, their operation in frequently dynamic conditions does accelerate the risk of gear failures. This paper explores the phenomenon of fatigue cracking in planetary gearsets, more specifically in thin-rim helicopter main rotor transmission planet gears. Such fatigue cracks typically initiate at or near the planet bearing outer raceway surface and can propagate through the gear body. Whilst such a failure is catastrophic for any gearbox, it is especially disastrous in the case of a helicopter gearbox due to the potential loss of life involved. Given that the reliable detection of planetary gear cracks remains a significant challenge for the vast majority of condition monitoring approaches, a data contest was organized by DSTG at the HUMS2023 conference. DSTG conducted a unique test campaign where vibrations were measured on a main rotor gearbox of a Bell Kiowa 206B-1 (OH-58) helicopter. This campaign produced an extensive vibration data set that was partially shared with the contestants. The purpose of the contest entailed the early detection of the rim gear crack as well as tracking the fault progression. This paper presents the main observations of this data challenge and goes into more detail with regard to the employed approaches as well as the main difficulties encountered when analysing planetary gear vibration data.

Original languageEnglish
Article number111292
Pages (from-to)1-26
Number of pages26
JournalMechanical Systems and Signal Processing
Publication statusPublished - 15 Apr 2024

Bibliographical note

Funding Information:
This research was supported by funding from the Flemish Government under the “Onderzoeksprogramma Artificiële Intelligentie (AI) Vlaanderen” programme. They would like to acknowledge FWO (Fonds Wetenschappelijk Onderzoek), Belgium for their support through the post-doctoral grant of Cedric Peeters ( 1282221N ) and SBO project Robustify ( S006119N ) and Blauwe Cluster ICON project Supersized 4.0. The authors would also like to thank the FOD Economie for the ETF Poseidon project.

Publisher Copyright:
© 2024 Elsevier Ltd


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