Fault Detection and Remaining Useful Life Estimation of a Scuffed Gear
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Abstract
In helicopter drivetrains, vibration-based gear fault detection is critical to safety, reliability, and operational availability. Although there are numerous gear fault detection algorithms have been proposed, there is comparatively little work on gear wear.
This study presents a quantitative comparison of time synchronous average (TSA) based gear fault detection algorithms for identifying scuffing and wear in a turboshaft engine high-speed turbine shaft pinion. A large field dataset from a degraded engine is compared with data from a nominal replacement component. Condition indicator (CI) responses are evaluated using statistical separability to determine each algorithm’s ability to distinguish the damaged gear from the nominal baseline.
The comparison includes residual and difference-signal analysis, energy-operator methods and variants, narrowband analysis with bandwidth sensitivity evaluation, amplitude and frequency modulation analysis, and standard gear fault condition indicators. The statistical significance and robustness of each method are quantified.
The best-performing indicators are then used to construct a component health index (HI), which is applied to assess gear condition and demonstrate remaining useful life (RUL) estimation in a maintenance-relevant framework.
How to Cite
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RUL, Prognostic, Condition Indicator, TSA
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