Improving the Performance of Bearing Fault Detection on a Turbo Shaft Engine

Abstract

Health and usage monitoring systems (aka “HUMS”) have typically not been associated with CFR Title 14 type 27 normal category rotorcraft (weighing less than 7000 pounds, with a seating capacity of 9 or less) due in part to the cost of such systems relative to the asset value. This paper describes performance improvements to HUMS bearing diagnostics methodologies to enhance functionality and improve the business case for HUMS. From a system perspective, this implementation allowed the detection of a real-world turboshaft bearing fault prior to a catastrophic engine failure. The system requirements used vibration data that was resampled to control for changes in shaft rate to reduce smearing of the spectrum. A spectral estimation algorithm is then performed to improve the measured energy associated with the bearing defect. Bearing energy was calculated using the envelope analysis, where a novel approach is taken to correctly select the best window. Finally, a process for thresholding and alerting was implemented, the results being that the aircraft was grounded at the appropriate time and a repair was effectuated prior to engine failure.