Evaluation of Cepstrum Algorithm with Impact Seeded Fault Data of Helicopter Oil Cooler Fan Bearings and Machine Fault Simulator Data.

摘要

This report documents the evaluation of the cepstrum algorithm with seeded fault data for oil cooler fan bearings from the Impact Technologies, LLC, and Machine Fault Simulator (MFS) bearing data collected at the U.S. Army Research Laboratory (ARL). The Impact data collection was part of the Air Vehicle Diagnostic and Prognostic Improvement Program (AVDPIP), which was a three-year collaborative agreement between Impact Technologies, LLC, the Georgia Institute of Technology, and ARL. In this report, we describe the two types of data Impact and MFS. The results of those data sets using the cepstrum algorithm are presented. It shows that under the control environment (laboratory) with not much surrounding interference, the cepstrum algorithm can clearly estimate fault frequencies such as inner race and outer race frequencies. Otherwise, the algorithm does not clearly identify other fault frequencies of rolling element bearings.