The Application of Time-Frequency Methods to HUMSThis paper reports the study of four time-frequency transforms applied to vibration signals and presents a new metric for comparing them for fault detection. The four methods to be described and compared are the Short Time Frequency Transform (STFT), the Choi-Williams Distribution (WV-CW), the Continuous Wavelet Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel gear tooth fatigue cracks, under a variety of operating load levels, are analyzed using these methods. The new metric for automatic fault detection is developed and can be produced from any systematic numerical representation of the vibration signals. This new metric reveals indications of gear damage with all of the methods on this data set. Analysis with the CWT detects mechanical problems with the test rig not found with the other transforms. The WV-CW and CWT use considerably more resources than the STFT and the DWT. More testing of the new metric is needed to determine its value for automatic fault detection and to develop methods of setting the threshold for the metric.
Document ID
20010048426
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Pryor, Anna H. (NASA Ames Research Center Moffett Field, CA United States)
Mosher, Marianne (NASA Ames Research Center Moffett Field, CA United States)
Lewicki, David G. (Army Research Lab. Cleveland, OH United States)
Norvig, Peter
Date Acquired
August 20, 2013
Publication Date
January 1, 2001
Subject Category
Quality Assurance And Reliability
Meeting Information
Meeting: AHS 57th Annual Forum and Technology Display