Diagnosing Rotating Machinery Using Spectral Distribution Functions

A method for detecting and characterizing faults in a rotating machine involves analysis of selected aspects of the evolution of the spectral distribution function (SDF) of its vibrations. The method is based on the proposition that long-term accumulation of damage (e.g., bearing wear or spalling of gear teeth) is accompanied by long-term changes in the SDF, and that these changes are revealed as differences among SDFs computed from short-observation-time vibration data. Data displays produced according to older vibration-analysis methods, including methods based on the conventional power spectral density (PSD), tend to display large components of random noise and other artifacts that often make interpretation difficult. The present method based on the SDF gives more robust indications of changes, yet entails little more computation than do methods based on the conventional PSD.