High-speed bearing diagnostics: Observations from the Surveillance 8 Safran contest data

Mechanical Systems and Signal Processing(2024)

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Abstract
It is usually assumed that faulty bearings produce second-order cyclostationary (CS2) signals, and thus the natural process for their diagnostic analysis involves first the removal of first-order cyclostationary (CS1) components, such as from gears, followed by amplitude demodulation of an ‘informative’ frequency band, and subsequent envelope analysis, in which the spectrum of the (squared) envelope is inspected for signs of a fault, typically manifesting as discrete frequency components at or near one of the expected fault frequencies, the latter calculated from basic kinematic relationships.However, recent theoretical research, supported by empirical evidence from the aero industry, has shown that bearing signals are in fact not purely CS2, but rather exhibit both CS1 and CS2 properties, dominant in the lower and higher frequency ranges, respectively, with the ‘crossover’ between these ranges proportional to machine speed. Thus, for high-speed bearings, where the frequency range available for analysis may span only a handful of fault frequency harmonics, the relative importance of CS1 signal content is far greater than for lower speed applications, and it can no longer be assumed that the envelope spectrum is the optimal diagnostic tool.These and other issues associated with high-speed bearing diagnostics are discussed in this paper, using as an example the aircraft engine data provided by Safran for the diagnostic contest at the 2015 Surveillance 8 Conference in Roanne, France. The objective of the paper is to guide the reader in the analysis of high-speed bearing signals, pointing out in particular the ways in which the required analysis techniques differ from the ‘conventional wisdom’ of the diagnostics field, most of which is based on more common, lower speed applications.
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Key words
Bearing diagnostics,Aero-engine monitoring,Cyclostationary analysis
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