A Comparison of Signal Analysis Techniques for the Diagnostics of the IMS Rolling Element Bearing Dataset

In this paper, a comparison of signal analysis techniques for the diagnostics rolling element bearings is carried out. Specifically, performed in terms fault detection, diagnosis and prognosis with regards to first bearing dataset released by NASA IMS Center 2014. As it obtained that RMS value, Kurtosis Detectivity, as statistical parameters, are able properly detect arising on defective bearings. Then, several processing techniques, such deterministic/random separation, time-frequency cyclostationary analyses applied perform diagnosis. Among these found combination Cepstrum Pre-Whitening Squared Envelope Spectrum, Improved allow faults be correctly identified specific components. Finally, Correlation, Monotonicity Robustness previous parameters computed identify most accurate tools prognosis.