Juan David Arango and Alejandro Restrepo-Martinez
Rolling Element Bearing Diagnosis by Improved Envelope Spectrum Optimal Frequency Band Selection
322 - 330
2021
15
8
International Journal of Mechanical and Mechatronics Engineering
https://publications.waset.org/pdf/10012159
https://publications.waset.org/vol/176
World Academy of Science, Engineering and Technology
The Rolling Element Bearing (REB) vibration diagnosis is worth of special interest by the variety of REB and the wide necessity of those elements in industrial applications. The presence of a localized fault in a REB gives rise to a vibrational response, characterized by the modulation of a carrier signal. Frequency content of carrier signal (Spectral Frequency –f) is mainly related to resonance frequencies of the REB. This carrier signal is modulated by another signal, governed by the periodicity of the fault impact (Cyclic Frequency –α). In this sense, REB fault vibration response gives rise to a secondorder cyclostationary signal. Second order cyclostationary signals could be represented in a bispectral map, where Spectral Coherence –SCoh are plotted against f and α. The Improved Envelope Spectrum –IES, is a useful approach to execute REB fault diagnosis. IES could be applied by the integration of SCoh over a predefined bandwidth on the f axis. Approaches to select fbandwidth have been recently exposed by the definition of a metric which intends to evaluate the magnitude of the IES at the fault characteristics frequencies. This metric is represented in a 13binary tree as a function of the frequency bandwidth and centre. Based on this binary tree the optimal frequency band is selected. However, some advantages have been seen if the metric is changed, which in fact tends to dictate different optimal fbandwidth and so improve the IES representation. This paper evaluates the behaviour of the IES from a different metric optimization. This metric is based on the sample correlation coefficient, detecting high peaks in the selected frequencies while penalizing high peaks in the neighbours of the selected frequencies. Prior results indicate an improvement on the signalnoise ratio (SNR) on around 86 of samples analysed, which belong to IMS database.
Open Science Index 176, 2021