In the field of vibration based condition monitoring a trusted symptom of a defective bearing is the observation of peaks, at characteristic frequencies, in the squared envelope spectrum (SES). If a machine is operating in a varying speed regime the SES is computed on the order tracked signal, i.e. the signal resampled at constant angular increments, and the SES can still be used for diagnostic. Despite its versatility a common problem with the SES is that peaks from other sources of vibrations, as for instance gears, can prevent the diagnosis of a defective bearing. Therefore pre-processing techniques are applied to the vibrational signal before the computation of the SES to enhance the signal from the bearings. Among these techniques cepstral prewhitening (CPW) has gained much attention oering a remarkable capability of eliminating, in a blind way, both harmonics and modulation side-bands of the unwanted components. In the case of a varying speed regime the usual procedure consists of three steps: order track the signal, calculate the CPW, evaluate the SES. In this paper on the contrary the CPW is applied before the step of order tracking; therefore the proposed approach is: CPW the raw time signal, order tracking, evaluation of the SES. The remarkable observation is that for this approach the cepstrum does not present peaks at characteristic quefrencies, being the raw signal acquired in a varying speed regime. However this paper shows by means of numerical simulations and analysis of experimental data, that with the proposed methodology the masking components coming from the gears are suppressed and the signal from the defective bearing is enhanced.
|Publication status||Published - 12 Sep 2016|
|Event||International Congress on Technical Diagnostics and Condition Monitoring of Machinery in Non-Stationary Operations - Gliwice, Poland|
Duration: 12 Sep 2016 → 16 Sep 2016
Conference number: 5
|Conference||International Congress on Technical Diagnostics and Condition Monitoring of Machinery in Non-Stationary Operations|
|Abbreviated title||ICTD CMMNO|
|Period||12/09/16 → 16/09/16|