Adaptive Bearings Vibration Modelling for Diagnosis
نویسندگان
چکیده
An adaptive algorithm for vibration signal modeling is proposed in the paper. The aim of the signal processing is to detect the impact signals (shocks) related to damages in rolling element bearings (REB). Damage in the REB may result in cyclic impulsive disturbance in the signal, however they are usually completely masked by the noise. Moreover, impulses may have amplitudes that vary in time due to changes transmission path, load and properties of the noise. Thus, the solution should be an adaptive one. The proposed approach is based on the normalized exact least-square time-variant lattice filter (adaptive Schur filter). It is characterized by an extremely fast start-up performance, an excellent convergence behavior, and a fast parameter tracking capability and make this approach interesting. The method is well-adapted for analysis of the non-stationary time-series, so it seems to be very promising for diagnostics of machines working in time varying load/speed conditions.
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