Wavelet-Based Hölder Regularity Analysis in Condition Monitoring
Vesa Kotila, Sulo Lahdelma, K. Ruotsalainen · Birkhäuser Boston eBooks · 2009
Condition monitoring is becoming more and more important in various areas of industry, due to the demands of efficiency and prolonged continuous running time of machinery. For example, in the Finnish pulp industry there have been demands for continuous running times of up to 18 months. To be cost efficient, maintenance operations should be carried out during scheduled downtime; hence, early and reliable fault detection is very important. Vibration measurements have been the central tool in condition monitoring. Signals from displacement, velocity, and acceleration sensors have been used to estimate the condition of the machinery. For example, increased rootmean- square (RMS) values or changes in the frequency spectrum may indicate different types of faults, such as unbalance, misalignment, and bearing defects. In rolling element bearings, a local fault on the raceways or on the rolling elements causes wideband bursts in the vibration signal measured from the bearing house. When the fault is on the inner race, the time interval between the bursts corresponds to the shaft frequency. If the shaft is rotating slowly, as in pulp washers, these bursts occur at long intervals and may be hard to detect from the frequency spectrum or the RMS value of the signal. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.