Fault monitoring in complex dynamic system by utilization statistical analysis technique | ||
| The International Conference on Applied Mechanics and Mechanical Engineering | ||
| Article 13, Volume 12, 12th International Conference on Applied Mechanics and Mechanical Engineering., May 2006, Pages 643-658 PDF (5.18 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/amme.2006.41681 | ||
| Author | ||
| Gomaa F. R. | ||
| Assistant Professor, Department of Production Engineering and Mechanical Design, Faculty of engineering, Shebin El-Kom, Egypt. | ||
| Abstract | ||
| ABSTRACT: Vibration monitoring is widely accepted defects in rotating machinery components using traditional diagnostic analysis to match spectral line with known defect frequencies that are characteristics of the affected machinery components. The present work highlights the accurate fault defect, higher order spectrum analysis (HOSA) in rotating machinery and focus on the rare failure due nonlinearity based on compound mode which cannot appear in traditional diagnostics. And compare the results of the traditional linear spectra analysis in the case of fault monitoring of experimental tests carried out on eccentric cam in a specially designed cam dynamic test fixture. The test performed on the complex system, the cam is excited by impact hammer. An accelerometer is used to measure the acceleration response for different manufacturing routes of cams. The ambient excitation and the system response are used to compute a number of quantities for the system under two operating conditions of surface finish. In particular the power spectrum density (PSD), the frequency response function (FRF), the second order coherence function and the third order system bicoherence are measured and calculated. The measurements are compared and the results are discussed. The results shows that the nonlinearity due to compound mode cannot appear in linear spectra analysis. The results shows also that the traditional linear spectra analysis is of limited value in monitoring faults. | ||
| Keywords | ||
| Vibration monitoring; Feature selection of damage; Detect nonlinear behavior and high order spectrum analysis | ||
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