A Prognostic Approach to the Resonance Failure Problem by Triple Sensing Technology

• Autorzy: Erol Salih Seçkin

Identyfikatory

DOI

10.24425/aoa.2020.133157

• Języki publikacji: EN

Abstrakty

EN

Within this study, resonance phenomenon, which is one of the crucial problems in mechanical constructions, has been analyzed with respect to oil starvation failure in a ball bearing. A unique test rig is designed, constructed, and placed in a laboratory ambience. A ball bearing on the electrical motor, which is a component of the test rig, has been selected for acquisition of data within triple sensing technology in vibration, acoustic, and electrical consumption through testing conditions. The target of that study is condition monitoring of oil starvation fault and resonance fault for comparison of various predictive maintenance methods. The testing was carried out within the electrical frequency of 40.5 Hz, which actuated the electrical motor in order to identify the rotation speed. According to the analyzed results, oil starvation fault and resonance fault is most accurately inspected by vibration analysis.

Słowa kluczowe

EN

oil starving; resonance; vibration; acoustic; electrical consumption

• Wydawca: Instytut Podstawowych Problemów Techniki PAN ; Komitet Akustyki PAN ; Polskie Towarzystwo Akustyczne
• Czasopismo: Archives of Acoustics
• Rocznik: 2020
• Tom: Vol. 45, No. 2
• Strony: 297--301
• Opis fizyczny: Bibliogr. 10 poz., tab., wykr.

Twórcy

autor

Erol Salih Seçkin

• Center for Advanced Life Cycle Engineering, University of Maryland, College Park, MD 20742 USA

Bibliografia

• 1. Acosta G. G., Verucchi C. J., Gelso E. R. (2006), A current monitoring system for diagnosing electrical failures in induction motors, Mechanical Systems and Signal Processing, 20 (4): 953-965, doi: 10.1016/j.ymssp.2004.10.001.
• 2. Ayo-Imoru R. M., Cilliers A. C. (2018), A survey of the state of condition-based maintenance (CBM) in the nuclear power industry, Annals of Nuclear Energy, 112: 177-188, doi: 10.1016/j.anucene.2017.10.010.
• 3. Collacott R. A. (1977), Mechanical fault diagnosis, p. 405, Chapman & Hall, London.
• 4. Er P. V., Tan K. K. (2018), Machine vibration analysis based on experimental modal analysis with radial basis functions, Measurement, 128: 45-54, doi: 10.1016/j.measurement.2018.06.013.
• 5. Erol S. S. (2016), A Research study on vibrating elements and consuming electricity in predictive maintenance, European Journal of Interdisciplinary Studies, 2 (3): 45-50, doi: 10.26417/ejis.v2i3-45-50.
• 6. Goodenow T., Hardman W., Karchnak M. (2000), Acoustic emissions in broadband vibration as an indicator of bearing stress, IEEE Aerospace Conference Proceedings, 6: 95-122, doi: 10.1109/AERO.2000.877886.
• 7. Hardman W., Hess A., Sheaffer A. (2000), A helicopter powertrain diagnostics and prognostics demonstration, IEEE Aerospace Conference Proceedings, 6: 355-366, doi: 10.1109/AERO.2000.877911.
• 8. Loukopoulos P. et al. (2019), Abrupt fault remaining useful life estimation using measurements from a reciprocating compressor valve failure, Mechanical Systems and Signal Processing, 121: 359-372, doi: 10.1016/j.ymssp.2018.09.033.
• 9. Velarde-Suarez S., Ballesteros-Tajadura R., Hurtado-Cruz J. P. (2006), A predictive maintenance procedure using pressure and acceleration signals from a centrifugal fan, Applied Acoustics, 67 (1): 49-61, doi: 10.1016/j.apacoust.2005.05.006.
• 10. Welz Z., Coble J., Upadhyaya B., Hines W. (2017), Maintenance-based prognostics of nuclear plant equipment for long-term operation, Nuclear Engineering and Technology, 49 (5): 914-919, doi: 10.1016/j.net.2017.06.001.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).