Development of an Effective Strategy for Prognostic Monitoring of a Large Centrifugal Air Compressor in an Automotive Plant
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Abstract
Prognostic monitoring of health condition of a large centrifugal air compressor that supplies compressed air in an automotive plant is crucial because its failure will seriously impair operation of the entire plant. It was desired to
develop an effective prognostic maintenance methodology of air compressors after the failure of an air compressor in one of major automotive companies in US, which brought a highly undesirable situation to the manufacturing line of the plant. In this work, the shaft motion of the compressor measured at transient and steady-state conditions were used to develop techniques and a strategy for effective prognostic monitoring. The pseudo frequency response function (FRF) obtained from the Campbell diagram and directional Power Spectrum (dPS) were new techniques employed to develop the prognostic health monitoring strategy. The analytic wavelet transform (AWT) is adopted to monitor temporal change of the system characteristics during the start-up period. In addition, AWT was utilized to monitor the steady state condition.
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PHM
Gómez-Mancilla, J., Sinou, J.-J., Nosov, V. R., Thouverez, F., & Zambrano, A. (2004). The influence of crackimbalance orientation and orbital evolution for an extended cracked Jeffcott rotor. Comptes Rendus Mécanique, 332(12), 955–962. https://doi.org/10.1016/j.crme.2004.09.007
Kim, H. (2006). Development of a Prognosis Method for Journal Bearing Failures in Centrifugal Air Compressor. University of Cincinnati, OH.
Lee, C.-W., Han, Y.-S., & Park, J.-P. (1997). Use of Directional Spectra for Detection of Engine Cylinder Power Fault. Shock and Vibration, 4(5–6), 391–401. https://doi.org/10.3233/SAV-1997-4401
Lee, C., & Han, Y. (n.d.). Directional spectrum analysis and its applications to rotating machine diagnosis.
Mallat, S. (1998). A Wavelet Tour of Signal Processing. San Diego: Academic Press.
Qiu, H., Lee, J., Lin, J., & Yu, G. (2006). Wavelet filterbased weak signature detection method and its application on rolling element bearing prognostics. Journal of Sound and Vibration, 289(4–5), 1066–1090. https://doi.org/10.1016/j.jsv.2005.03.007
Singhal, S., & Khonsari, M. M. (2005). A simplified thermohydrodynamic stability analysis of journal bearings. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 219(3), 225–234.
https://doi.org/https://doi.org/10.1243/135065005X33874
Tiwari, R., Lees, A. W., & Friswell, M. I. (2002). Identification of Speed-Dependent Bearing Parameters. Journal of Sound and Vibration, 254(5), 967–986. https://doi.org/10.1006/jsvi.2001.4140
Wan, F., Xu, Q., & Li, S. (2004). Vibration analysis of cracked rotor sliding bearing system with rotor–stator rubbing by harmonic wavelet transform. Journal of Sound and Vibration, 271(3–5), 507–518. https://doi.org/10.1016/S0022-460X(03)00277-3
Zhu, X., & Kim, J. (2006). Application of analytic wavelet transform to analysis of highly impulsive noises. Journal of Sound and Vibration, 294(4–5), 841–855. https://doi.org/10.1016/j.jsv.2005.12.034