A Semi-Classical Signal Analysis Method for the Analysis of Turbomachinery Flow Unsteadiness
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32807
A Semi-Classical Signal Analysis Method for the Analysis of Turbomachinery Flow Unsteadiness

Authors: Fadi Eleiwi, Taous Meriem Laleg-Kirati, Sofiane Khelladi, Farid Bakir

Abstract:

This paper presents the use of a semi-classical signal analysis method that has been developed recently for the analysis of turbomachinery flow unsteadiness. We will focus on the correlation between theSemi-Classical Signal Analysis parameters and some physical parameters in relation with turbomachinery features. To demonstrate the potential of the proposed approach, a static pressure signal issued from a rotor/stator interaction of a centrifugal pump is studied. Several configurations of the pump are compared.

Keywords: Semi-classical signal analysis, turbomachines, newindices, physical parameters

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075515

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1407

References:


[1] M. Cudina,"Detection of cavitation phenomenon in a centrifugal pump using audible sound". Mechanical Systems and Signal Processing 17(6), 1335{1347, 2003.
[2] T.M.Laleg-Kirati, E. Crépeau and M. Sorine "Semi-classical signal analysis," submitted for publication.
[3] T.M.Laleg-Kirati, C. Médigue, Y. Papelier, F. Cottin and A. Van de Louw, "Validation of a semi-classical signal analysis method for stroke volume variation assessment: A comparison with the PiCCO technique " Annals of biomedical engineering, vol. 38, no. 12, pp. 3618-3629, 2010.
[4] T. M. Laleg, C. Médigue, F. Cottin, and M. Sorine. "Arterial blood pressure analysis based on scattering transform II", in Proc. EMBC,Lyon, France, August 2007
[5] B. Helffer and T.M.Laleg-Kirati, "On semi-classical questions related to signal analysis," Asymptotic Analysis Journal, to be published.
[6] I. Howard,"A review of rolling element bearing vibration "detection, 290 diagnosis and prognosis. published by DSTO Aeronautical and Maritime Research Laboratory, 1994.
[7] Z.K. Peng and F.L. Chu, "Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography", Mechanical systems and signal processing, vol. 18, pp. 199-221, 2004.