Bivariate analysis of complex vibration data: An application to condition monitoring of rotating machinery

• Published in: Mechanical systems and signal processing Vol. 20; no. 8; pp. 2340 - 2374
• Main Authors: Pennacchi, P., Vania, A., Bachschmid, N.
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 01.11.2006; Elsevier
• Subjects: Acceptance regions; Applied sciences; Bivariate analysis of data; Condition monitoring; Data depth; Drives; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Measurement and testing methods; Mechanical engineering. Machine design; Physics; Robust estimation; Rotor dynamics; Shafts, couplings, clutches, brakes; Solid mechanics; Structural and continuum mechanics; Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...); Condition monitoring; Rotor dynamics; Robust estimation; Bivariate analysis of data; Data depth; Acceptance regions; Measurement; Data analysis; Electric power plant; Vibration; Rotating machine; Statistical method; Shaft; Signal processing; Robustness; Monitoring; Structural analysis
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2005.05.008

The problem of the robust definition of the acceptance regions in condition monitoring of the vibrations of rotating machinery is related to the more wide field of the analysis of bivariate data. Traditional parametric techniques and innovative nonparametric methods based on the statistical concept of the data depth are presented and critically examined in the paper. The performances with respect to the robustness in the estimation of the acceptance regions are analysed by means of experimental cases of real rotating machinery of a power plant.