Please use this identifier to cite or link to this item: http://hdl.handle.net/10362/76241
Title: Vibration analysis based on HJ-biplots
Author: Vairinhos, Valter
Parreira, Rui
Lampreia, Suzana
Lobo, Vítor
Galindo, Purificación
Keywords: CBM
Vibration analysis
Interpretation
sensor
Biplot
periodogram
observational data
Computer Science (miscellaneous)
Civil and Structural Engineering
Safety, Risk, Reliability and Quality
Energy Engineering and Power Technology
Mechanical Engineering
Issue Date: 1-Jan-2018
Abstract: Vibration Analysis (VA) is now routinely used for condition monitoring and failure diagnosis in Condition Based Maintenance (CBM). In the context of VA, a methodology is proposed, based on biplots, to simultaneously display both vibration frequencies and their measurement points, in support of monitoring and diagnostics tasks. In this research, real observational data obtained measuring mechanical vibrations on four generators aboard a Portuguese Navy Ship in real operating conditions is used. A portable vibration collector was employed, and the measurements were taken at 13 measurement points in each one of four generators, using the same collector settings. Spectrograms resulting from vibration measurements were transformed into biplots and used for decision support according to the proposed methodology. Data analysis showed a robust stability in the macrostructure of biplots when observations resulting from different generators of the same model and at the same assumed conditions was analyzed. This invariance allows the specification of reference conditions, rules to detect changes of operating conditions and the emergence of failures. The proposed methodology, once embedded in dedicated software, will reduce the interpretation error in diagnosis and prognosis associated to variability in personnel training and experience. Consequently, it will increase the safe use of VA in an increasing number of situations.
Description: Vairinhos, V., Parreira, R., Lampreia, S., Lobo, V., & Galindo, P. (2018). Vibration analysis based on HJ-biplots. International Journal of Prognostics and Health Management, 9(2), [030].
Peer review: yes
URI: http://www.scopus.com/inward/record.url?scp=85068446463&partnerID=8YFLogxK
DOI: https://doi.org/10.36001/ijphm.2018.v9i2.2739
ISSN: 2153-2648
Appears in Collections:NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)

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