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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Fault parameter identification in rotating system: Comparison between deterministic and stochastic approaches

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Author(s):
Garoli, Gabriel Yuji [1] ; Alves, Diogo Stuani [1] ; Machado, Tiago Henrique [1] ; Cavalca, Katia Lucchesi [1] ; de Castro, Helio Fiori [1]
Total Authors: 5
Affiliation:
[1] Univ Estadual Campinas, Sch Mech Engn, Rua Mendeleyev 200, BR-13083860 Campinas - Brazil
Total Affiliations: 1
Document type: Journal article
Source: STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL; v. 20, n. 6 JAN 2021.
Web of Science Citations: 1
Abstract

Fault identification is a recurrent topic in rotating machines field. The evaluation of fault parameters allows better maintenance of such expensive and, sometimes, large machines. Unbalance is one of the most common faults, and it is inherent to rotors functioning. Wear in journal bearings is another common fault, caused by several start/stop cycles - when at low rotating speed, there is still contact between shaft and bearing wall. Fault parameter identification generally uses deterministic model-based methods. However, these methods do not take into account the uncertainties inherently involved in the identification process. The stochastic approach by the Bayesian inference is, then, used to account the uncertainties of the fault parameters. The generalized polynomial chaos expansion is proposed to evaluate the inference, due to its faster performance regarding the Markov chain Monte Carlo methods. Deterministic and stochastic approaches were compared; all were based on experimental vibration measurements of the shaft inside the journal bearings. The Bayesian inference with the polynomial chaos showed reliable and promising results for identification of unbalance and bearing wear fault parameters. (AU)

FAPESP's process: 18/24600-0 - Experimental evaluation of a fault model for wear in hydrodynamic bearings
Grantee:Diogo Stuani Alves
Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
FAPESP's process: 18/21581-5 - Experimental evaluation of a fault model for wear in hydrodynamic bearings.
Grantee:Diogo Stuani Alves
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 15/20363-6 - Fault tolerant identification and control of rotating systems
Grantee:Katia Lucchesi Cavalca Dedini
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 16/13223-6 - Uncertainty estimation and quantification applied to fault models of rotating machines
Grantee:Gabriel Yuji Garoli
Support Opportunities: Scholarships in Brazil - Doctorate (Direct)