Joint Estimation of Additive and Parametric Faults: A Model-Based Fault Diagnosis Approach towards Predictive Maintenance

Koen Classens (Corresponding author), Stan Verbeek, W.P.M.H. Heemels, Tom Oomen

Onderzoeksoutput: Bijdrage aan tijdschriftCongresartikelpeer review

3 Citaten (Scopus)
39 Downloads (Pure)

Samenvatting

The condition of systems, such as production equipment, typically deteriorates over time, increasing the risk of failure and associated unscheduled downtime. Predictive maintenance is a strategy to prevent failure, while maximizing the life cycle of equipment within a system. This paper contributes in this context to the theory of real-time fault diagnosis with an approach that can jointly estimate additive and parametric faults. The proposed fault diagnosis system consists of detection filters which are complemented with a residual evaluator, enabling effective fault isolation and fault estimation for open-loop and closed-loop controlled systems. The effectiveness of this unified approach is illustrated on a mass-spring-damper system.

Originele taal-2Engels
Pagina's (van-tot)304-309
Aantal pagina's6
TijdschriftIFAC-PapersOnLine
Volume55
Nummer van het tijdschrift6
DOI's
StatusGepubliceerd - 29 jul. 2022
Evenement11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2022 - Pafos, Cyprus
Duur: 8 jun. 202210 jun. 2022

Bibliografische nota

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© 2022 Elsevier B.V.. All rights reserved.

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