Joint Estimation of Additive and Parametric Faults: A Model-Based Fault Diagnosis Approach towards Predictive Maintenance. Issue 6 (2022)

• Record Type: Journal Article
• Authors: Classens, Koen; Verbeek, Stan; (Maurice) Heemels, W.P.M.H.; Oomen, Tom
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 6(2022)
• Page Start: 304
• Page End: 309
• Publication Date: 2022
• Subjects: Fault Diagnosis -- Fault Detection -- Fault Isolation -- Fault Estimation -- Predictive Maintenance -- Mechatronic Systems -- Production Equipment -- Linear Fractional Representation; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.07.146
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: 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.