Title :
Fault detection and diagnosis using fuzzy models
Author :
Mendonca, L.F. ; Sa da Costa, J.M.G. ; Sousa, J.M.
Author_Institution :
Technical University of Lisbon, Instituto Superior Técnico, Dept. of Mechanical Engineering, GCAR/IDMEC, Av. Rovisco Pais, 1049-001 Lisbon, Portugal
Abstract :
The inherent characteristics of fuzzy logic theory makes it suitable for fault detection and diagnosis (FDI). Fault detection can benefit from nonlinear fuzzy modeling and fault diagnosis can profit from a transparent reasoning system, which can embed operator experience, but also learn from experimental and/or simulation data. Thus, fuzzy logic-based diagnostic is advantageous since it allows the incorporation of a-priori knowledge and lets the user understand the inference of the system. In this paper, the successful use of a fuzzy FDI based system, based on dynamic fuzzy models for fault detection and diagnosis of an industrial servo-actuated valve is presented. Only real plant data is used for the design and validation of the fuzzy FDI system. The validation results show the effectiveness of this approach.
Keywords :
Adaptation models; Data models; Fault detection; Fault diagnosis; Mathematical model; Observers; Valves; Fault detection; fault diagnosis; fuzzy modeling; fuzzy observers; model-based fault diagnosis;
Conference_Titel :
European Control Conference (ECC), 2003
Conference_Location :
Cambridge, UK
Print_ISBN :
978-3-9524173-7-9
