Fault isolation based on HSFNN applied to DAMADICS benchmark problem

Calado, João Manuel FerreiraLouro, R.Mendes, Mário J. G. C.Costa, J. M. G. Sá daKowal, M.2020-01-022020-01-022003-06CALADO, João M. F. [et al] – Fault Isolation based on HSFNN applied to DAMADICS Benchmark Problem. IFAC Proceedings Volumes. ISSN 2589-3653. Vol. 36, N.º 5 (2003), pp. 951-9562589-3653http://hdl.handle.net/10400.21/10924The present paper is concemed with the application of a hierarchical structure of fuzzy newal networks (HSFNN) to fault isolation on a pneumatic servo-motor actuated valve that is the benchmark considered for all the DAMADICS (Development and Application of Methods for Actuator Diagnosis in IndusIrial Control Systems) project partners. The adoption of a hierarchical structure of fuzzy newal netwoIks for fault isolation pwposes aims the development of an architecture that can localise abrupt and incipient single and multiple faults correctly or at least with a minimum misclassification rate and be easily trained, ftom only single abrupt fault symptoms.engFault isolationHierarchical structuresNeural networksFuzzy systemsActuatorsFault isolation based on HSFNN applied to DAMADICS benchmark problemjournal articlehttps://doi.org/10.1016/S1474-6670(17)36615-6