Actuator Fault Diagnosis Using Single and Meta-Classification Strategies

Abstract : The paper presents the application of various classification schemes for actuator fault diagnosis in industrial systems. The main objective of this study is to compare either single or meta-classification strategies that can be successfully used as reasoning means in the diagnostic expert system that is realized within the frame of the DISESOR project. The applied research was conducted on the assumption that classic as well as soft computing classification methods would be adopted. The comparison study was carried out within the DAMADICS benchmark problem which provides a popular framework for confronting different approaches in the development of fault diagnosis systems.
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Communication dans un congrès
Danielle Boulanger; Eunika Mercier-Laurent; Mieczysław Lech Owoc. 2nd IFIP International Workshop on Artificial Intelligence for Knowledge Management (AI4KM), Sep 2014, Warsaw, Poland. IFIP Advances in Information and Communication Technology, AICT-469, pp.132-149, 2015, Artificial Intelligence for Knowledge Management. 〈10.1007/978-3-319-28868-0_8〉
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Mateusz Kalisch, Piotr Przystałka, Anna Timofiejczuk. Actuator Fault Diagnosis Using Single and Meta-Classification Strategies. Danielle Boulanger; Eunika Mercier-Laurent; Mieczysław Lech Owoc. 2nd IFIP International Workshop on Artificial Intelligence for Knowledge Management (AI4KM), Sep 2014, Warsaw, Poland. IFIP Advances in Information and Communication Technology, AICT-469, pp.132-149, 2015, Artificial Intelligence for Knowledge Management. 〈10.1007/978-3-319-28868-0_8〉. 〈hal-01369808〉

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