Fault Diagnosis and Failure Mode Estimation by a Data-Driven Fuzzy Similarity Approach
Volume 8, Number 1, January 2012 - Paper 4 - pp. 49-65
ENRICO ZIO1,2, and FRANCESCO DI MAIO11 Energy Department, Polytechnic of Milan, Via Ponzio 34/3, 20133 Milano, Italy
2 Ecole Centrale de Paris and Supelec, Grande Voie des Vignes, 92295 Chatenay-Malabry Cedex, France
(Received on December 10, 2010, and revised on September 06, 2011)
In the present work, a data-driven fuzzy similarity approach is proposed to assist the operators in fault diagnosis tasks. The approach allows: i) prediction of the Recovery Time (RT), i.e., the time remaining until the system can no longer perform its function in an irreversible manner, ii) Fault Diagnosis (FD), i.e., the identification of the component faults and iii) estimation of the system Failure Mode (FM), i.e., the system-level outcome of the failure scenario. The approach is illustrated by way of the analysis of failure scenarios in the Lead Bismuth Eutectic eXperimental Accelerator Driven System (LBE-XADS).
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