Int J Performability Eng ›› 2012, Vol. 8 ›› Issue (1): 49-65.doi: 10.23940/ijpe.12.1.p49.mag
• Original articles •
ENRICO ZIO1,2 and FRANCESCO DI MAIO1
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).
ENRICO ZIO and FRANCESCO DI MAIO. Fault Diagnosis and Failure Mode Estimation by a Data-Driven Fuzzy Similarity Approach [J]. Int J Performability Eng, 2012, 8(1): 49-65.
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