Hybrid Universal Generating Function for the Reliability Assessment of Multi-State Systems under Aleatory and Epistemic Uncertainties

Yan-Fu Li (1) , Y. Ding (2) , Enrico Zio (1)

1 SSEC - Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec
2 Department of Electrical Engineering

In this work, we extend the traditional universal generating function (UGF) approach for multi-state system (MSS) reliability assessment to account for both aleatory and epistemic uncertainties. Firstly, a theoretical extension, named hybrid UGF (HUGF), is made to introduce the use of random fuzzy variables (RFVs) in the approach; secondly, the composition operator of HUGF is defined by considering simultaneously the probabilistic convolution and the fuzzy extension principle; finally, an efficient algorithm is designed to extract probability boxes (p-boxes) from the system HUGF, which allow quantifying different levels of imprecision in system reliability estimation. The HUGF approach is demonstrated on a numerical example.

Domaines: Sciences de l'ingénieur [physics]

Yan-Fu Li, Y. Ding, Enrico Zio. Hybrid Universal Generating Function for the Reliability Assessment of Multi-State Systems under Aleatory and Epistemic Uncertainties. ESREL 2013, Sep 2013, Amsterdam, Netherlands. pp.1-8. ⟨hal-00911991⟩