The reliability investigation considering data uncertainty; an application of Fuzzy Transformation Method in substation protection

Sensitivity analysis with MC simulation for the failure rate evaluation and reliability assessment

“…In addition to the example of data from field above mentioned, in a complex system as a process or plant other sources of uncertainty affect input data can be considered such as measurement errors for sensor wear or fault, poor information about equipment installation and work environment, environmental condition of use, maintenance activities, partial understanding of the driving forces and mechanisms, and so on [13][14][15][16][17][18][19]. Considering the incomplete knowledge of data, often acquired by fieldfield data of service as, for instance, maintenance information or failure informationor collected in database, and different sources of uncertainty, it is fundamental to identify model inputs that cause significant uncertainty in the output.…”

“…Best-fitting distribution in the six cases under analysis is lognormal (13) and gamma (14) distribution: Also in this case, the reliability function is considered with yearly frequency until sixth year to evaluate the evolution of the confidence interval.…”