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EN
Owing to expensive cost and restricted structure, limited sensors are allowed to install in modern systems to monitor the working state, which can improve their availability. Therefore, an effective sensor placement method is presented based on a VIKOR algorithm considering common cause failure (CCF) under epistemic uncertainty in this paper. Specifically, a dynamic fault tree (DFT) is developed to build a fault model to simulate dynamic fault behaviors and some reliability indices are calculated using a dynamic evidence network (DEN). Furthermore, a VIKOR method is proposed to choose the possible sensor locations based on these indices. Besides, a sensor model is introduced by using a priority AND gate (PAND) to describe the failure sequence between a sensor and a component. All placement schemes can be enumerated when the number of sensors is given, and the largest system reliability is the best alternative among the placement schemes. Finally, a case study shows that CCF has some influence on sensor placement and cannot be neglected in the reliabilitybased sensor placement.
EN
Quality control generally requires data of higher quality to quantify the error in any measured quantity. The following work shows that the Proszyhski Reliability Criterion (PRC) is fulfilled if the measurement variance is greater than its prediction function based on the remaining observations. The partial derivatives with respect to the parameters of the residuals' equations are taking the role of the observations within the system. Therefore the prediction variance can be measured. If the prediction function is bounded then a reliable observational system (i.e. each observation has fulfilled the PRC) can be achieved.
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