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Definition and bayes estimation of stochastic safety index: application to cable-way point (Articolo in rivista)
- Type
- Label
- Definition and bayes estimation of stochastic safety index: application to cable-way point (Articolo in rivista) (literal)
- Anno
- 2003-01-01T00:00:00+01:00 (literal)
- Alternative label
Vittorio Cecconi, Elio Chiodo, Maurizio Cirrincione, Marcello Pucci (2003)
Definition and bayes estimation of stochastic safety index: application to cable-way point
in International journal of engineering intelligent systems for electrical engineering and communications (1997)
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- Vittorio Cecconi, Elio Chiodo, Maurizio Cirrincione, Marcello Pucci (literal)
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- Le misure sono state effettuate sull'impianto di trasposto a fune in dotatazione alla sezione di Palermo dell'ISSIA (literal)
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- ISSIA-CNR, uos di Palermo
Università di Palermo
Università di Napoli, Federico II (literal)
- Titolo
- Definition and bayes estimation of stochastic safety index: application to cable-way point (literal)
- Abstract
- The aim of the paper is to define a probabilistic methodology for the definition of a stochastic safety index, and to show a possi- ble estimation method based upon Bayesian inference. As an important application of the proposed methodology, the attention is focused upon cable-way plant design. Actually the probabilistic methodologies, already applied to the generic fields of elec- trical power and control systems, which are themselves important parts of a modern cable-way plant, can be applied to the planning of the mechanical part of the system, thus permitting the design of the whole system on stochastic criteria. Researchers of the Universities of Naples and Palermo and of CE.RI. S.E.P. - C.N.R. (Research Centre on Power Electrical Systems) of Paler- mo have realised a cable-way plant, situated at the Department of Electrical Engineering of the University of Palermo, to obtain real-world measurements during the plant management. This paper presents and discusses the results of a first series of experi- mental tests for system safety evaluation. For this purpose, a stochastic index for the braking system is first presented and dis- cussed; then, its Bayesian estimation is developed and its feasibility and efficiency shown, with reference to field data and extensive Monte Carlo Simulation. Finally, studies on the robustness of the estimate have been performed with excellent results. (literal)
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