Abstract
As dynamics has been significant characteristics of modern systems, many dynamic reliability analysis methods are studied, such as Markov method and dynamic Bayesian network. Among these existing methods, generalized stochastic Petri net (GSPN) has an excellent ability of characterizing the dynamic behaviors of systems, but because of its poor computing capability it can only be applied to simple system reliability analysis. Monte Carlo simulation method is powerful in computing, but it has no ability to model system dynamic behavior intuitively. In view of the fact that both GSPN and Monte Carlo method have a potential of making up the disadvantage of each other, this paper proposes a dynamic reliability analysis methodology by the combination of these two methods. Specifically, the paper defines a new GSPN for modeling dynamic systems. Afterwards, a simulation algorithm for analyzing the new GSPN is developed based on the Monte Carlo theory. Finally, the correctness and effectiveness of the proposed methodology is validated with a dynamic electromechanical system, which is analyzed by using the new proposed method and traditional Markov method, separately.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
