Abstract: In view of the complexity and uncertainty of system, both the state performances and state probabilities of multi-state components can be expressed by interval numbers. The belief function theory is used to characterize the uncertainty caused by various factors. A modified Markov model is proposed to obtain the state probabilities of components at any given moment and subsequently the mass function is used to represent the precise belief degree of state probabilities. Based on the primary studies of universal generating function (UGF) method, a belief UGF (BUGF) method is utilized to analyze the reliability and the uncertainty of excavator rectifier feedback system. This paper provides an available method to evaluate the reliability of multi-state systems (MSSs) with interval state performances and state probabilities, and also avoid the interval expansion problem.

Key words: excavator rectifier feedback system| multi-state components| Markov model| belief universal generating function

摘要： In view of the complexity and uncertainty of system, both the state performances and state probabilities of multi-state components can be expressed by interval numbers. The belief function theory is used to characterize the uncertainty caused by various factors. A modified Markov model is proposed to obtain the state probabilities of components at any given moment and subsequently the mass function is used to represent the precise belief degree of state probabilities. Based on the primary studies of universal generating function (UGF) method, a belief UGF (BUGF) method is utilized to analyze the reliability and the uncertainty of excavator rectifier feedback system. This paper provides an available method to evaluate the reliability of multi-state systems (MSSs) with interval state performances and state probabilities, and also avoid the interval expansion problem.

关键词: excavator rectifier feedback system| multi-state components| Markov model| belief universal generating function