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针对多状态系统可靠性评估中存在的不确定性问题,研究了采用云模型表示状态概率的随机不确定性和认知不确定性的多状态系统可靠性评估方法。基于状态概率云模型进一步扩展了通用生成函数(Universal Generating Function,UGF),形成了云通用生成函数(Cloud Universal Generating Function,CUGF),并定义了其2种基本运算,给出了在给定需求下多状态系统可用度的求解步骤以及云模型表示系统可用度的3个云数字特征。最后,通过3单元串-并联多状态系统算例及其与基于概率理论的评估结果的比较,验证了方法的准确性和可行性。研究成果为多状态系统可靠性评估中信息或数据的不完整性、不精确性及模糊性等的处理提供了新的思路和方法。
Aiming at the problem of uncertainty in multi-state system reliability assessment, a multi-state system reliability evaluation method based on stochastic uncertainty and cognitive uncertainty is proposed. Based on the state-probabilistic cloud model, Universal Generating Function (UGF) is further extended to form Cloud Universal Generating Function (CUGF). Two basic operations are defined, The solving procedure for the availability of multi-state systems, and the three cloud digital characteristics of the cloud model that indicate the availability of the system. Finally, the accuracy and feasibility of the proposed method are verified by comparing the three-cell series-parallel multi-state system and its comparison with the evaluation results based on probability theory. The research results provide new ideas and methods for the processing of the incompleteness, inaccuracy and fuzziness of information or data in the reliability assessment of multi-state systems.