基于平均互信息熵的复杂系统可靠性评定方法

可靠性评定是定量评估系统可靠性水平的重要途径,是对其可靠性进行定量控制的必要手段.某些复杂系统由于研制时间和经费的限制,现场试验样本量极其有限,依赖传统的基于大样本的数理统计方法将难以获得客观结论,因此其可靠性评定一直是工程实践中的技术难题.针对复杂系统可靠性评估和寿命预测时现场样本量不足的问题,提出了一种基于多源信息融合的可靠性评定方法.该方法利用平均互信息熵来度量多源验前信息对可靠性评定不确定性减少所起的作用,以此为依据确定多源信息融合权重,并通过融合验前分布进行复杂系统的可靠性评定,从而减少了评定过程中的主观性,增强了评定结论的可信性.最后通过仿真实例验证了方法的有效性.

Reliability assessment of complex system based on mean interactive entropy

Reliability assessment is an important way to evaluate the reliability of system,and it has been an essential way to control the reliability of system quantitatively.But there are some difficulties in achieving an objective result on reliability of complex system using the traditional way of statistics based on large samples due to time and cost.Thus,the reliability assessment of this kind of system has been a problem in reality.Considering the problem met in the reliability assessment and the life prediction for complex system,the reliability information fusion method based on mean interactive entropy is proposed.Based on mean interactive entropy,the weight of fusion was achieved,and the reliability of system was assessed by fusion of multiple prior distributions.By reducing uncertainty in the process,the new method increased the dependence of assessment and was less subjective.Finally,a simulation example was presented to illustrate the efficiency of the fusion method.