考虑多种故障状态的机械系统可靠性评估方法研究

RESEARCH ON RELIABILITY ASSESSMENT METHOD OF MECHANICAL SYSTEM CONSIDERING MULTIPLE FAILURE STATES

为解决传统可靠性分析方法在多状态且难以获得精确故障率的机械系统可靠性评估中的不足,以及T-S故障树存在计算复杂、不能逆向推理等问题,提出一种将T-S故障树和区间模糊多态贝叶斯网络相结合的系统可靠性评估方法。将T-S故障树映射成贝叶斯网络,在模糊贝叶斯网络可靠性分析方法中引入区间理论,对模糊子集边界值进行模糊化处理,构建区间三角模糊贝叶斯网络,结合区间模糊子集和贝叶斯网络处理不确定性因素的能力,在仅知根节点故障状态下,得到叶节点故障子集、根节点区间模糊重要度和后验概率的求解算法。最后,利用该方法对巷道堆垛机伸缩传动系统进行了可靠性评估,验证了该方法能准确有效地识别多故障状态系统的薄弱环节,为维修与诊断提供指导。

In order to solve the limitations of traditional methods in the reliability assessment of complex systems with multi-states and difficult to obtain accurate failure rates, and the problems of T-S fault tree in the system reliability analysis, such as complex calculation and inverse reasoning, etc., a reliability assessment method based on T-S fault tree and interval-valued fuzzy multi-state Bayesian network is proposed. Based on the analysis of the T-S fault tree, it is mapped into a Bayesian network. In the existing fuzzy Bayesian network reliability analysis method, the interval variable is introduced. Fuzzy processing is carried out to construct an interval-valued triangular fuzzy Bayesian network. Combining the characteristics of interval fuzzy subsets and Bayesian networks, a solution algorithm for leaf node failure probability, interval fuzzy importance, and interval fuzzy posterior probability is obtained under the condition of knowing only the root node failure status. Finally, the method is used to evaluate the reliability of the expansion system of the tunnel stacker, and it is verified that this method can accurately and effectively identify the weak links of the polymorphic system, and provide guidance for maintenance and diagnosis.