摘要
用模糊数描述节点的多种故障状态,用模糊子集描述根节点的故障概率,用贝叶斯网络的条件概率表描述节点间的不确定关系,构建数控机床故障的模糊贝叶斯网络;采用桶消元算法,对数控机床故障的模糊贝叶斯网络进行推理和计算,获得根节点的后验概率,为数控机床故障诊断与分析提供依据;最后,以数控机床刀架系统故障的贝叶斯网络推理过程为例,验证所提理论和方法的有效性。
Aiming at the fault information of CNC machine tools with incompleteness, inaccuracy and uncertainty, a reasoning method of fuzzy Bayesian network for CNC machine tool fault based on bucket elimination was proposed. The fuzzy numbers were used to describe the various fault states of the nodes, the fuzzy subsets were used to describe the failure probabilities of the root nodes, and the conditional probability tables （CPT） of the Bayesian network were used to describe the uncertainty relations between the nodes. The fuzzy Bayesian network for CNC machine tool fault was established. The bucket elimination algorithm was introduced to reason and compute the fuzzy Bayesian network for CNC machine tool fault, and the posterior probabilities of root nodes was obtained to provide the basis for diagnosing and analyzing CNC machine tool fault. The fault reasoning process of Bayesian network for CNC machine tool carrier system was taken as an example to verify the effectiveness of proposed theory and method.
出处
《航空精密制造技术》
2016年第5期14-18,共5页
Aviation Precision Manufacturing Technology
基金
国家自然科学基金项目(51575443)
陕西省教育厅重点实验室科学研究计划项目(16JS075)
关键词
桶消元算法
模糊贝叶斯网络
数控机床
故障推理
刀架系统
Bucket elimination algorithm
fuzzy Bayesian network
numerical control machine tool
fault reasoning
tool carrier system
