Fault diagnosis in analog circuit based on binary tree with maximum fault information volume.
2．研究了基于最大故障信息量的模拟电路故障诊断方法。
参考来源 - 基于时频分析和神经网络的模拟电路故障诊断及可测性研究Fault diagnosis in analog circuit based on binary tree with maximum fault information volume.
2．研究了基于最大故障信息量的模拟电路故障诊断方法。
参考来源 - 基于时频分析和神经网络的模拟电路故障诊断及可测性研究·2,447,543篇论文数据，部分数据来源于NoteExpress
在故障模糊集划分的基础上，根据故障信息量，建立了实时故障树的节点优选方法。
Based on carving up the fuzzy sets, according to quantity of fault information, a node selecting method for real-time fault diagnosis tree is established.
在故障模糊集划分的基础上，根据故障信息量，建立了实时故障树的节点优选方法。
Based on carving up the fuzzy sets, according to the quantity of fault information, a node selecting method for real - time fault diagnosis tree is astablished.
依据故障点处提供的故障信息量最大，将故障诊断问题转化为寻找最优故障检测点问题。
According to the rule that fault information volume is maximal at fault point, the fault diagnosis problem is transferred into problem on seeking for optimum fault detecting point.
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