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基于符号有向图的汽车涡轮增压系统故障诊断
引用本文:许堃,王春芳,彭亚丽,朱明.基于符号有向图的汽车涡轮增压系统故障诊断[J].汽车科技,2011(4):18-20,24.
作者姓名:许堃  王春芳  彭亚丽  朱明
作者单位:合肥工业大学机械与汽车工程学院,合肥,230009
摘    要:基于符号有向图SDG(Signed Directed Graph)的传统故障诊断方法融入了定量推理的方法,提高了诊断精度,然而对不可测节点的处理大多采取等效删除以及假设状态信息扩展有效节点的方法,容易引起信息丢失和诊断效率低下的问题.结合汽车涡轮增压系统诊断实例,针对含有不可测节点的故障传播路径,提出引入模糊聚类的方法...

关 键 词:符号有向图  模糊聚类  定性定量模型

Diagnosis of Turbo System Fault Based on SDG
XU Kun,WANG Chun-fang,PENG Ya-li,ZHU Ming.Diagnosis of Turbo System Fault Based on SDG[J].Automobile Science and Technology,2011(4):18-20,24.
Authors:XU Kun  WANG Chun-fang  PENG Ya-li  ZHU Ming
Institution:(Hefei University of Technology School of Mechanral and Automotive Engineering,Hefei 230009,China)
Abstract:The traditional SGD-based fault diagnosis method blended the quantitative reasoning methods,which has improved the precision of the diagnostic a lot.However,during the process of dealing with the unmeasured nodes,the traditional fault diagnosis mostly takes the measure of equivalent deleting or assumption on the information extension's active nodes.These measures will easily cause the problems of information loss and low efficient in fault diagnosis.This paper will firstly do some research from the prospective of the unmeasured nodes' propagation path and propose the method of fuzzy clustering method.Then establishing the membership matrix of failure causes and symptoms from the empirical knowledge and combining the rule of maximum membership and threshold methods.Lastly,by fault reasoning,a valid fault diagnosis method will be concluded.
Keywords:signed directed graph(SDG)  fuzzy clustering  qualitative and quantitative model
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