【作者】 李钢；

【导师】 赵海；

【作者基本信息】 东北大学 ， 计算机软件与理论， 2008， 硕士

【摘要】 制动系统是汽车设备中至关重要的运行设备,其运行状态直接关系到人员的安全,因此,在制动系统运行状态检测的基础上展开故障诊断就显得尤为必要。但是,由于制动系统中存在很多错综复杂的相互关系,并存在大量的不确定因素及不确定信息,使得故障诊断较为困难。针对以上问题,本文对贝叶斯网络在液压制动系统故障诊断中的应用进行了研究。贝叶斯网络是目前不确定性知识表达和推理领域最有效的理论模型之一,适用于不确定性和概率推理的知识表达和推理。它是一种基于网络结构的有向图解描述,能进行双向并行推理,并能综合先验信息和样本信息,使得推理结果更为准确可信。因此,贝叶斯网络在故障诊断领域中的应用具有重要意义。本文以液压制动系统的故障诊断为研究对象,在对液压制动系统故障模式及原因分析的基础之上,提出了用贝叶斯网络来解决液压制动系统故障诊断的方法。根据多专家提供的规则进行贝叶斯网络结构学习,建立了基于贝叶斯网络的液压制动系统故障诊断分层结构模型,对模型的知识表达、建造方法进行了深入研究,同时也对贝叶斯网络基于团树传播的精确推理方法进行了论述。然后设计了贝叶斯网络故障诊断系统,并用c#语言实现了从建造贝叶斯网络结构,到进行诊断推理得出诊断结论整个过程。最后给出了一个例子来分析如何利用故障诊断系统进行故障诊断。经实验数据分析表明：本文的故障诊断系统诊断准确率高于模糊逻辑方法诊断准确率9.96个百分点,有效地解决了故障诊断中存在的不确定性问题,提高了诊断的准确率,从而验证了本文的故障诊断模型的有效性和具体的应用价值。更多还原

【Abstract】 The braking system is one of the important operation equipment in the automotive equipment and its running state directly relates to the safety of personnel, Therefore, it is particularly necessary to spread fault diagnosis, which is based on the check-up of running state in the braking system. But because of a lot of anfractuous correlations in the braking system and the existing of many uncertainty factors and much uncertainty information, it is very difficult to carry through fault diagnosis.In view of the above problems, the author made a research on applications of Bayesian network in the fault diagnosis of hydraulic braking system.The Bayesian network is one of the most efficient theoretical models in the current uncertainty of knowledge and inference areas. It can be used to the inference and knowledge expression of uncertainty and probability inference. As a exist-way diagram description based on net construction, it can start a two-way parallel inference, synthesize pre-tested and sample information and make the result of inference more accurate and credible. Therefore, Bayesian network has a deep impact on applications of fault diagnosis.This paper based on the fault diagnosis of hydraulic braking system for the study object, and on the basis of the analysis of the hydraulic braking system fault mode and the reasons put forward a method by Bayesian network to solve the fault diagnosis of hydraulic braking system. According to many rules provided by experts, the author learned the network structure of Bayesian,built the fault diagnosis of hydraulic braking system hierarchical structure model based on Bayesian network,carried out in-depth research about the knowledge expression and construction method, and discussed the accurate inference approaches based on clique tree. Then the author designed a Bayesian network fault diagnosis system, and using c# language realized the process from the construction of Bayesian network to a diagnostic inference drawn conclusions. Finally, the author gave an example of how to use fault diagnosis system for fault diagnosis.The analysis of the experimental data showed:In this paper, the diagnostic accuracy rate of the fault diagnosis system is 9.96 percentage points higher than the fuzzy logic method diagnostic accuracy rate, the uncertain problems of fault diagnosis were availably solved. The paper enhanced the diagnostic accuracy rate, as a result, proved the effectiveness of fault diagnosis model and idiographic application value.更多还原