模糊诊断规则自学习中规则条件优选技术研究

规则条件优选技术是模糊诊断规则自学习方法的重要环节之一.针对条件优选问题,提出了一种基于面积计算的模糊贴近度函数,并采用该函数对各规则条件的可区分程度做出评估,然后根据得到的评估矩阵设计了规则条件和测点的优选算法.仿真证明,通过条件优选可以大量减少规则中条件的数量,减少了规则学习的计算量,提高了学习的效率;同时,所研究的测点优选技术还可为自动测试程序的设计提供参考.      

基于Driscoll凹腔稳焰模型的超声速燃烧火焰稳定尺度效应研究

为了研究超声速燃烧室尺度放大后,保持火焰稳定边界相对于基准燃烧室不变,凹腔火焰稳定器几何参数应遵循何种放大准则的问题,基于已有的Driscoll凹腔稳焰数学模型,采用典型的单凹腔矩形截面燃烧室作为基准燃烧室,分别计算基准燃烧室在贫燃和富燃状态时的火焰稳定准则数DaNP,再按照燃烧室尺度放大定义写出尺度放大燃烧室的稳焰准则数表达式Da''NP,将稳焰边界不变作为约束条件,构建尺度放大准则方程式DaNP= Da''NP,求解准则方程式获得凹腔几何参数放大准则表达式,绘制准则特性曲线,分析归纳近似准则,并通过数值计算方法初步验证准则的有效性。采用Driscoll凹腔稳焰模型的尺度效应分析结果表明,燃烧室放大一定倍数n后,无法通过调整凹腔长度和深度放大倍数k1和k2使得贫燃熄火边界保持不变;但是,可以通过调整参数k1和k2使得富燃熄火边界保持不变,此时凹腔几何参数遵循的放大准则近似为 k1≈k2≈n1/4。     

一种基于有效修剪的最大频繁项集挖掘算法

对关联挖掘中的最大频繁项集挖掘问题进行了研究,提出了一种基于项集格修剪机制的最大频繁项集挖掘算法.采用项集格生成树的数据结构,将最大频繁项集挖掘过程转化为对项集格生成树进行深度优先搜索获取所有最大频繁节点的过程. 其中提高算法效率的一个重要措施是在遍历项集格生成树的过程中对生成树进行修剪.给出了项集格生成树的三个性质,并在此基础上提出了直接超集修剪、间接超集修剪与事务集等价修剪三种修剪机制,尽可能忽略非频繁节点及其所生成的扩展节点以减少遍历的节点数目.试验结果表明,三种修剪机制都能够有效地减少搜索空间,其中事务集等价修剪机制的效果最好,算法的性能与输入数据集的稠密程度相关.      

一种基于被动探测的双机雷达协同定位方法

针对有源探测易被发现及干扰的问题,设计基于被动探测的双机协同射频隐身定位方法。通过测向交叉定位处理获得目标的距离信息,利用属性数据关联消除“鬼影”,从而完成对目标稳定有效的探测。所设计的双机雷达协同定位方法具有目标定位精度高和隐蔽性良好等优点,并通过仿真验证了算法的有效性和实用性。     

An ECR-PCR rule for fusion of evidences defined on a non-exclusive framework of discernment

In the research of uncertain information processing, Dempster-Shafer Theory (DST) provides a framework for dealing with uncertain information, where evidence is defined on a Frame of Discernment (FOD) consisting of mutually exclusive elements. However, the requirement of exclusiveness on FOD sometimes is not satisfied, as shown in Dezert-Smarandache Theory(DSmT), a derivative of DST. In DSmT, the non-exclusiveness is expressed by propositions’ intersection and the fusion of evidence is realized through a Proportional Conflict Redistribution (PCR) rule. In order to handle non-exclusive FODs, a new framework called D Number Theory (DNT) has been proposed recently, which quantifies the non-exclusive degree between propositions different from DSmT. In previous studies, an Exclusive Conflict Redistribution (ECR) rule has been designed in DNT to implement the fusion of evidence defined on a non-exclusive FOD, but there are some deficiencies in the ECR rule. In this paper, a new rule called ECR-PCR rule is proposed by combining the ECR and PCR rules to better implement the fusion of evidence defined on a non-exclusive FOD. Within the proposed rule, the definition of conflict utilizes the idea of ECR’s exclusive conflict, and the disposal of conflict is following the idea of PCR’s proportional redistribution. Properties of the ECR-PCR rule are presented. The effectiveness of the proposed new rule is verified through numerical examples and applications, in comparison with other fusion methods.     

液体火箭发动机端面密封用石墨材料内部缺陷检测工艺方法

介绍了石墨材料的制造工艺和缺陷类型,并结合液体火箭发动机端面密封的工作特性,阐明了端面密封用石墨材料内部缺陷检测的必要性。对目前通用的无损检测方法进行了对比分析,确定了适用于液体火箭发动机端面密封用石墨材料内部缺陷的X射线检测方法,并对X射线检测过程中图像灰度、对比度、电压、电流、滤片及积分时间等关键工艺参数的影响因素进行了对比分析,确定了石墨材料内部缺陷检测的工艺参数设置准则及高精度检测方法,实现了石墨材料内部孔隙的可视化仿真分析,并提出了一种基于图像处理的石墨材料气孔率统计计算方法,最终建立了液体火箭发动机端面密封用石墨材料内部典型缺陷的特征标样。     

On the evidential reasoning rule for dependent evidence combination

Evidential Reasoning (ER) rule, which can combine multiple pieces of independent evidence conjunctively, is widely applied in multiple attribute decision analysis. However, the assumption of independence among evidence is often not satisfied, resulting in ER rule inapplicable. In this paper, an Evidential Reasoning rule for Dependent Evidence combination (ERr-DE) is developed. Firstly, the aggregation sequence of multiple pieces of evidence is determined according to evidence reliability. On this basis, a calculation method of evidence Relative Total Dependence Coefficient (RTDC) is proposed using the distance correlation method. Secondly, as a discounting factor, RTDC is introduced into the ER rule framework, and the ERr-DE model is formulated. The aggregation process of two pieces of dependent evidence by ERr-DE is investigated, which is then generalized to aggregate multiple pieces of non-independent evidence. Thirdly, sensitivity analysis is carried out to investigate the relationship between the model output and the RTDC. The properties of sensitivity coefficient are explored and mathematically proofed. The conjunctive probabilistic reasoning process of ERr-DE and the properties of sensitivity coefficient are verified by two numerical examples respectively. Finally, the practical application of the ERr-DE is validated by a case study on the performance assessment of satellite turntable system.     

A new interpretable fault diagnosis method based on belief rule base and probability table

It is vital to establish an interpretable fault diagnosis model for critical equipment. Belief Rule Base (BRB) is an interpretable expert system gradually applied in fault diagnosis. However, the expert knowledge cannot be utilized to establish the initial BRB accurately if there are multiple referential grades in different fault features. In addition, the interpretability of BRB-based fault diagnosis is destroyed in the optimization process, which reflects in two aspects: deviation from the initial expert judgment and over-optimization of parameters. To solve these problems, a new interpretable fault diagnosis model based on BRB and probability table, called the BRB-P, is proposed in this paper. Compared with the traditional BRB, the BRB-P constructed by the probability table is more accurate. Then, the interpretability constraints, i.e., the credibility of expert knowledge, the penalty factor and the rule-activation factor, are inserted into the projection covariance matrix adaption evolution strategy to maintain the interpretability of BRB-P. A case study of the aerospace relay is conducted to verify the effectiveness of the proposed method.     

一种可靠性增长试验抽样数Max-Min准则的反馈修正方法

对成败型航空发动机部件可靠性增长试验抽样数的确定问题进行了研究。推导出了初始故障数服从典型离散分布时的最小化最大准则(Max-Min准则),提出了一种逐次抽样样本估计值反馈修正方法。最后给出了一个应用实例,验证了该方法的有效性。     

A novel combination belief rule base model for mechanical equipment fault diagnosis

Due to the excellent performance in complex systems modeling under small samples and uncertainty, Belief Rule Base(BRB) expert system has been widely applied in fault diagnosis. However, the fault diagnosis process for complex mechanical equipment normally needs multiple attributes, which can lead to the rule number explosion problem in BRB, and limit the efficiency and accuracy. To solve this problem, a novel Combination Belief Rule Base(C-BRB) model based on Directed Acyclic Graph(DAG) structu...