基于AFPN的舰船电子综合化系统总线故障诊断研究

针对舰船电子综合化系统总线故障诊断模糊性、不确定性的日益增强,且难以实现快速故障诊断的难题,提出一种基于自适应模糊Petri网(Adaptive Fuzzy Petri Net,AFPN)的舰船电子综合化系统总线故障诊断方法;在加权模糊Petri网(Weighted Fuzzy Petri Net,WFPN)的基础上,引入神经网络技术,给出了AFPN的形式化定义及学习算法;实例分析验证了所提方法的有效性,研究表明:AFPN模型具有很强的自适应能力和推理能力,克服了传统单纯依靠人工经验故障诊断的不确定性和偶然性,可以实现舰船电子综合化系统总线快速精确的故障诊断。     

基于PCA-KNN聚类的通用在线故障诊断算法设计

为了克服以往故障诊断算法所具有的难以诊断效率低、诊断精度不高和模型通用性不强的缺点,提出了一种基于PCA主元分析特征优化和KNN聚类的故障诊断法算法;首先,给出了故障诊断的总体模型和诊断原理,然后在故障征兆原始样本数据的基础上,通过PCA主元分析法进行特征优化,获得维数约简的样本数据,从而提高故障诊断的效率;在此基础上,采用训练样本数据对模糊K均值分类器进行训练,并计算每个聚类的距离和阈值;最后,将在线获取的测试样本数据或离线样本数据输入到模糊K均值分类器,获得其所属分类,并采用KNN最近邻算法来获取其K个近邻,根据其与近邻的距离平方和与所属聚类距离平方阈值来判断其是否为故障样本,从而实现故障诊断;以滚动轴承故障诊断试验和模拟电路故障诊断试验为例,实验结果证明了文中方法较其它方法具有诊断效率高和诊断精度高的优点,是一种通用的和可行的在线故障诊断方法。     

模糊故障树分析法在航空发动机滑油渗漏分析中的应用

目的：为准确查找航空发动机滑油渗漏原因,研究模糊故障树理论在飞机故障诊断方面的应用。方法：以CFM56-7B发动机滑油系统为研究对象,将故障树理论应用于滑油系统渗漏故障诊断中,采用下行法求解最小割集得到故障诱因最小事件。根据滑油故障发生概率具有模糊和不确定性特点,结合Delphi专家调查采用模糊数学理论进行定量分析,确定故障诱因事件风险重要度排序。结果：从CFM56-7B滑油渗漏故障原因重要度排序可知,故障诱因依次为后收油池供油口盖封严损坏（x1）、后收油池滑油回油管接头处裂纹(x2)、发动机使用MJO291滑油后导致密封材料损坏（x8)等,维修时应注意。结论：维修单位故障记录验证了方法的有效性,可为准确和快速诊断和排除滑油渗漏故障提供参考。     

融入模糊推理的新型故障树诊断方法

在以预防为主、准确、高效武器装备故障诊断的指导思想下,针对故障树诊断法固有的优缺点属性,本文将产生式规则和模糊理论引入故障树中,设计了故障树的确定性诊断和不确定性推理的故障诊断推理方法,将模糊故障机理以“故障树”的方式进行表达,使故障树诊断从确定性诊断领域扩展到模糊诊断领域,并构建了相应诊断算法流程。通过仿真对比,说明了该故障诊断推理方法的正确性,同时还证明了该方法具备快速性、准确性,以及处理模糊故障机理问题的能力。     

温度测量及故障诊断系统的设计

文章给出基于数字式温度传感器DS18X2 0的温度测量系统 ,并利用模糊原理、在线测量温度等方法进行故障诊断。详细论述系统的组成原理、模糊故障诊断方法、硬件电路和软件设计思想。该系统具有故障在线检测、自诊断、显示故障类型及发出声音报警等功能 ,在实际应用中取得了很好的效果。     

基于免疫遗传算法改进的BP神经网络在灭火系统电路板故障诊断中的应用

针对装甲车辆灭火系统电路板规模较大,功能日趋多样与完善的同时,其复杂程度也日益提高,故障层次越来越多,故障现象与故障原因的映射关系更加复杂,组合故障频发,传统的故障诊断方法已不能满足灭火系统电路板故障诊断的要求。设计了基于免疫遗传算法优化的BP神经网络对灭火系统电路板进行故障诊断,并在免疫和遗传过程中保留了部分训练最优解。实现了神经网络收敛速度的提高,使用Matlab编程优化算法并完成了电路板仿真故障的诊断。通过实验验证了该诊断模型的准确性和可靠性,为电气系统通用检测设备的神经网络诊断方法实现提供了理论支撑。     

基于CLIPS的机载光电跟踪设备故障诊断专家系统研究

针对机载光电跟踪设备传感器种类多、单元部件结构复杂和急需快速故障定位的要求,设计了机载光电跟踪设备故障诊断专家系统。通过建立跟踪系统故障树并分析其故障特点,确定了模糊多值产生式规则的知识表示方式和冲突消解策略,构建了专家系统知识库和推理机;同时结合数据库建立的故障表和规则表,实现专家系统解释器功能;最后将CLIPS嵌入VC设计友好人机交互界面。实验表明,该专家系统操作方便,能快速准确定位故障、解释故障成因以及提供维修建议。     

基于有色Petri网的机械系统故障诊断研究

故障诊断对于机械系统的使用与维护起着重要的作用;为了提高机械系统故障诊断的效率以及直观性,提出了一种使用基于知识的故障诊断方法,即使用有色Petri网诊断方法建立一种通用机械系统故障诊断模型并进行分析。针对数控机床液压元件故障这一案例,首先获取其故障来源建立故障树;其次在故障树基础上运用有色Petri网建模工具CPNTools建立有色Petri网模型;最后对模型进行了仿真分析以模拟故障的传递,进行状态空间分析以判断模型安全性,结果表明所提出的建模方法能够使得故障传递更加直观化,快速了解故障的发展趋势,并表明此模型有着较强的易用性以及通用性。     

复杂机载电子系统故障综合诊断技术研究

故障综合诊断技术一直是复杂机载电子系统研发过程中的关键部分,当前的故障诊断技术同时需要机内测试（BIT）和场外自动化测试设备（ATE）的测试结果才能得出诊断结果,诊断效率低,时间长并且不能在线诊断。针对新一代战斗机将更加依赖航空电子系统的趋势,迫切需要一种诊断时间短,且能够实现在线诊断的故障诊断技术。因此,一种基于模型的故障诊断方法被提出。该方法通过融合多信号模型和整数编码故障字典模型,模块间采用多信号模型,单个模块中采用整数编码故障字典模型,克服了多信号模型对测试信息的浪费和整数编码故障字典模型建模困难的缺点,并提出一种多目标测试优选方法,通过优化检测方案,充分发挥BIT的检测性能。该方法通过充分使用BIT的测试信息,摆脱了对场外ATE的依赖,实现了在线快速定位故障并识别故障模式。     

基于多信号流模型的电子设备故障诊断方法

为了提高产品的可靠性,并且在电子设备发生故障时迅速地确定故障源,保障设备的正常运行,基于多信号流模型的诊断建模方法,在多信号流基础上引入了以故障重要先验知识为主的多信号流故障诊断策略,通过引入故障模式的故障概率改进了多信号流诊断技术。该方法已应用于BEPCⅡ磁铁电源接口控制设备故障诊断系统,使用TEAMS测试工具箱建模实现了快速准确的故障诊断和定位,提高了磁铁电源控制设备的故障诊断检测率和隔离率,并且可以方便地扩展到其他设备和系统上。     

基于CAN总线的某型数字化战车自动测试系统设计

针对现代数字化战车电气与电子系统技术复杂、各分系统关联程度高、维修保障困难等问题,设计了一种基于CAN总线的数字化战车自动测试系统;整体设计基于模块化思想,充分利用车载备用总线,综合运用了DSP+FPGA控制处理技术、AFPN智能故障诊断技术,能够对车载电气与电子系统进行分系统独立测试和全系统联合检测,具有快速故障定位能力和拓扑适应能力;采用适配器与上位机测试软件的分体式设计,实现了平台物理资源复用。应用表明,该系统能够较好的适用于现代数字化战车的维修保障,使用方便,故障诊断快速有效。     

Feature Enhancement Method of Rolling Bearing Based on K-Adaptive VMD and RBF-Fuzzy Entropy

The complex and harsh working environment of rolling bearings cause the fault characteristics in vibration signal contaminated by the noise, which make fault diagnosis difficult. In this paper, a feature enhancement method of rolling bearing signal based on variational mode decomposition with K determined adaptively (K-adaptive VMD), and radial based function fuzzy entropy (RBF-FuzzyEn), is proposed. Firstly, a phenomenon called abnormal decline of center frequency (ADCF) is defined in order to determine the parameter K of VMD adaptively. Then, the raw signal is separated into K intrinsic mode functions (IMFs). A coefficient En for selecting optimal IMFs is calculated based on the center frequency bands (CFBs) of all IMFs and frequency spectrum for original signal autocorrelation operation. After that, the optimal IMFs of which En are bigger than the threshold are selected to reconstruct signal. Secondly, RBF is introduced as an innovative fuzzy function to enhance the feature discrimination of fuzzy entropy between bearings in different states. A specific way for determination of parameter r in fuzzy function is also presented. Finally, RBF-FuzzyEn is used to extract features of reconstructed signal. Simulation and experiment results show that K-adaptive VMD can effectively reduce the noise and enhance the fault characteristics; RBF-FuzzyEn has strong feature differentiation, superior noise robustness, and low dependence on data length.     

侧入式导光板网点全自动优化设计研究

为解决目前侧入式导光板网点优化设计中存在经验式手动优化繁琐、且很难达到一个高均匀效果的问题,提出了一种基于模糊优化理论的网点自动优化设计方法。网点形状采用锥形结构,为使目标面上各处的光能分布主要由其正下方网点的散射光贡献,分析了其半顶角与网点位置的关系,并使得网点半顶角仅由其位置决定。以网点半径为主要优化参数,通过隶属度函数将网点结构模糊化,并自定义评价函数来解模糊化实现均匀照明。进而,采用动态数据交换(DDE)技术将Matlab与TracePro进行联立,通过Matlab语言与Scheme语言混编控制TracePro自动进行数据交换、光线追迹与模糊优化。导光板网点优化设计实例仿真结果表明,优化后均匀度达到92.17%,光能利用率达到70.37%,全程实现自动优化,无需任何手动调节。     

Intelligent Fault Diagnosis of Rolling-Element Bearings Using a Self-Adaptive Hierarchical Multiscale Fuzzy Entropy

The fuzzy-entropy-based complexity metric approach has achieved fruitful results in bearing fault diagnosis. However, traditional hierarchical fuzzy entropy (HFE) and multiscale fuzzy entropy (MFE) only excavate bearing fault information on different levels or scales, but do not consider bearing fault information on both multiple layers and multiple scales at the same time, thus easily resulting in incomplete fault information extraction and low-rise identification accuracy. Besides, the key parameters of most existing entropy-based complexity metric methods are selected based on specialist experience, which indicates that they lack self-adaptation. To address these problems, this paper proposes a new intelligent bearing fault diagnosis method based on self-adaptive hierarchical multiscale fuzzy entropy. On the one hand, by integrating the merits of HFE and MFE, a novel complexity metric method, named hierarchical multiscale fuzzy entropy (HMFE), is presented to extract a multidimensional feature matrix of the original bearing vibration signal, where the important parameters of HMFE are automatically determined by using the bird swarm algorithm (BSA). On the other hand, a nonlinear feature matrix classifier with strong robustness, known as support matrix machine (SMM), is introduced for learning the discriminant fault information directly from the extracted multidimensional feature matrix and automatically identifying different bearing health conditions. Two experimental results on bearing fault diagnosis show that the proposed method can obtain average identification accuracies of 99.92% and 99.83%, respectively, which are higher those of several representative entropies reported by this paper. Moreover, in the two experiments, the standard deviations of identification accuracy of the proposed method were, respectively, 0.1687 and 0.2705, which are also greater than those of the comparison methods mentioned in this paper. The effectiveness and superiority of the proposed method are verified by the experimental results.     

A Fault Diagnosis Method Considering Meteorological Factors for Transmission Networks Based on P Systems

Bad meteorological conditions may reduce the reliability of power communication equipment, which can increase the distortion possibility of fault information in the communication process, hence raising its uncertainty and incompleteness. To address the issue, this paper proposes a fault diagnosis method for transmission networks considering meteorological factors. Firstly, a spiking neural P system considering a meteorological living environment and its matrix reasoning algorithm are designed. Secondly, based on the topology structure of the target power transmission network and the action logic of its protection devices, a diagnosis model based on the spiking neural P system considering the meteorological living environment is built for each suspicious fault transmission line. Following this, the action messages of protection devices and corresponding temporal order information are used to obtain initial pulse values of input neurons of the diagnosis model, which are then modified with the gray fuzzy theory. Finally, the matrix reasoning algorithm of each model is executed in a parallel manner to obtain diagnosis results. Experiment results achieved out on IEEE 39-bus system show the feasibility and effectiveness of the proposed method.     

基于自适应模糊控制的分数阶混沌系统同步

本文主要研究了带有未知外界扰动的分数阶混沌系统的同步问题.基于分数阶Lyapunov稳定性理论,构造了分数阶的参数自适应规则以及模糊自适应同步控制器.在稳定性分析中主要使用了平方Lyapunov函数.该控制方法可以实现两分数阶混沌系统的同步,使得同步误差渐近趋于0.最后,数值仿真结果验证了本文方法的有效性.     

Fault tolerant synchronization of chaotic systems based on T-S fuzzy model with fuzzy sampled-data controller

In this paper the fault tolerant synchronization of two chaotic systems based on fuzzy model and sample data is investigated. The problem of fault tolerant synchronization is formulated to study the global asymptotical stability of the error system with the fuzzy sampled-data controller which contains a state feedback controller and a fault compensator. The synchronization can be achieved no matter whether the fault occurs or not. To investigate the stability of the error system and facilitate the design of the fuzzy sampled-data controller, a Takagi--Sugeno (T--S) fuzzy model is employed to represent the chaotic system dynamics. To acquire the good performance and produce less conservative analysis result, a new parameter-dependent Lyapunov--Krasovksii functional and a relaxed stabilization technique are considered. The stability conditions based on linear matrix inequality are obtained to achieve the fault tolerant synchronization of the chaotic systems. Finally, a numerical simulation is shown to verify the results.     

ARINC659总线桥接的设计及对总线同步的影响分析

ARINC659总线因其在时间和空间上均提供了完备的故障冗余和操作健壮性,已经逐渐在对数据通信确定性及故障沉默和屏蔽要求较高的航天领域中展开应用。为了使ARINC659总线能够更好的适应航天器综合电子系统的高度冗余容及分布式控制的需求,对一种能够在不同设备中ARINC659总线之间相互桥接的技术进行了研究,进而实现分布式综合电子系统中所有硬件模块的统一时序规划和通信调度,可以显著提升系统中的资源共享、并行处理、故障冗余及分布式控制能力,同时也为关键系统中不同设备中的硬件模块间实现严格的时序关系操作提供了一种解决方案。最后就桥接对ARINC659总线同步机制的影响进行了分析,据此提出了桥接设计的约束和实现规则。