微处理机应用系统容错设计之实例分析——温控仪容错设计

在微处理机应用系统容错设计理论的基础上,采用了过程通道、 Ｒ Ａ Ｍ 的备用容错以及系统恢复和重入技术,对温控仪容错进行了设计．     

Ho∞-based fault detection for nonlinear networked systems with random packet dropout and probabilistic interval delay

The fault detection problem for the nonlinear networked control system (NCS) with packet dropout and delay is investigated.A nonlinear stochastic system model is proposed to account for the NCS with random packet dropout and networkinduced non-uniformly distributed time-varying delay in both from sensor to controller (S/C) and from controller to actuator (C/A).Based on the obtained NCS model,employing an observer-based fault detection filter as the residual generator,the addressed fault detection problem is converted into an auxiliary nonlinear H∞ control problem.Then,with the help of Lyapunov functional approach,a sufficient condition for the desired fault detection filter is constructed in terms of certain linear matrix inequalities,which depend on not only the delay interval but also the delay interval occurrence rate and successful packet communication rate.Especially,a trade-off phenomenon between the maximum allowable delay bound and successful data packet transmission rate is found,which is typically resulted from the limited bandwidth of communication networks.The effectiveness of the proposed method is demonstrated by a simulation example.     

具有混合执行器故障的多智能体分布式有限时间自适应协同容错控制

针对多智能体编队系统执行器发生故障时,所引起的参数不确定以及系统瞬态不稳定问题,本文采用径向基函数神经网络(radial basis function neural networks, RBFNNs)对不确定参数(未知函数)进行估计。同时,基于反推技术设计出合理的自适应容错控制器,并通过有限时间理论保证系统实现瞬态稳定。首先,本文采用10个智能体作为被控对象,基于有向通讯拓扑结构理论,构建了非线性多智能体系统模型。其次,基于RBFNNs逼近特性,采用反推技术与动态面技术相结合,设计出合理的容错控制器,补偿多智能体中出现的未知非线性执行器故障,并采用有限时间理论解决系统瞬态不稳定问题。接着,基于Lyapunov稳定性理论分析了控制器的稳定性和快速收敛性。最后,通过两种算例对比,验证了所设计的控制器性能优于传统的反推技术,为工程实践提供了一种有效的研究思路。     

H_∞-based fault detection for nonlinear networked systems with random packet dropout and probabilistic interval delay

The fault detection problem for the nonlinear networked control system(NCS) with packet dropout and delay is investigated.A nonlinear stochastic system model is proposed to account for the NCS with random packet dropout and networkinduced non-uniformly distributed time-varying delay in both from sensor to controller(S/C) and from controller to actuator(C/A).Based on the obtained NCS model,employing an observer-based fault detection filter as the residual generator,the addressed fault detection problem is converted into an auxiliary nonlinear H∞ control problem.Then,with the help of Lyapunov functional approach,a sufficient condition for the desired fault detection filter is constructed in terms of certain linear matrix inequalities,which depend on not only the delay interval but also the delay interval occurrence rate and successful packet communication rate.Especially,a trade-off phenomenon between the maximum allowable delay bound and successful data packet transmission rate is found,which is typically resulted from the limited bandwidth of communication networks.The effectiveness of the proposed method is demonstrated by a simulation example.     

基于Park-HHT的故障特征提取方法

针对三相对称系统,提出了一种新的故障特征提取方法。该方法首先将系统输出信号进行Park变换,之后进行希尔伯特-黄变换(Hilbert-Huang transform, HHT),从HHT的本征模态函数中选取低频分量,提取信号幅度作为故障特征值。该方法兼具Park变换和HHT的优点,在降低变量维度的同时提高了故障分辨率,并且具有较强的抗噪声能力。最后,在三相逆变电路中进行了仿真实验,根据特征向量间距离分布对不同方法的提取效果进行评价,验证了所提方法的有效性。     

考虑单元互测的测试性指标分配方法

测试性分配是将系统级测试性指标按照一定规则分配给各组成单元的过程。针对现有主流测试性分配方法未考虑单元之间的互测情形,导致分配结果不合理,尤其是部分单元分配指标虚高,难以实现或代价过高等问题,提出了在综合考虑单元故障率、故障危害度等多重影响因素基础上,进一步考虑单元互测因素的测试性指标分配方法。首先实施考虑多重影响因素的指标初次分配;然后基于单元测试性初步设计结果,实施测试性建模与分析,得到单元自检故障率与他检故障率;再利用这两个数据以及初次分配结果构造分配函数实施再次分配,进而得到最终的分配结果;最后应用该方法进行仿真和实例运算,证明了该方法的有效性和先进性。     

基于隐Markov树的设备状态综合诊断模型

为了充分利用小波系数之间的统计相依性以更有效地诊断设备状态,提出了一种基于隐Markov树(HMT)的综合诊断模型。首先通过主成分分析将来自多个传感器的信号转换为主成分,求出各主成分对应的频谱,然后通过比较对已训练的各HMT模型的适应度,运用Bayes决策融合法则得到设备状态综合诊断决策。为了克服HMT模型存在的计算溢出困难,采用尺度变换对EM算法进行了改进。通过两个实例验证了该综合诊断模型具有较高的诊断准确率。     

共振解调和小波分析在机械故障诊断中的应用

提出共振解调技术的数学模型,求解数学模型的脉冲响应,为该技术在正常低频振动中提取所夹带的微小冲击的应用提供了理论依据。介绍小波分析提取微小冲击信息在诊断轴承初始故障中的应用,通过MATLAB数字仿真和现场应用实例,取得与共振解调技术相同的应用效果,说明小波分析和共振解调技术在提取齿轮、轴承机械故障的微小冲击的应用上是非常有效的。     

基于模糊神经网络的车用发电机故障诊断系统的研究

文章针对车用交流发电机的特点，建立了故障现象与故障征兆列表，并应用基于模糊神经网络的故障诊断方法，实现了对该类发电机故障的模糊诊断。文中还介绍了模糊神经网络的结构和对应的学习方法，以及基于CAN总线的实时的车用交流发电机故障诊断系统的组成，该系统利用计算机作平台。仿真和试验结果表明，该诊断方法是行之有效的。