双通道自适应Lattice滤波器及其在故障检测中的应用

推导出一种双通道自适应Ｌａｔｔｉｃｅ滤波器算法，并将它用于动态系统的故障检测。这种故障检测方案不需要建立准确的数学模型，只要根据系统的输入输出数据，利用Ｌａｔｔｉｃｅ滤波器算法生成故障残差序列，再对故障残差序列进行统计检验，可实现动态系统的故障检测。该方法用于一个仿真的直流伺服系统的故障检测，实验效果是满意的。     

基于观测器的l~1鲁棒故障检测方法

基于参数化的控制系统输出观测器 ,将鲁棒控制理论中的l1最优化方法用于故障检测技术 ,提出一种新的控制系统鲁棒故障检测方法 .通过求解一个混合 0 1型整数线性规划问题 ,可得出l1优化残差函数 .仿真结果验证了所提方法的有效性     

考虑输出量化的控制系统传感器故障检测

针对一类考虑输出均匀量化的控制系统,研究了传感器故障下的故障检测问题.首先,从优化的角度出发,考虑残差对未知干扰的鲁棒性和对传感器故障灵敏性之间的折中问题,给出了H∞/H∞性能指标,并通过求解代数黎卡提方程得出最优残差生成器的增益矩阵;然后,利用量化误差的随机过程特性,设计了残差评价器,同时给出了所设计阈值误报率的上确...     

基于自适应滑模观测器的航空电连接器间歇性失效检测

针对航空电连接器系统建立数学模型,提出基于自适应滑模观测器的故障重构方法实现间歇性失效检测.针对乘性故障上界未知的情况,设计自适应律在线修正滑模观测器增益.采用Lyapunov函数作为稳定观测器的判别条件,保证跟踪状态的收敛性.引入线性变换矩阵进一步求取实现滑模运动的滑模观测器增益常数项,并验证滑模运动将在有限时间内发生.应用等价输出误差介入原理获取故障信息,实现乘性故障的检测和重构.对重构出的特征参数进行分析可以判断电连接器是否发生失效.用SIMULINK进行仿真,结果验证该方法有效.     

基于残差决策的自动飞行控制系统远程实时故障诊断

针对自动飞行控制系统结构复杂、关联部件众多,发生故障时诊断时间长,从而影响飞机运行效率的问题,提出一种基于飞机通信寻址报告系统(ACARS)的远程实时故障诊断方案。首先,分析自动飞行控制系统的故障特点,设计搭建检测滤波器;然后,利用ACARS数据链实时发送的自动飞行控制系统的关键信息进行相关部件的残差计算,并根据残差决策算法进行故障诊断及定位;最后,针对不同故障部件残差间的差异大、决策门限无法统一的缺点,提出基于二次差值的残差决策改进算法,减缓了检测对象的整体变化趋势,降低了随机噪声和干扰的影响,避免了将瞬态故障诊断为系统故障的情况。实验仿真结果表明,基于二次差值的改进残差决策算法避免了多决策门限的复杂性,在采样时间为0.1 s的情况下,故障检测所需时间大约为2 s,故障检测时间大幅降低,有效故障检测率大于90%。     

Fault detection of networked control systems with limited communication

Fault detection (FD) of networked control systems (NCS) with limited communication is addressed in this article. In periodic communication sequence-based NCS, at each time instant only parts of the actuators and sensors are allowed to communicate with the central FD system, which leads to incomplete plant information at the central station. In this article, a parity space based multi-solution FD scheme is proposed based on different information structures of the incomplete plant information. In this multi-solution scheme, each solution is an independent residual generator and has different properties. It is proved that there is a tradeoff between fast FD and detection performance, i.e. the solution with a smaller FD delay has a poorer fault sensitivity and thus a larger miss detection rate, whereas the one with a higher fault sensitivity has a larger FD delay. The FD scheme can be realised by diagnostic observers as well, which have more design freedom. Simulation results are also given to illustrate the results obtained.     

A robust detection and isolation scheme for abrupt and incipientfaults in nonlinear systems

This paper presents a robust fault diagnosis scheme for abrupt and incipient faults in nonlinear uncertain dynamic systems. A detection and approximation estimator is used for online health monitoring. Once a fault is detected, a bank of isolation estimators is activated for the purpose of fault isolation. A key design issue of the proposed fault isolation scheme is the adaptive residual threshold associated with each isolation estimator. A fault that has occurred can be isolated if the residual associated with the matched isolation estimator remains below its corresponding adaptive threshold, whereas at least one of the components of the residuals associated with all the other estimators exceeds its threshold at some finite time. Based on the class of nonlinear uncertain systems under consideration, an isolation decision scheme is devised and fault isolability conditions are given, characterizing the class of nonlinear faults that are isolable by the robust fault isolation scheme. The nonconservativeness of the fault isolability conditions is illustrated by deriving a subclass of nonlinear systems and of faults for which these conditions are also necessary for fault isolability. Moreover, the analysis of the proposed fault isolation scheme provides rigorous analytical results concerning the fault isolation time. Two simulation examples are given to show the effectiveness of the fault diagnosis methodology     

网络化切换控制系统故障检测与优化设计

研究存在未知短时延、丢包和系统不确定性的网络化切换控制系统故障检测与时域优化问题. 首先基 于观测器构建残差发生器, 结合Lyapunov 函数方法和平均驻留时间方法分析系统的稳定性, 并以线性矩阵不等式(LMI) 形式给出故障检测滤波器的求解方法; 然后为了改善故障检测系统的性能, 采用后置滤波器对残差信号进行时域优化, 并利用奇偶空间方法给出其最优解; 最后设计并推导出自适应阈值. 仿真结果验证了所提出方法的有效性.

     

基于自主诊断重构技术的航天器故障检测系统设计

传统航天器故障检测系统姿态定位能力较差,导致不能突破阈值,准确实现检测,且传统系统不具备重构能力;为解决上述问题,基于自主诊断重构技术,提出了一种故障检测的新方法,优化设计了航天器故障检测系统的硬件和软件部分,硬件设计采用EEC-I型检测器,为保证检测器的运行,对检测器的电压与电流范围进行了设置;设计采用MATLAB的数据采集器,选用Telnet接入端口,实现采集器的通信,确保数据的顺利采集;采用FIR滤波器,为保证信号的完整性对通带和阻带进行设置;设计采用4NIC-UPS27型号一体化不间断电源为航天器故障检测系统提供动能;软件设计基于自主诊断重构技术的航天器故障检测系统流程,运用小波网络算法对航天器的姿态角数据进行分析,预测航天器的姿态角的安全阈值,最后利用残差数据分布概率模型进行航天器故障诊断;实验结果表明,设计的基于自主诊断重构技术的航天器故障检测系统能够很好地从X、Y、Z三个轴进行检测,确定不同方位的航天器故障,在设定阈值后,提出的检测系统能够很好地分析阈值,实现残差突破,同时具备路线重构能力。     

Recursive observer‐based fault detection for a class of nonlinear uncertain systems with output constraints

This paper investigates the fault detection (FD) problem for a class of nonlinear uncertain systems in strict feedback form with an output constraint. The key idea is to design an observer to generate the FD signals and the output estimate, which also satisfies the output constraint. To facilitate constraint handling, the constraints on the output and the output estimate are transformed into the output estimation error constraint. Then, the FD observer is designed in a recursive framework. By employing a barrier Lyapunov function, the output estimation error constraint is incorporated in the last step of the recursive observer design algorithm to prevent constraint violation. It is shown that the output estimation error is uniformly bounded and satisfies the constraint for the fault‐free case. Furthermore, the residual signal is constructed by the output estimation error, and its corresponding bound is used as threshold. Compared with the FD method without considering the constraints, the proposed FD scheme provides a smaller threshold and characterizes a larger set of faults, which can be detected. Finally, simulation results are presented to illustrate the benefits of the proposed FD scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

Fault Detection Based On Online Probability Density Function Estimation

This study presents a new fault detection scheme based on the probability density function (PDF) of system output. Unlike the classical fault detection and diagnosis methods, in the proposed method, distribution of the system output is estimated online. To achieve this goal, an algorithm is introduced to estimate PDF online using fuzzy logic. Furthermore, convergence of this algorithm is investigated. Then, a residual is constructed that can show the existence of a fault in the system. The main advantages of the proposed method are robustness against measurement noise, even though it does not need the exact model and measured data of inputs and states. Simulation results show that this scheme can detect abrupt faults very well.     

质子交换膜燃料电池系统数字孪生故障诊断模型研究

基于数字孪生的平行故障诊断方法通过检测和评估真实系统与数字孪生系统之间的残差进行故障诊断,相关数字孪生体基于质子交换膜燃料电池动力学模型和数据集合建立.如果残差向量超过故障检测阈值,则利用故障残差的相对敏感度执行故障隔离.本文将平行故障诊断方法引入质子交换膜燃料电池系统,构建了基于数字孪生估计器的平行故障诊断模型.仿真...     

一类基于非线性状态观测器的鲁棒故障检测

本文提出了一种新的基于非线性状态 观测器的鲁棒故障诊断策略．该方法在传统故障检测滤波器（FDF）的基础上,针对一类满 足Lipshitz条件的仿射非线性系统,构造了非线性故障检测滤波器,给出了故障检测增益阵 的设计算法及其闭环观测误差系统稳定性的证明,解决了非线性系统的故障可检测性问题． 在残差决策阶段,采用模糊自适应门限的判决方法,提高了故障检测的鲁棒性．最后,针对 歼击机结构故障的仿真,验证了本文方法的有效性．     

Small oscillation fault detection for a class of nonlinear systems with output measurements using deterministic learning

Early detection of small faults is an important issue in the literature of fault diagnosis. In this paper, for a class of nonlinear systems with output measurements, an approach for rapid detection of small oscillation faults is presented. Firstly, locally accurate approximations of unknown system dynamics and fault functions are achieved by combining a high gain observer and a deterministic learning (DL) theory. The obtained knowledge of system dynamics for both normal and fault modes is stored in constant RBF networks. Secondly, a bank of dynamical estimators are constructed for all the normal mode and oscillation faults. The knowledge obtained through DL is reused with a nonhigh-gain design. The occurrence of a fault can be detected if one of residual norms of a fault estimator becomes smaller than that of the normal estimator in a finite time. A rigorous analysis of the detectability properties of the proposed fault detection scheme is also given, which includes the fault detectability condition and the fault detection time. The attractions of the paper lie in that with output measurements, the knowledge of modeling uncertainty and nonlinear faults is obtained and then is utilized to enhance the sensitivity to small faults.     

Structured residual vector-based approach to sensor fault detection and isolation

This paper proposes a novel approach to detection and isolation of faulty sensors in multivariate dynamic systems. After formulating the problem of sensor fault detection and isolation in a dynamic system represented by a state space model, we develop the optimal design of a primary residual vector for fault detection and a set of structured residual vectors for fault isolation using an extended observability matrix and a lower triangular block Toeplitz matrix of the system. This work is, therefore, a vector extension to the earlier scalar-based approach to fault detection and isolation. Besides proposing a new algorithm for consistent identification of the Toeplitz matrix from noisy input and output observations without identifying the state space matrices {A, B, C, D} of the system, the main contributions of this newly proposed fault detection and isolation scheme are: (1) a set of structured residual vectors is employed for fault isolation; (2) after determination of the maximum number of multiple sensors that are most likely to fail simultaneously, a unified scheme for isolation of single and multiple faulty sensors is proposed; and (3) the optimality of the primary residual vector and the structured residual vectors is proven. We prove the advantage of our newly proposed vector-based scheme over the existing scalar element-based approach for fault isolation and illustrate its practicality by simulated and experimental evaluation on a multivariate pilot scale, computer interfaced system.     

基于自适应阈值与扩张状态滑模观测器的AUV执行机构故障检测与估计

作为自主式水下机器人(AUV)的重要组成部分,执行机构的可靠性对系统的安全运行具有重要意义.本文以AUV六自由度模型为基础,提出了一种基于自适应阈值与扩张状态滑模观测器相结合的故障检测与估计机制.首先,本文将模型中除去控制输入的部分扩张成新的系统状态,得到估计值和实际值之间的残差;其次,针对执行机构的未知扰动,文章设计了一种改进的自适应阈值以监测残差的变化,进一步降低了误诊率与漏诊率;随后,文章在扩张状态的结构基础上设计滑模观测器,将观测器的增益求解转化为线性矩阵不等式(LMI)约束优化问题;最后,通过动态滑模面的设计实现了抖振的抑制并论证了该动态滑模面的收敛性,同时引入等效控制输出误差注入原理,实现了AUV执行机构的故障重构.仿真结果表明,本文所提方法对AUV执行机构的故障具有较好的检测灵敏度和估计精度.     

Distributed fault diagnosis for process and sensor faults in a class of interconnected input–output nonlinear discrete-time systems

This paper presents a distributed fault diagnosis scheme able to deal with process and sensor faults in an integrated way for a class of interconnected input–output nonlinear uncertain discrete-time systems. A robust distributed fault detection scheme is designed, where each interconnected subsystem is monitored by its respective fault detection agent, and according to the decisions of these agents, further information regarding the type of the fault can be deduced. As it is shown, a process fault occurring in one subsystem can only be detected by its corresponding detection agent whereas a sensor fault in a subsystem can be detected by either its corresponding detection agent or the detection agent of another subsystem that is affected by the subsystem where the sensor fault occurred. This discriminating factor is exploited for the derivation of a high-level isolation scheme. Moreover, process and sensor fault detectability conditions characterising quantitatively the class of detectable faults are derived. Finally, a simulation example is used to illustrate the effectiveness of the proposed distributed fault detection scheme.     

Fault detection for linear distributed-parameter systems using finite-dimensional functional observers

In this article, finite-dimensional residual generators are directly designed for Riesz-spectral systems with bounded input and output operators to detect faults. This is achieved by using finite-dimensional observers, that can estimate linear functionals of the state without spillover. These observers allow for a decoupling of the unknown disturbances from the estimation error dynamics under mild assumptions. Then, a finite-dimensional residual generator is obtained by approximately decoupling the state from the residual, that is generated by the observer states and the outputs. It is shown that the resulting approximation error can be made small by increasing the observer order. Then, fault detection with the finite-dimensional residual generator can be assured by introducing a time-varying threshold. A faulty Euler–Bernoulli beam with structural damping illustrates the proposed finite-dimensional fault detection approach.     

飞控系统传感器故障诊断研究

研究故障检测和诊断技术对提高系统可靠性具有重要意义,针对飞控系统中常见的传感器故障,提出了基于神经网络预测器的故障诊断方法。利用传感器输出时间序列构造神经网络预测器模型,网络结构使用多层感知器结构,根据网络输出和实际输出之差与某·阈值的大小比较关系判断故障。最后针对某型飞机建立仿真模型,并对单一及多个传感器故障诊断进行研究,给出了仿真实现结果,并加以分析。仿真结果表明,所提出的基于神经网络预测器的故障诊断方法是行之有效的,能够及时准确地确定故障的发生。