Active fault detection based on set‐membership approach for uncertain discrete‐time systems

Active fault detection facilitates determination of the fault characteristics by injecting proper auxiliary input signals into the system. This article proposes an observer‐based on‐line active fault detection method for discrete‐time systems with bounded uncertainties. First, the output including disturbances, measurement noise and interval uncertainties at each sample time is enclosed in a zonotope. In order to reduce the conservativeness in the fault detection process, a zonotopic observer is designed to estimate the system states allowing to generate the output zonotopes. Then, a proper auxiliary input signal is designed to separate the output zonotopes of the faulty model from the healthy model that is injected into the system to facilitate the detection of small fault . Since the auxiliary input signal generation leads to a nonconvex optimization problem, it is transformed into a mixed integer quadratic programming problem. Finally, a case study based on a DC motor is used to show the effectiveness of the proposed method.     

Active fault detection and isolation of discrete-time linear time-varying systems: a set-membership approach

Active fault detection and isolation (AFDI) is used for detection and isolation of faults that are hidden in the normal operation because of a low excitation signal or due to the regulatory actions of the controller. In this paper, a new AFDI method based on set-membership approaches is proposed. In set-membership approaches, instead of a point-wise estimation of the states, a set-valued estimation of them is computed. If this set becomes empty the given model of the system is not consistent with the measurements. Therefore, the model is falsified. When more than one model of the system remains un-falsified, the AFDI method is used to generate an auxiliary signal that is injected into the system for detection and isolation of faults that remain otherwise hidden or non-isolated using passive FDI (PFDI) methods. Having the set-valued estimation of the states for each model, the proposed AFDI method finds an optimal input signal that guarantees FDI in a finite time horizon. The input signal is updated at each iteration in a decreasing receding horizon manner based on the set-valued estimation of the current states and un-falsified models at the current sample time. The problem is solved by a number of linear and quadratic programming problems, which result in a computationally efficient algorithm. The method is tested on a numerical example as well as on the pitch actuator of a benchmark wind turbine.     

Active fault detection for open loop stable LTI SISO systems

Active fault detection for a stable open-loop LTI SISO system is considered. The optimal active fault detection setup is developed around an estimator based architecture. The auxiliary signal and estimator are then designed in order to maximize detection performance. Equations are derived which relate the estimator design to the nominal residual signal covariance. The relationship between the auxiliary input and the system performance degradation constraint is considered. The effect of estimator gain and excitation signal frequency on the dual Youla-Jabr-Bongiorno-Kucera parameter is investigated. Finally, the effect of the excitation signal frequency on detector performance is investigated, and a minimum targeted detection time parameter is introduced. This set of equations are then used to minimise the fault detection time for fixed performance constraints and minimum targeted detection time.     

基于SαS分布参数估计的系统鲁棒故障检测

因为复杂系统难以建立精确的数学模型,基于模型的故障检测方法在实际复杂控制系统中应用时往往难以获得很好的效果。针对这类数学模型未知的非线性系统,提出了一种基于SαS分布参数估计的系统故障检测方法。首先应用预测方法对系统输出序列进行预测建模,利用预测误差放大信号的脉冲突变,然后利用SαS分布的参数估计方法对预测误差序列的参数α进行估计,获得α的变化曲线,根据α的变化可以直观地判断出故障的发生。该方法对大幅值的有色噪声污染的信号仍然有很好的检测鲁棒性。以轴承系统的故障检测为例进行仿真实验,通过分析轴承振动信号故障条件下α曲线的变化情况,判断轴承的故障状态。仿真结果证实了该方法有效且可行。     

Robust fault detection for networked systems with communication delay and data missing

In this paper, the robust fault detection problem is investigated for a class of discrete-time networked systems with unknown input and multiple state delays. A novel measurement model is utilized to represent both the random measurement delays and the stochastic data missing phenomenon, which typically result from the limited capacity of the communication networks. The network status is assumed to vary in a Markovian fashion and its transition probability matrix is uncertain but resides in a known convex set of a polytopic type. The main purpose of this paper is to design a robust fault detection filter such that, for all unknown inputs, possible parameter uncertainties and incomplete measurements, the error between the residual signal and the fault signal is made as small as possible. By casting the addressed robust fault detection problem into an auxiliary robust H_∞ filtering problem of a certain Markovian jumping system, a sufficient condition for the existence of the desired robust fault detection filter is established in terms of linear matrix inequalities. A numerical example is provided to illustrate the effectiveness and applicability of the proposed technique.     

Fault detection and isolation design for uncertain nonlinear systems based on full-order,reduced-order and high-order high-gain sliding-mode observers

This paper considers the observer-based fault detection and isolation design problems when the observer matching condition is not satisfied. Based on the relative degree concept, an auxiliary output vector that may satisfy the observer matching condition is constructed. Since the auxiliary output vector contains unknown information, we use a high-order high-gain sliding-mode observer to exactly estimate not only the auxiliary outputs, but also their derivatives in a finite time. Then, an adaptive robust full-order observer is developed to serve as an actuator fault detection observer. For the actuator fault reconstruction purpose, a reduced-order observer is proposed to estimate the system states even if there are some actuator faults and an actuator fault reconstruction method is provided to reach the fault isolation purpose. A numerical simulation example is used to illustrate the effectiveness of the proposed methods.     

微小故障下的深空探测航天器闭环主动故障检测

深空探测航天器是发展空间技术、扩展人类探索疆域的重要工具.航天器运行过程中一旦发生故障,极易导致探测活动失败甚至航天器损毁,而对航天器进行早期微小故障诊断,可以有效预防重大故障的发生,对于深空探测活动的顺利进行具有十分重要的意义.本文针对模型参数不确定下的深空探测航天器系统,提出一种闭环主动故障检测方法,实现对微小故障的准确检测.通过设计合适的辅助输入信号,分别注入标称和故障模型系统,使故障系统的输出与标称系统的输出无交集,以达到故障检测的目的.此外,为减小对深空探测航天器系统产生的影响,所设计的辅助信号必须尽可能小.通过对两方面需求的考虑,在传统开环研究的基础上,加入观测器建立闭环系统,在提升对微小故障的检测能力的同时减小对系统的影响.最后,利用深空探测航天器的数学仿真验证了所提闭环方法对微小故障的检测能力,并与传统开环方法进行了对比,结果表明闭环辅助信号具有更优的性能.     

控制系统传感器增益故障的一种鲁棒诊断方法

本文基于状态观测器，提出了一种模型含有不确定性误差情况下，传感器增益漂移故障的诊断与分离方法。作者通过一个辅助系统产生故障特征信号，然后采用拟合的方法，从观测器残差中提取出故障信息，从而实现故障的诊断与分离。     

基于CPCI总线的航天器通信信号设备故障检测系统设计

针对当前航天器通信信号设备故障检测系统受到噪声影响,导致系统通信设备故障信号检测精准度低,检测时间长的问题,设计基于CPCI总线的航天器通信信号设备故障检测系统;CPCI故障模拟模块利用RS232串行线控制注入机,采用故障注入器执行故障注入CPCI总线,接收控制系统参数和指令,使用时钟分配芯片传输时钟信号,通过CPCI检测板卡模块,配合FPGA实现接口控制,完成系统硬件结构设计,利用任务间相互依赖关系,实现任务间相互检测,通过终端网工作站定期发送多路通信网相关信息,返回无疵点检测结果,采用二次相关算法,提取多通道通信故障信号详细信息,准确估算通信信号时延,排除多通道网络噪声影响造成的通信故障,完成系统软件部分设计;实验结果表明,基于CPCI总线的故障检测系统的故障信号检测时间仅为1.8 s,故障信号幅度最大为28 dB,最小为1 dB,与实际变化幅度一致,通信设备故障信号检测精准度较高,能够有效缩短通信设备故障信号检测时间。     

Optimal piecewise-constant signal design for active fault detection

Recently there has been an increasing interest in active fault detection when traditional approaches are not effective or cannot be used. Previous papers have shown how to construct continuously varying test (auxiliary) signals for use in fault detection and identification. Such signals may not always be easy to implement. In this paper a new algorithm is presented to compute optimal piecewise constant test signals. In the important case where the test signal changes values a small number of times, the new test signals can be both smaller and more effective than test signals computed by other means. Two computational examples are given to illustrate both computational issues and differences between different types of piecewise constant signals.     

FDI by extended Kalman filter parameter estimation for an industrial actuator benchmark

The extended Kalman filter (EKF) is formulated as a parameter estimator and used to estimate position sensor bias and actuator current bias signals for the industrial actuator benchmark system. These bias estimates are compared instantaneously to a threshold for fault detection and identification (FDI). The paper reports results for applying this method to given benchmark data. The FDI performance is good for detecting position sensor and actuator current faults in the presence of unmodeled nonlinear dynamics and an unmodeled load change for small-amplitude signal conditions when the EKF implementation assumes parameter pseudonoise and a slow decay in the parameter dynamics. For large-amplitude signals, the results are reasonably good, but they suggest that a more accurate model for a saturation nonlinearity could improve the method's FDI performance.     

一种基于小波网络的故障检测方法

本文针对突变故障给出了一种基于小波网络的检测方法。故障检测方法一般分为两种：一种是基于信号分析；而另一种是基于过程的数学模型。本文给出了一种基于小波网络的故障检测方法，它具有信号分析，数学模型两者优点，从而更准确地检测出突变故障。     

Fault detection for discrete-time networked nonlinear systems with incomplete measurements

This article addresses the problem of fault detection (FD) for discrete-time networked systems with global Lipschitz nonlinearities and incomplete measurements, including time delays, packet dropouts and signal quantisation. By utilising a discrete-time homogeneous Markov chain, an improved model which considers packet dropout compensation has been proposed to describe the above network-induced phenomena. We aim to design a mode-dependent fault detection filter (FDF) such that the FD system is asymptotically mean-square stable and satisfies a prescribed attenuation level. The addressed FD problem is then converted into an auxiliary H _∞ filtering problem of Markov jump system with time-varying delay. A sufficient condition for the existence of the FDF is derived in terms of certain linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of the desired FDF can also be characterised. A numerical example is exploited to show the effectiveness of the results obtained.     

发电机励磁碳刷运行故障检测方法

针对发电机励磁系统中碳刷结构故障检测困难,故障定位不准确的问题,本文根据实际碳刷运行过程建立碳刷结构检测系统。通过建立组件对象模型(Component Object Model COM)动态检测方案将碳刷结构模型化,使系统能够更为精确的检测到故障原因。设计数字式光纤传感器(BF5R)检测电路将碳刷故障过程图像化,缩短系统检测时间。通过改进维格纳威尔分布(Wigner Ville distribution WVD)故障定位算法精准定位碳刷故障位置,采用合理方式进行维修。通过Proteus软件仿真检测系统运行过程,实验表明本设计对碳刷故障检测具有明显效果,在15KW发电机环境中,碳刷故障定位时间为3.5min,信号幅值为13V,结果精确度为96.4%,证实了本设计的可行性;通过仿真对比三种不同系统信号检测幅值电压和检测准确度曲线,由此验证了本研究的优越性。     

Distributed fault detection over sensor networks with Markovian switching topologies

This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.     

基于递推参数辨识的齿轮箱故障在线检测

为实现齿轮箱故障的在线检测,提出基于递推AR模型参数辨识的齿轮箱振动信号在线辨识方法。对实验室的齿轮箱进行不同工况下振动信号的检测,利用最优辅助变量法确定其自回归模型的阶次和模型参数的初值,以自回归模型系数作为状态变量,采用Kalman滤波器技术进行在线递推参数辨识。实验结果表明,该方法中参数变化量的2-范数会发生突变,能检测出齿轮磨损和轴承外圈剥落的故障。     

基于辅助输入信号和冗余执行器的主动故障诊断

针对具有模型不确定项的系统,提出一种辅助信号结合冗余执行器的主动故障检测方法来检测微小故障.首先,以提升故障灵敏度和抗干扰鲁棒性为指标,构建最优观测器得到残差信号;其次,引入辅助输入信号来增大故障系统的残差,同时构建冗余执行器来避免辅助输入信号对无故障系统的影响;然后,给出随模型不确定项变化的自适应阈值构建方法降低故障检测的保守性.所提出的主动故障检测方法对无故障系统不造成影响,当故障发生时残差迅速变化且高于阈值以实现快速检测.最后通过仿真对比验证了所提出方法的有效性.     

基于联合压缩感知重构的网络通信故障检测系统设计

针对当前故障检测系统检测网络通信故障信号时存在不精准的问题,设计了基于联合压缩感知重构的网络通信故障检测系统。结合联合压缩感知理论,设计系统总体结构。选用光时域反射仪F7高端电信级光缆故障光纤测试仪OTDR作为系统硬件,依据工作原理,判断通信网络传输特性,设置菜单按钮,缩放、等比、还原检测出的波形。采用AD8066型号低噪声放大器,设计电流电压转换电路,在反馈电阻两端并联一个电容以抑制噪声,并利用单色驱动器24-40W激光驱动器为激光电源提供电流,使脉冲信号转换为电信号。在J2SE平台下,设计中心服务功能,通过激光驱动发射正脉冲,使格雷互补码偏置到峰值的一半左右,实现格雷互补码在OTDR中应用,依据系统检测流程,完成网络通信故障检测。系统性能测试结果表明,基于联合压缩感知重构检测系统对网络通信故障信号检测结果较为精准,误差最大为0.3dB,为网络运行维护奠定基础。     

Robust Unknown Input Observer Design for Linear Uncertain Time Delay Systems with Application to Fault Detection

In this paper, a novel approach is proposed to design a robust fault detection observer for uncertain linear time delay systems. The system is composed of both norm‐bounded uncertainties and exogenous signals (noise, disturbance, and fault) which are considered to be unknown. The main contribution of this paper is to present unknown input observer (UIO)‐based fault detection system which shows the maximum sensitivity to fault signals and the minimum sensitivity to other signals. Since the system contains uncertainty terms, an H_∞ model‐matching approach is used in design procedure. The reference residual signal generator system is designed so that the fault signal has maximum sensitivity while the exogenous signals have minimum sensitivity on the residual signal. Then, the fault detection system is designed by minimizing the estimation error between the reference residual signal and the UIO residual signal in the sense of H_∞ norm. A sufficient condition for the existence of such a filter is exploited in terms of certain linear matrix inequalities (LMIs). Application of the proposed method in a numerical example and an engineering process are simulated to demonstrate the effectiveness of the proposed algorithm. Simulation results show the validity of the proposed approach to detect the occurrence of faults in the presence of modeling errors, disturbances, and noise.