风力机系统基于H_/H∞未知输入观测器的故障诊断

针对实际工程中风力机传动系统未知输入难以完全解耦的问题,提出基于H_-/H_∞未知输入观测器(unknown input observer, UIO)故障诊断方法.首先,利用未知输入观测器的等式条件将未知输入分解为可解耦与不可解耦两部分,且将可解耦部分从估计误差中消除.其次,利用H_-/H_∞性能指标设计未知输入观测器的残差产生器,使残差对未知输入中不可解耦部分具有鲁棒性并对故障信号具有敏感性,并通过引入松弛矩阵解决观测器参数设计过程中的保守问题.考虑残差信号的随机特性,采用统计理论确定故障检测阈值.经仿真验证,该方法可对风力机传动系统传感器加性故障和乘性故障进行有效诊断.     

基于未知输入观测器的导弹间歇故障诊断

针对带有未知扰动和噪声的导弹间歇故障诊断问题,设计了一种基于未知输入观测器的导弹问题故障诊断方法,系统的输入部分或全部未知情况下也能获取系统状态的称为未知输入观测器.首先,为实现对外部扰动的解耦,设计降维未知输入观测器,并通过滑动时间窗口得到对间歇故障敏感而对未知扰动解耦的残差信号;然后,在满足误报率和漏报率的条件下,通过假设检验,确定了间歇故障发生时刻和消失时刻的可检测阈值;最后,对所提出的方法进行了仿真验证.仿真结果表明,在误差允许的范围内,设计的方法能够实现对间歇故障检测,满足实时性和准确性的要求.     

基于未知输入观测器的非线性系统故障诊断

针对一类含未知输入和执行器故障的非线性系统,提出基于未知输入观测器的故障诊断算法,改进了Luenberger故障诊断观测器对系统出现未知扰动时的不足.利用广义逆方法,将未知输入从残差信号中完全解耦,通过产生对故障高敏感性以及对未知扰动强抗扰动性的观测器实现系统的故障诊断,并通过Lyapunov函数用线性矩阵不等式保证了系统稳定性.     

单区域负荷频率控制系统故障诊断研究

针对一类包含有干扰的负荷频率控制系统,提出一种利用未知输入观测器(UIO,unknown inputobserver)对单区域负荷频率控制系统执行机构进行故障诊断的方法.首先通过构建单区域负荷频率控制系统模型,给出系统的动态方程;其次,通过对系统中的加性未知干扰项进行解耦,构造一个使残差对未知输入具有鲁棒性,而对故障敏感的全阶未知输入观测器,以达到对执行器故障诊断的目的.最后通过Matlab仿真验证了所设计方法的正确性和可行性.     

含未知输入观测器的广义系统故障诊断

基于未知输入观测器设计和故障诊断的概念,讨论含未知输入的Lipschitz条件下非线性广义系统传感器故障诊断问题。在非线性广义系统中,通过引入传感器的故障信号,重新构造非线性广义系统,设计基于未知输入观测器,在满足Lipschitz条件下,实现了传感器故障的检测与分离。给出数值仿真算例验证该算法的有效性。     

一种基于最优未知输入观测器的故障诊断方法

针对含有未知输入干扰和噪音的不确定动态系统,使用全阶未知输入观测器(Unknown input observer, UIO)来消除干扰项,实现状态估计, 结合Kalman滤波器算法来求解状态反馈矩阵,以使得输出残差信号的协方差最小,从而增强系统对噪声的鲁棒性,实现了 一种基于最优未知输入观测器的残差产生器.采用极大似然比(Generalized likelihood ratio, GLR)的方法对残差信号进行评估,通过设定的阈值来提高诊断率. 最后以风力发电机组传动系统出现加性传感器故障和乘性传感器故障为例, 进行了残差信号的仿真,仿真结果说明了该方法的有效性.     

线性时滞系统故障检测滤波器设计H∞优化方法

研究一类线性时滞系统的基于观测器的故障检测滤波器设计问题.通过对线性时滞系统进行广义坐标变换,得到了只包含输入、输出时滞,无状态时滞的新的系统表达形式.在此基础上,选用基于观测器的故障检测滤波器作为残差产生系统,使得到的残差动态方程为仅包含未知输入时滞和故障时滞的线性时不变形式,进而可应用已取得的线性时不变系统故障诊断研究成果设计故障检测滤波器.同时给出一种线性时滞系统故障检测滤波器设计的H∞优化设计方法,并通过算例验证了所提方法的有效性.     

一类存在参数摄动的线性随机系统的鲁棒间歇故障诊断方法

间歇故障（Intermittent faults, IFs）具有随机性,其检测要求在本次间歇故障消失之前检测出间歇故障的发生,在下一次间歇故障发生之前检测出间歇故障的消失.本文针对一类存在未知时变参数摄动的离散线性随机动态系统,研究了其鲁棒间歇故障检测与分离问题.基于降维未知输入观测器,通过引入滑动时间窗口,本文设计了一组与未知时变摄动解耦的结构化截断残差,并提出其存在的一个充分条件.与传统残差相比,截断残差信号更为显著地反映了间歇故障的发生和消失.为满足间歇故障的检测要求,本文提出两个假设检验分别用于检测间歇故障的发生时刻和消失时刻,并给出了一个详细算法.最后,在沿参考轨道运行的卫星模型上对所述方法进行了仿真实验,结果表明该方法能够有效检测出间歇故障的所有发生时刻和消失时刻,并准确实现故障分离.     

基于广义回归神经网络的传感器故障诊断研究

针对诊断传感器偏置故障与漂移故障的难点问题,提出了一种基于广义回归神经网络(GRNN)的传感器故障诊断方法。该方法充分利用控制系统闭环回路测控信息,建立一组多输入单输出GRNN观测器,通过将观测器输出与传感器实际输出相比较获取残差序列,获得基于残差序列的传感器偏置故障和漂移故障的辨识策略,实现控制系统传感器故障在线诊断。仿真结果表明:该方法可以快速准确地检测和分离传感器故障,辨识传感器故障类型、故障大小以及故障发生的时间。     

故障检测滤波器鲁棒性设计新方法

针对航空发动机动态过程中由于模型误差造成故障检测误报的问题,采用参数变化率法建立航空发动机动态线性变参数(LPV)数学模型反映发动机动态特性,同时结合全维非线性未知输入观测器,利用特征结构配置实现故障检测滤波器对于被控对象模型误差和系统不确定性因素的干扰解耦.通过某型涡扇发动机控制系统传感器故障检测仿真表明,减小残差信号与故障信号之间的误差,提高了残差信号对模型误差和未知输入信号的鲁棒性,对发动机过渡过程中故障检测准确度高,实时性好.     

风力发电系统传感器故障诊断

针对非线性风力发电系统,提出了一种基于滑模观测器的传感器故障诊断方法.基于考虑传感器加性故障的非线性动态模型,利用T--S模糊理论建立风力发电系统全局T--S模型,设计模糊T--S系统滑模故障观测器,产生对故障具有敏感性的残差,实现故障检测.通过等价输出控制方法来维持滑模运动,直接获取故障信息,重构传感器故障.最后以三叶片水平轴风力发电系统为例,仿真验证了该方法的有效性与可靠性.     

Design of unknown input functional observers for nonlinear systems with application to fault diagnosis

This paper considers the design of low-order unknown input functional observers for robust fault detection and isolation of a class of nonlinear Lipschitz systems subject to unknown inputs. The proposed functional observers can be used to generate residual signals to detect and isolate actuator faults. By using the generalized inverse approach, the effect of the unknown inputs can be decoupled completely from the residual signals. Conditions for the existence and stability of reduced-order unknown input functional observer are derived. A design procedure for the generation of residual signals to detect and isolate actuator faults is presented using the proposed unknown-input observer-based approach. A numerical example is given to illustrate the proposed fault diagnosis scheme in nonlinear systems subject to unknown inputs.     

Fault detection in wind turbine transmission systems via finite frequency observers

This paper addresses fault detection for wind turbine transmission system (WTTS) subject to actuator stuck faults and wind disturbances. Taking into account the frequency domain characteristics of such faults and disturbances, a modified observer is designed in terms of finite frequency (FF) performance indices that have detection performances superior to some formerly proposed ones. With the generalized Kalman–Yakubovich–Popov (GKYP) lemma and the Lyapunov theory, the FF performance indices are related to linear matrix inequalities (LMIs), and parametrization of the corresponding FF modified observer is completed by convex optimization under LMI constraints. One typical advantage of the modified observer is that fault and disturbance signals in distinctive FF domains can be dealt with simultaneously. This makes the residual system sensitive to actuator stuck faults and robust against external wind disturbances. Simulations are included to show that the design method achieves fault detection performances better than those of the entire frequency observers.     

基于深度置信网络风电机组变桨系统的故障诊断

针对风电机组变桨系统常见故障,提出一种基于深度置信网络(DBN)的故障诊断方法。设计出基于DBN的变桨系统故障诊断框架;通过堆叠多层受限玻尔兹曼机(RBM),对比重构数据与原始输入数据差异,研究了DBN故障特征自提取能力;将堆叠RBM提取的故障特征输入到顶层分类器中进行训练,得到故障诊断模型;最后采用风场真实故障数据集进行了验证测试。实验结果表明,采用该方法进行风电机组变桨系统故障诊断相比其他方法具有更高的准确率。     

Unknown Input Fault Detection and Isolation Observer Design for Neutral Systems

This paper deals with actuator fault diagnosis of neutral delayed systems with multiple time delays using an unknown input observer. The main purpose is to design an observer that guarantees the asymptotic stability of the estimate error dynamics and the actuator fault detection. The existence conditions for such an observer are established. The main problem studied in this paper aims at designing observer‐based fault detection and isolation. The designed observer enhances the robust diagnosis performance, including rapidity and accuracy, and generates residuals that enjoy perfect decoupling properties among faults. Based on Lyapunov stability theory, the design of the observer is formulated in terms of linear matrix inequalities, and the diagnosis scheme is based on a bank of unknown input observers for residual generation that guarantees fault detection and isolation in the presence of external disturbances. A numerical example is presented to illustrate the efficiency of the proposed approach.     

Designing fault detection observers for linear systems with mismatched unknown inputs

Algebraic unknown input observers (UIOs) that have been previously reported in the literature can be constructed under the assumption that linear systems with unknown inputs satisfy the so-called observer matching condition. This condition restricts practical applications of UIOs for fault detection and isolation (FDI). We present an algebraic design for fault detection observers (FDOs) for the case in which the observer matching condition is not satisfied. To loosen the restriction imposed by the observer matching condition, the UIO design method combined with the unknown input modeling technique is proposed to design an FDO that decouples the effect of mismatched unknown inputs. To do this, first, unknown inputs that denote the faults of no interest and process disturbances are decomposed into algebraically rejectable unknown inputs and modeled unknown inputs such that the observer matching condition is satisfied. Under the assumption that mismatched unknown inputs are deterministic and can be expressed as the responses of fictitious autonomous dynamical systems, an augmented system is obtained by combining the original system model with the unknown input model. Finally, through the design technique of a UIO for the augmented system, a reduced-order FDO is constructed to estimate an augmented state vector that consists of both the original state variables and the augmentative state variables. The estimated state is then used to generate the residual, which should be designed to be insensitive to unknown inputs while being sensitive to the faults of interest. Two numerical examples are provided to show the usefulness and the feasibility of the presented approach.     

Fault Detection and Isolation Method Based on H−/H∞ Unknown Input Observer Design in Finite Frequency Domain

This paper proposes an actuator fault detection and isolation strategy based on a bank of unknown input observers with finite frequency specifications. In order to deal with actuator fault diagnosis problem, a bank of H _?/H _∞ unknown input observers are designed to generate residuals, which are insensitive to the corresponding faults but sensitive to the other actuators faults, and meanwhile robust against the unknown disturbances. In this paper, the actuator faults and unknown disturbances are considered to belong to finite frequency domains, and two finite frequency performance indices are used to measure the fault sensitivity and the disturbance robustness of the residuals. Furthermore, some parameters for extra design of freedom are introduced in the H _?/H _∞ unknown input observers design. Based on the generalised Kalman‐Yakubovich‐Popov (GKYP) lemma, the design conditions of the H _?/H _∞ unknown input observer are derived and formulated as linear matrix inequalities (LMIs). Finally, a VTOL aircraft model is used to demonstrate the performance of the proposed fault diagnosis scheme.     

UIO design for singular delayed LPV systems with application to actuator fault detection and isolation

In this paper, the unknown input observer (UIO) design for singular delayed linear parameter varying (LPV) systems is considered regarding its application to actuator fault detection and isolation. The design procedure assumes that the LPV system is represented in the polytopic framework. Existence and convergence conditions for the UIO are established. The design procedure is formulated by means of linear matrix inequalities (LMIs). Actuator fault detection and isolation is based on using the UIO approach for designing a residual generator that is completely decoupled from unknown inputs and exclusively sensitive to faults. Fault isolation is addressed considering two different strategies: dedicated and generalised bank of observers’ schemes. The applicability of these two schemes for the fault isolation is discussed. An open flow canal system is considered as a case study to illustrate the performance and usefulness of the proposed fault detection and isolation method in different fault scenarios.     

基于Matlab的风机传动链数据采集与分析系统设计与应用

基于Matlab和NI cDAQ的风机状态监测设备能快速方便地对风机传动链实现准确的故障检测。提出一种先进的风机传动链数据采集和分析系统,该系统中数据采集任务在后台运行,在保证完整准确采集的基础上实现了实时示波和自定义录波,可同步获得风机传动链的振动数据和齿轮箱输出轴转速数据,为故障检测提供有效、完整的数据,可从时间域、频率域、周期域和阶次域自定义分析,识别故障特征,为风机状态监测提供故障信息依据。该系统功能丰富、自定义程度高、系统响应快,可准确检测风机故障。