【作者】 杨建平；

【导师】 张建华；

【作者基本信息】 华北电力大学（北京） ， 控制理论与控制工程， 2004， 硕士

【摘要】 本文总结了非线性系统传感器故障诊断的方法，讨论了非线性滤波在故障诊断中的应用。针对机炉非线性系统的传感器故障，本文提出了三种基于非线性滤波的故障诊断方案。在协调对象数学模型已知的情况下，分别用扩展卡尔曼滤波和隐性卡尔曼滤波实现了传感器故障诊断的算法。文中分析了算法的原理、实现过程以及对各种传感器故障的检测和辨识效果，讨论了算法的敏感性、鲁棒性和稳定性，并对这两种算法进行了仿真比较。其中隐性卡尔曼滤波算法实现了对渐变型传感器故障的检测和多输入多输出、强耦合系统传感器故障的隔离，仿真结果表明算法有较好的鲁棒性和稳定性。在协调系统模型未知的情况下，用拉格里自适应滤波器对系统进行在线辨识，设计了传感器故障诊断算法，并应用到锅炉汽机协调系统的传感器故障诊断中，仿真表明该算法能够准确诊断出传感器故障，满足实际的要求。最后对全文的工作进行了总结。更多还原

【Abstract】 The methods of sensor faults diagnosis in nonlinear system are summarized and the application of nonlinear filters in fault diagnosis is discussed in this paper. Three schemes based on nonlinear filter technique are presented to detect sensor faults in boiler-turbine system. When the plant model is known, those algorithms of fault diagnosis are implemented by extended kalman filter and unscented kalman filter respectively. The principle and implementation process of algorithms are described, and the effect of identification and detection to multiple sensor faults are analyzed. In addition, the sensitivity, robustness and stability of these algorithms are also discussed and the difference between two kinds of algorithms are given by simulation experiment. Unscented filter can be used to detect incipient faults, isolate sensor faults in MIMO and intense coupling system. Simulation results show it’s robust and stable. When the model is unknown, adaptive laguerre filter is designed to identify the plant online. Then the scheme of fault diagnosis is applied to detect sensor faults in boiler-turbine system. Simulation results show the algorithm can properly detect the faults in the system and meet the demand of production. Finally, the overall work is summarized.更多还原