摘要
为了在线监测运行工况和提高其可靠性,研究了液压伺服系统的实时故障诊断模型和方法。使用强跟踪滤波器联合估计系统的状态和未知时变参数,使用修正的贝叶斯算法检测故障和估计出故障的幅值,从而建立故障诊断模型和实现液压伺服系统的实时故障诊断。仿真结果证实了模型的合理性和可行性,参数估计误差小于1.2%。该方法对模型参数的不确定性具有较强的鲁棒性,能正确检测和分离液压伺服系统的故障。
In order to online monitor running condition and to improve reliability,a real time fault diagnostic model and a methodology of hydraulic servo systems were studied.Modeling and online diagnosis of hydraulic servo systems were realized by estimating unknown time-varying parameters and system status with strong tracking filter,and by detecting fault and estimating fault magnitude using modified Bayes algorithm.Simulation results show that the model is correct and feasible,and that parameter estimation error is less than 1.2%.Hydraulic servo system fault can be detected and isolated correctly by this way,which has strong robustness against uncertainty of model parameters.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2009年第23期7553-7556,共4页
Journal of System Simulation
基金
国家自然科学基金(60721003)
关键词
液压伺服系统
故障诊断
强跟踪滤波器
参数估计
hydraulic servo systems
fault diagnosis
strong tracking filter
parameters estimation
