摘要
针对普通粒子滤波器在非线性系统随机系统故障诊断中的'退化'现象和估计精度的不足,进而影响诊断准确率的问题,提出应用U-粒子滤波器(Unscented particle filter,UPF)进行改进的方法。在建立正常/异常UPF滤波器模型的基础上,推导基于UPF的似然概率密度函数和似然比(Log likelihood ratio,LLR)计算方法,构造故障的检测律和诊断律,并给出完整的故障诊断算法,不仅能准确预报故障发生的时刻,而且可以诊断出故障的类型。最后在某直升机非线性舵回路上进行了试验验证,结果证明了该方法的有效性和优越性。
As for the problem of fault diagnosis of nonlinear system in non-Ganssian noises, a new method based on the unscented particle filter（UPF） is proposed, concerning of the shortcoming of degeneracy and estimation precision of generic particle filter, Firstly, normal/abnormal UPF models are established separately, and the calculation method of likelihood probability density function and log likelihood ratio are deducted. Then, the fault detection and diagnosis rule are given, which can forecast both the happening time and type of the fault. At last, some experiments of nonlinear actuator loop of helicopter are carried out, which can demonstrate the validity and superiority of the proposed method.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2007年第10期27-31,共5页
Journal of Mechanical Engineering
基金
国家自然科学基金(50375153)
维修工程预先研究(413270303)资助项目。
关键词
U-粒子滤波器
似然比
故障诊断
非线性
非高斯
Unscented particle filter Log likelihood ratio Fault diagnosis Nonlinear Non-Gaussian
