摘要
针对飞机起落架损伤识别问题,提出了一种识别起落架损伤的改进粒子滤波方法。首先,建立了飞机起落架动力学模型,分析起落架损伤的危险点,得到其应力响应信号;然后,采用核平滑技术和快速高斯采样法,实现非线性系统中状态与参数估计,解决了粒子滤波重采样过程中的参数粒子枯竭现象,增加了该方法运行的实时性。实验信号分析结果表明,改进粒子滤波方法能准确识别飞机起落架危险点损伤,识别精度优于传统粒子滤波方法。
An improved particle filter method is proposed for improving damage identification of the aircraft landing gear.First,we establish landing gear model and analyze its dangerous point to obtain the stress signal.Then,kernel smoothing technology and fast Gaussian sampling method are used to estimate the states and parameters of nonlinear system.This method can accurately identify the landing gear damage.The experimental results and their analysis confirm preliminarily that the proposed method outperforms the traditional method.
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
2013年第3期397-400,共4页
Journal of Northwestern Polytechnical University
基金
国家自然科学基金(50975231)资助
关键词
飞机起落架
改进粒子滤波
核平滑技术
快速高斯采样法
损伤识别
damage detection
flowcharting
landing gear(aircraft)
mathematical models
nonlinear systems
parameter estimation
state estimation
fast Gaussian sampling method
improved particle filter
kernel smoothing