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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。
Aiming at the problem of aircraft landing gear damage identification, an improved particle filter method is proposed to identify the landing gear damage. Firstly, the dynamic model of the landing gear was established, the dangerous point of the landing gear was analyzed, and the stress response signal was obtained. Then, the kernel smoothing technique and fast Gaussian sampling method were used to estimate the state and parameters of the nonlinear system, The parameter particle depletion during filtering resampling increases the real-time performance of the method. The experimental results show that the improved particle filter can accurately identify the dangerous point damage of the landing gear, and the recognition accuracy is better than the traditional particle filter.