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介绍了一种基于经验模式分解(Empirical Mode Decomposition,EMD)与粒子群优化算法相结合的飞机结构模态参数辨识方法。一个复杂的脉冲响应信号利用EMD方法使得耦合在一起的多阶模态响应信号分解为与各单阶模态响应信号一一对应的分量,得到前几阶主要的内禀模式函数(Intrinsic Mode Function,IMF),再对分解得到的每一单阶IMF利用粒子群算法辨识得到各阶模态参数。试验仿真结果表明该方法有较高的计算精度,可应用于结构运行模态分析,为飞机等结构设计、运行检测提供有力保障。
A method for identifying modal parameters of aircraft structures based on the combination of empirical mode decomposition (EMD) and particle swarm optimization (PSO) is presented. A complex impulse response signal uses the EMD method to decompose the coupled multi-order modal response signals into components corresponding to the single-order mode response signals to obtain the first few intrinsic Intrinsic Mode Functions , IMF), and then use the Particle Swarm Optimization (PSO) algorithm to identify the modal parameters for each single-order IMF. The experimental results show that the proposed method has high calculation accuracy and can be applied to the analysis of structural modalities of operation to provide effective protection for structural design and operation testing of aircraft.