摘要
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。
The method based on empirical mode decomposition and particle swarm optimization combined aircraft modal parameter identification is presented.A complex impulse response signal using EMD method makes the coupling of multi-modal response signal decomposition with the single-modal response signals correspond,to get the first steps by major intrinsic mode function.Decomposition again be used in every single order IMF PSO can be identified by the modal parameters.Test results show that the method has high accuracy,it an be used in operational modal analysis of structures.for the aircraft and other structures provide effective protection.
出处
《飞机设计》
2011年第2期13-15,共3页
Aircraft Design
关键词
经验模态分解
粒子群优化
内禀模式函数
参数辨识
empirical mode decomposition（EMD）
particle swarm optimization（PSO）
intrinsic mode function
parameter identification
