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Multi-swarm fruit fly optimization algorithm for structural damage identification

机译:多群果蝇优化算法在结构损伤识别中的应用

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摘要

In this paper, the Multi-Swarm Fruit Fly Optimization Algorithm (MFOA) is presented for structural damage identification using the first several natural frequencies and mode shapes. We assume damage only leads to the decrease of element stiffness. The differences on natural frequencies and mode shapes of damaged and intact state of a structure are used to establish the objective function, which transforms a damage identification problem into an optimization problem. The effectiveness and accuracy of MFOA are demonstrated by three different structures. Numerical results show that the MFOA has a better capacity for structural damage identification than the original Fruit Fly Optimization Algorithm (FOA) does.
机译:在本文中,提出了多群果蝇优化算法(MFOA),该算法使用前几个固有频率和振型来识别结构损伤。我们假设损坏只会导致单元刚度的降低。结构的损坏状态和完整状态的固有频率和众数形状的差异用于建立目标函数,从而将损坏识别问题转化为优化问题。 MFOA的有效性和准确性由三种不同的结构来证明。数值结果表明,MFOA具有比原始果蝇优化算法(FOA)更好的结构损伤识别能力。

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