基于量子天牛群算法的高桩码头横向排架结构损伤识别
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Damage identification of high-piled wharf’s lateral bent structure based on quantum beetle swarm optimization algorithm
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    摘要:

    针对高桩码头损伤识别问题,引入量子行为优化天牛群(BSO)算法,利用结构模态参数(固有频率和振型)的差别构造目标函数,提出了一种基于量子天牛群(QBSO)算法的损伤识别方法。采用所提方法对一高桩码头模型单直桩、单叉桩的单损伤,双直桩、双叉桩、直桩+叉桩的双损伤进行了计算,并与天牛群(BSO)算法与粒子群(PSO)算法进行对比;对振型添加噪声后单叉桩的单损伤进行了计算。结果表明:所提方法计算效率高、收敛速度快,具有较强的稳定性和抗噪性,能够快速精准地识别出损伤位置与损伤程度。

    Abstract:

    Aiming at the problem of damage identification of high piled-wharf,the paper introduces the quantum behavior optimization BSO(beetle swarm optimization),constructs the objective function by using the difference of structural modal parameters (natural frequency and mode shape),and proposes a damage identification method based on the QBSO (quantum beetle swarm optimization)algorithm.The single damage of single straight pile or single fork pile,double damage of double straight pile,double fork pile or straight pile+fork pile in a high piled-wharf model are calculated by the proposed method,and compared with BSO algorithm and PSO(particle swarm optimization) algorithm;the single damage of single fork pile after adding noise to vibration mode shape is calculated.The results show that the proposed method can identify the location and degree of damage quickly and accurately,with high computational efficiency,fast convergence speed,good stability and noise resistance.

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胥松奇,周世良,皮东衢.基于量子天牛群算法的高桩码头横向排架结构损伤识别[J].水运工程,2020(8):91-99.

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  • 在线发布日期: 2020-08-12
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