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Research on the performance of GMCBO methodology based on model updating of a pedestrian bridge
Mechanical Systems and Signal Processing ( IF 7.9 ) Pub Date : 2024-06-28 , DOI: 10.1016/j.ymssp.2024.111686
Zhiyuan Xia , Huiyuan Shi , Baijian Tang , You Wang , Xin Chen , Sheng Gu

Consider the loss of diversity of the bodies at the later optimization stage and the low efficiency of the global searching ability of the traditional colliding bodies optimization algorithm in dealing with complex optimization issues of practical structures. Herein, an improved colliding bodies optimization method combing Gaussian-white-noise mutation and innovative collision mode is proposed. The introduction of Gaussian-white-noise is mutating the positions of the selected bodies and enriching the diversity during the whole optimization process. The changed collision mode from ‘one to one’ to ‘one to best’ is accelerating the process to global extremum. During searching the global extremums of the 12 test functions which are unimodal, multimodal and multimodal with fix dimension, the proposed shows relatively better accuracy and efficiency. The comparison based on the maximum, minimum, average, standard deviation and non-parametric Wilcoxon test of the optimization results by the above algorithms confirmed the outstanding performance of the proposed method. Through the application of the proposed method to the model updating of a pedestrian bridge, all the differences of the first five frequencies between the measured vibration data and finite element model are reduced from approximate 25% to nearly 5%, and the updated dynamic characteristics show great agreement with the practical structure. From the comparison of the responses between updated model and human-induced vibration experiment, most of the response differences are around 10%. The application of the above real structure further verifies that the proposed method is feasible and strongly recommended in optimization issues of practical structures.

中文翻译:


基于人行天桥模型更新的GMCBO方法性能研究



考虑到传统碰撞体优化算法在处理实际结构的复杂优化问题时,优化后期物体多样性的损失以及全局搜索能力的低效率。在此,提出了一种结合高斯白噪声突变和创新碰撞模式的改进碰撞体优化方法。高斯白噪声的引入使所选物体的位置发生变异,丰富了整个优化过程的多样性。从“一对一”到“一对一”的碰撞模式正在加速走向全球极值的过程。在搜索单峰、多峰和定维多峰12个测试函数的全局极值时,该方法表现出相对较好的精度和效率。上述算法的优化结果基于最大值、最小值、平均值、标准差和非参数Wilcoxon检验的比较证实了该方法的优异性能。通过将该方法应用到人行天桥的模型更新中,实测振动数据与有限元模型的前5个频率的差异均从约25%减少到近5%,更新后的动态特性表明与实际结构非常吻合。从更新模型与人致振动实验的响应对比来看,大部分响应差异在10%左右。上述实际结构的应用进一步验证了该方法的可行性,强烈推荐用于实际结构的优化问题。
更新日期:2024-06-28
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