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作 者:郝付军[1] HAO Fujun(International Transport School,Shaanxi Vocational Institute of Railway Engineering Technology,Weinan 714099,Shaanxi,China)
机构地区:[1]陕西铁路工程职业技术学院国际交通学院,陕西渭南714099
出 处:《噪声与振动控制》2022年第4期121-126,137,共7页Noise and Vibration Control
基 金:国家自然科学基金资助项目(51908144);陕西省渭南市科研计划资助项目(2019ZDYF-JCYJ-129)。
摘 要:为合理评价桥梁现有运营状况,以桥梁变形监测成果为基础,先通过极限位移准则构建变形程度分级指标,以实现对桥梁变形程度的评价;其次,利用经验模态分解、核极限学习机和混沌理论构建基于变形数据信息分解基础上的预测模型,以实现其变形预测;最后,通过对比变形程度评价结果和变形预测分析结果,综合判断桥梁运营状况。实例分析表明:某桥梁变形程度已相对较大,变形程度等级为Ⅳ级,变形趋于向稳定方向发展;同时,通过变形预测分析可得该预测模型具有较高的预测精度,其预测结果的平均相对误差均小于2%,且外推预测结果显示,桥梁变形具有小速率增加趋势,也趋于向稳定方向发展。因此,综合两者分析结果,得出该桥梁变形已趋于稳定,运营状况良好的结论。The operation conditions of the existing bridges are evaluated reasonably.Based on the results of bridge deformation monitoring,the deformation degree classification index is constructed through the limit displacement criterion to realize the evaluation of bridge deformation degree.Then,the prediction model based on the information decomposition of the deformation data is constructed by using empirical mode decomposition,kernel limit learning machine and chaos theory to realize the deformation prediction.Finally,by comparing the results of deformation degree evaluation and deformation prediction analysis,the bridge operation status can be comprehensively judged.A case study of an existing bridge shows that the bridge deformation degree is relatively large and up to grade IV,and the deformation development tends to stable.At the same time,through the deformation prediction analysis,the prediction model is found to have a high prediction accuracy,and the average relative error of the prediction results is less than 2%.The extrapolation prediction results show that the bridge deformation has a small rate of increase trend,and also tends to a stable development.Therefore,based on the analysis results of the two methods,it is concluded that the bridge deformation tends to stable and the operation condition is good.
关 键 词:振动与波 桥梁 变形程度 变形预测 核极限学习机 混沌理论
分 类 号:U446[建筑科学—桥梁与隧道工程]
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