混凝土重力坝水下爆炸毁伤快速识别方法研究

李麒1,2,3,王高辉2,卢文波2,钮新强1,顾冲时3

振动与冲击 ›› 2020, Vol. 39 ›› Issue (24) : 46-53.

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振动与冲击 ›› 2020, Vol. 39 ›› Issue (24) : 46-53.
论文

混凝土重力坝水下爆炸毁伤快速识别方法研究

  • 李麒1,2,3,王高辉2,卢文波2,钮新强1,顾冲时3
作者信息 +

A rapid identification method for underwater explosion damage of a concrete gravity dam

  • LI Qi1,2,3,WANG Gaohui2,LU Wenbo2,NIU Xinqiang1,GU Chongshi3
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摘要

传统的损伤识别技术很难实现混凝土重力坝水下爆炸毁伤位置及范围的快速识别。通过基于Python的ABAQUS二次开发,批量建立不同毁伤状态下混凝土重力坝有限元模型并进行模态分析的批量计算,构造单损伤、两损伤及三损伤时大坝频率数据库。利用粒子群(PSO)寻优建立了基于支持向量回归机(SVR)的重力坝毁伤识别模型,并通过大坝频率数据库检验集样本评估该模型的识别精度。考虑不同噪声水平对毁伤识别效果的影响,评估了SVR模型对大坝毁伤识别的抗噪性能。结果表明:通过PSO-SVR模型可以准确识别重力坝毁伤位置及毁伤范围,同时该模型具有良好的抗噪性能。

Abstract

The rapid identification of damage location and range of dams subjected to underwater explosion is difficult to realize using traditional damage identification technology.Through the secondary development of ABAQUS based on Python, the batch establishment of a finite element model and the batch calculation of modal analysis under different damage conditions were realized.The frequency databases of gravity dams at different damage locations and ranges were constructed.Particle swarm optimization (PSO) was used to find the optimal training parameters of single and multiple damage identification of dams via a support vector regression (SVR) model, and the model was validated by the test samples of the frequency database.Considering the influence of different noise levels on damage identification, the reliability of SVR models for dam damage identification was evaluated.The results show that the PSO-SVR model can accurately identify the damage location and radius of gravity dams, and the model has good anti-noise performance.

关键词

混凝土重力坝 / 毁伤识别 / 粒子群算法 / 支持向量机 / 抗噪性能

Key words

concrete gravity dam / damage identification / particle swarm optimization(PSO) / support vector regression(SVR) / anti-noise performance

引用本文

导出引用
李麒1,2,3,王高辉2,卢文波2,钮新强1,顾冲时3. 混凝土重力坝水下爆炸毁伤快速识别方法研究[J]. 振动与冲击, 2020, 39(24): 46-53
LI Qi1,2,3,WANG Gaohui2,LU Wenbo2,NIU Xinqiang1,GU Chongshi3. A rapid identification method for underwater explosion damage of a concrete gravity dam[J]. Journal of Vibration and Shock, 2020, 39(24): 46-53

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