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
1.Changjiang Institute of Survey, Planning, Design and Research, Wuhan 430010, China;
2.State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;
3.College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
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.
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. JOURNAL OF VIBRATION AND SHOCK, 2020, 39(24): 46-53.
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