建筑结构学报2026，Vol.47Issue(4)：37-49,13.DOI:10.14006/j.jzjgxb.2025.0445
基于小波时频图与卷积神经网络的高层建筑结构损伤定位
Structural damage localization in high-rise buildings based on wavelet time-frequency diagrams and convolutional neural networks
摘要
Abstract
Story-level damage localization for high-rise building structures is of great significance for ensuring their operational safety.Therefore,a multi-label classification damage localization method based on wavelet time-frequency diagrams and convolutional neural networks was proposed.Firstly,a dual attention mechanism was introduced based on the VGG16 architecture to construct a lightweight improved model VBAG-Net,which enhanced the learning ability for sensitive features of damage.Secondly,damage experiments for a semi-prefabricated steel frame-core tube model was designed and completed where structural damage was simulated by disassembling wall components,establishing a benchmark database for story-level damage identification in high-rise structures.The one-dimensional vibration signals were converted into two-dimensional time-frequency diagrams using the continuous wavelet transform(CWT)and synchrosqueezed wavelet transform(SWT)as the model input,respectively.Finally,the VBAG-Net was trained and tested based on this dataset,and compared with several mainstream CNN models.The results show that VBAG-Net achieved exact match ratio of 98.48%(CWT)and 98.86%(SWT)on the test set.It still maintains excellent performance even when varying the time-segment length of vibration signals for time-frequency diagram generation.The comprehensive identification effect and robustness are significantly superior to the comparative models,verifying the effectiveness of this method in locating story-level damage in high-rise buildings.关键词
高层建筑/损伤定位/卷积神经网络/多标签分类/小波时频图Key words
high-rise building/damage localization/convolutional neural networks/multi-label classification/wavelet time-frequency diagrams分类
建筑与水利引用本文复制引用
仇华华,王翠坤,陈才华,崔明哲,赵鹏飞..基于小波时频图与卷积神经网络的高层建筑结构损伤定位[J].建筑结构学报,2026,47(4):37-49,13.基金项目
国家重点研发计划(2022YFC3002300),中国建筑科学研究院有限公司关键共性技术研发项目(20251902970730016). （2022YFC3002300）
