河北工业科技2025，Vol.42Issue(5)：436-443,8.DOI:10.7535/hbgykj.2025yx05005
基于K-SVD字典学习与ResNet的混凝土结构损伤识别
Damage identification of concrete structures based on K-SVD dictionary learning and ResNet
摘要
Abstract
To address the issues of low signal-to-noise ratio,high background noise,and non-stationarity in detecting concrete structure source signals based on piezoelectric wave method,a piezoelectric signal filtering method based on K-singular value decomposition(K-SVD)to update the dictionary was proposed,and the damage of concrete structures were identified.Firstly,piezoelectric signals from concrete structures in both cracked and intact states were collected and classified.Secondly,the acquired piezoelectric signals were filtered,and the the results using the K-SVD dictionary learning method were compared and analyzed with the unfiltered results to evaluate the applicability of the K-SVD dictionary learning filtering method.Finally,the filtered piezoelectric signals using ResNet were classified and recognized.The results show that the method based on K-SVD dictionary learning and ResNet can stably identify the piezoelectric signals of internal damage in concrete structures.The accuracy of damage signal recognition in training set and test set is 93.25%and 92.38%,respectively.The recognition accuracy of lossless signal is 95.41%and 94.67%,respectively,which is more than 10 percentage points higher than that of unfiltered signal.The effective damage identification in concrete bridge structures through the integration of K-SVD dictionary learning and ResNet has achieved the localization of internal damage areas in the concrete structures.The research findings present a novel approach to data processing in the health monitoring of concrete bridge structures.关键词
混凝土与钢筋混凝土结构/压电波动法/K-SVD/ResNet/损伤识别Key words
concrete and reinforced concrete structures/piezoelectric wave method/K-SVD/ResNet/damage identification分类
建筑与水利引用本文复制引用
李红心,陈宗刚,韩松..基于K-SVD字典学习与ResNet的混凝土结构损伤识别[J].河北工业科技,2025,42(5):436-443,8.基金项目
中国电建集团西北勘测设计研究院有限公司重大科技项目(XBY-ZDKJ-2021-06) （XBY-ZDKJ-2021-06）
