建筑外墙外保温层缺陷检测与识别研究  

Research on Defect Detection and Recognition of ExternalThermal Insulation Layer of Building Exterior Wall

作　　者：崔译丹 孙永 Cui Yidan;Sun Yong(Yunnan Vocational College of Land and Resources,Kunming 652501,China)

机构地区：[1]云南国土资源职业学院,昆明652501

出　　处：《黑龙江科学》2024年第24期57-60,共4页Heilongjiang Science

基　　金：云南省教育厅科学研究基金项目“高烈度设防地区社区抗震韧性评估研究”(2023J611)。

摘　　要：为完善建筑外墙外保温层缺陷定量检测与识别方法,基于红外热像技术缺陷检测原理,通过预制缺陷试验分析了裂缝、空鼓缺陷的红外热像图特征,确定了两种缺陷的适宜检测环境,提出引入SE-Block并替换激活函数的网络模型,试验验证该模型对裂缝、空鼓缺陷分别具有97.89%、97.25%的识别准确率,证明其对建筑外墙外保温层缺陷识别的有效性。此结果为建筑外墙外保温层维护提供了技术参考,为深度学习在缺陷识别领域的应用提供了理论支撑。In order to improve the quantitative detection and identification method of building exterior insulation layer defects,based on the defect detection principle of infrared thermal imaging technology,the study analyzes the infrared and thermal image characteristics of cracks and hollow defects with prefabricated defect test,determines the suitable detection environment of two kinds of defects,and proposes a network model that introduces SE-Block and replaces the activation function.The test verifies that the model has 97.89%and 97.25%recognition accuracy for cracks and hollowing defects,respectively,which proves its effectiveness in identifying defects in the external thermal insulation layer of building exterior walls.This study can not only provide technical reference for the maintenance of building exterior insulation layer,but also provide theoretical support for the application of deep learning in defect recognition.

关 键 词：外保温层 红外热像 缺陷检测 识别 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TU761.12[自动化与计算机技术—计算机科学与技术]