Article(id=1276896679697715544, tenantId=1146029695717560320, journalId=1276577754012160025, issueId=1276896661737701828, articleNumber=null, orderNo=null, doi=10.3724/j.gyjzG26022502, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1771948800000, receivedDateStr=2026-02-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1782365492033, onlineDateStr=2026-06-25, pubDate=1779206400000, pubDateStr=2026-05-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1782365492033, onlineIssueDateStr=2026-06-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1782365492033, creator=13701087609, updateTime=1782365492033, updator=13701087609, issue=Issue{id=1276896661737701828, tenantId=1146029695717560320, journalId=1276577754012160025, year='2026', volume='56', issue='5', pageStart='1', pageEnd='264', issueExtLink='null', onlineDate='null', pubDate='1779206400000', pubDateStr='2026-05-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1782365487751, creator='13701087609', updateTime=1782367237543, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1276904000968589318, tenantId=1146029695717560320, journalId=1276577754012160025, issueId=1276896661737701828, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1276904000968589319, tenantId=1146029695717560320, journalId=1276577754012160025, issueId=1276896661737701828, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=14, endPage=28, ext={EN=ArticleExt(id=1276896679970345306, articleId=1276896679697715544, tenantId=1146029695717560320, journalId=1276577754012160025, language=EN, title=Research Progress on Diagnosis and Treatment for Building External Thermal Insulation Composite System, columnId=null, journalTitle=Industrial Construction, columnName=null, runingTitle=null, highlight=null, articleAbstract=
The external thermal insulation composite system (ETICS) is crucial for improving building energy efficiency and ensuring building functionality. In recent years, issues such as cracking, hollowing, peeling, and high-altitude falling have occurred frequently, posing a significant threat to public safety. A systematic review was conducted on domestic and international research and engineering practice regarding diagnosis and treatment methods for detection, evaluation, and repair of building ETICS. In terms of detection, non-destructive testing techniques were categorized into four types based on their energy forms and physical mechanisms, namely optical, thermal, electromagnetic, and acoustic. The research progress of various non-destructive testing techniques and commonly used destructive testing techniques was systematically reviewed. A comparative analysis was conducted on the technical points, advantages and disadvantages, and applicable scenarios of various detection techniques. In terms of evaluation, the characteristics and progress of existing evaluation methods were summarized from three aspects: qualitative evaluation, quantitative evaluation, and comprehensive evaluation. In terms of repair, the current development status of existing repair methods was introduced from the perspectives of repair technology, repair materials, and repair strategies. Finally, the deficiencies in the research and engineering practice regarding diagnosis and treatment methods for building ETICS were analyzed, and future research directions were discussed.
, authors=null, authorsList=Youlu HUANG, Qingfeng XU, Zhuolin WANG, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1276896683711664485, articleId=1276896679697715544, tenantId=1146029695717560320, journalId=1276577754012160025, language=CN, title=建筑外墙外保温系统诊治研究进展, columnId=1276896662844998087, journalTitle=工业建筑, columnName=工程诊治与运维理论方法, runingTitle=null, highlight=null, articleAbstract=
建筑外墙外保温系统是提升建筑节能和保障建筑功能的关键,近年来常出现开裂、空鼓、剥落和高空坠落等问题,严重影响公众安全。系统梳理了国内外建筑外墙外保温系统诊治在检测、评估与修复方面的研究与工程实践进展:在检测方面,基于能量形式和物理作用机制,将无损检测技术分为光学、热学、电磁学和声学分析四类,系统梳理了各类无损检测技术以及常用破损检测方法的研究进展,对比分析了各类检测技术的技术要点、优缺点和适用场景;在评估方面,从定性评估、定量评估和综合评估三方面总结了现有评估方法的特点与进展;在修复方面,从修复技术、修复材料和修复方案等方面介绍了现有修复方法的发展现状。最后,对建筑外墙外保温系统诊治研究和工程实践存在的不足进行了分析,并对后续的研究方向进行了展望。
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121: 105986., articleTitle=A novel fuzzy group decision-making approach based on CCSD method for thermal insulation board selection problem: a case study, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1276896684403724647, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, xref=1, ext=[AuthorCompanyExt(id=1276896684407918952, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, companyId=1276896684403724647, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
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1上海市建筑科学研究院有限公司,上海市工程结构安全重点实验室,上海200032)])], figs=[ArticleFig(id=1276896689860514180, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=EN, label=Fig.1, caption=
Crack recognition method based on deep learning algorithm, figureFileSmall=LV22HPnMxJQYKChoj1ULzg==, figureFileBig=hfIWPRn0WqCfdqNvJ0+BeA==, tableContent=null), ArticleFig(id=1276896689961177477, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=CN, label=图1, caption=
基于深度学习算法的裂缝识别方法[12], figureFileSmall=LV22HPnMxJQYKChoj1ULzg==, figureFileBig=hfIWPRn0WqCfdqNvJ0+BeA==, tableContent=null), ArticleFig(id=1276896691722785158, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=EN, label=Fig.2, caption=
Schematic diagram of the fusion framework for infrared and visible images, figureFileSmall=9zyL8pvnkxlg9IITx+9MVQ==, figureFileBig=TWmZ9oJA1VEhO9L0ifrgKA==, tableContent=null), ArticleFig(id=1276896691961860487, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=CN, label=图2, caption=
红外与可见光图像融合框架示意[47], figureFileSmall=9zyL8pvnkxlg9IITx+9MVQ==, figureFileBig=TWmZ9oJA1VEhO9L0ifrgKA==, tableContent=null), ArticleFig(id=1276896692028969352, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=EN, label=Fig.3, caption=
Defect recognition method based on ground-penetrating radar, figureFileSmall=D2QZFYR8euq5nBsYXdirWg==, figureFileBig=1WZAEtcDaJU1w9co4kM//Q==, tableContent=null), ArticleFig(id=1276896692104466825, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=CN, label=图3, caption=
基于探地雷达的缺陷识别方法[56], figureFileSmall=D2QZFYR8euq5nBsYXdirWg==, figureFileBig=1WZAEtcDaJU1w9co4kM//Q==, tableContent=null), ArticleFig(id=1276896692171575690, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=EN, label=Fig.4, caption=
Defect recognition process based on ultrasonic method, figureFileSmall=9DSLaB7OxKf/BITBRu3bZw==, figureFileBig=DPgGgde3ZElUf7YrNxaMZg==, tableContent=null), ArticleFig(id=1276896692381290891, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=CN, label=图4, caption=
基于超声波法的缺陷识别过程[72], figureFileSmall=9DSLaB7OxKf/BITBRu3bZw==, figureFileBig=DPgGgde3ZElUf7YrNxaMZg==, tableContent=null), ArticleFig(id=1276896692452594060, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=EN, label=Table 1, caption=
Comparative analysis of detection methods for building ETICS
, figureFileSmall=null, figureFileBig=null, tableContent=
| 类型 | 名称 | 优点 | 缺点 | 适用范围 |
|---|
| 光学 | 可见光成像法 | 非接触;支持大范围自动检测 | 结果受环境因素影响大;仅能检测表面缺陷 | 裂缝、剥落、霉变等表观缺陷检测 |
| 点云技术 | 可获得毫米级精度的三维模型 | 设备昂贵;对保温层内部缺陷不敏感 | 外墙整体或局部变形测量 |
| 热学 | 红外热像法 | 非接触;支持大范围自动检测;能可视化隐蔽的空鼓及渗水区域 | 结果受环境因素影响大;难以确定缺陷深度 | 剥落、内部空鼓、渗水、保温层厚度不均等缺陷检测 |
| 电磁学 | 探地雷达法 | 可探测内部结构;能估算缺陷深度与范围 | 设备昂贵;结果易受墙体内部金属构件影响 | 内部空鼓、锚栓位置等缺陷检测 |
| 康普顿背散射法 | 对保温层等低密度材料敏感 | 设备昂贵;涉及放射性源,安全要求极高 | 保温层密度均匀性、空鼓等检测 |
| 声学 | 叩诊法 | 成本低;支持大范围自动检测 | 难以检测深层或小面积缺陷 | 浅层空鼓检测 |
| 超声波法 | 对内部小缺陷敏感 | 超声波在非均质材料中衰减快 | 内部细小裂缝、空洞等检测 |
| 冲击回波法 | 结果比纯声学方法更客观 | 需要传感器与表面良好耦合;表面粗糙度影响大 | 内部空鼓检测 |
| 破损 | 钻芯取样法 | 结果直观可靠;芯样可用于测定抗压强度等性能指标 | 事后需修复;效率低;抽样难以反映整体状况 | 系统构造验证;材料性能检测 |
| 拉拔法 | 能量化黏结强度;通过破坏模式可确定失效位置 | 事后需修复;效率低;抽样难以反映整体状况 | 黏结强度评估;失效机理诊断 |
| 局部剥离法 | 结果直观可靠 | 事后需修复;效率低;抽样难以反映整体状况 | 有效黏结面积等施工工艺详查 |
), ArticleFig(id=1276896692528091533, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=CN, label=表1, caption=
建筑外墙外保温系统检测方法对比分析
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| 类型 | 名称 | 优点 | 缺点 | 适用范围 |
|---|
| 光学 | 可见光成像法 | 非接触;支持大范围自动检测 | 结果受环境因素影响大;仅能检测表面缺陷 | 裂缝、剥落、霉变等表观缺陷检测 |
| 点云技术 | 可获得毫米级精度的三维模型 | 设备昂贵;对保温层内部缺陷不敏感 | 外墙整体或局部变形测量 |
| 热学 | 红外热像法 | 非接触;支持大范围自动检测;能可视化隐蔽的空鼓及渗水区域 | 结果受环境因素影响大;难以确定缺陷深度 | 剥落、内部空鼓、渗水、保温层厚度不均等缺陷检测 |
| 电磁学 | 探地雷达法 | 可探测内部结构;能估算缺陷深度与范围 | 设备昂贵;结果易受墙体内部金属构件影响 | 内部空鼓、锚栓位置等缺陷检测 |
| 康普顿背散射法 | 对保温层等低密度材料敏感 | 设备昂贵;涉及放射性源,安全要求极高 | 保温层密度均匀性、空鼓等检测 |
| 声学 | 叩诊法 | 成本低;支持大范围自动检测 | 难以检测深层或小面积缺陷 | 浅层空鼓检测 |
| 超声波法 | 对内部小缺陷敏感 | 超声波在非均质材料中衰减快 | 内部细小裂缝、空洞等检测 |
| 冲击回波法 | 结果比纯声学方法更客观 | 需要传感器与表面良好耦合;表面粗糙度影响大 | 内部空鼓检测 |
| 破损 | 钻芯取样法 | 结果直观可靠;芯样可用于测定抗压强度等性能指标 | 事后需修复;效率低;抽样难以反映整体状况 | 系统构造验证;材料性能检测 |
| 拉拔法 | 能量化黏结强度;通过破坏模式可确定失效位置 | 事后需修复;效率低;抽样难以反映整体状况 | 黏结强度评估;失效机理诊断 |
| 局部剥离法 | 结果直观可靠 | 事后需修复;效率低;抽样难以反映整体状况 | 有效黏结面积等施工工艺详查 |
), ArticleFig(id=1276896692595200398, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=EN, label=Table 2, caption=
Classification of performance degradation levels for ETICS
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| Sw取值范围/% | 等级 | 描述 |
|---|
| Sw≤1 | A | 未改变 |
| 1<Sw≤10 | B | 良好 |
| 10<Sw≤30 | C | 轻微退化 |
| 30<Sw≤50 | D | 中等退化 |
| Sw>50 | E | 严重退化 |
), ArticleFig(id=1276896692662309263, tenantId=1146029695717560320, journalId=1276577754012160025, articleId=1276896679697715544, language=CN, label=表2, caption=
外保温系统性能退化等级划分
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| Sw取值范围/% | 等级 | 描述 |
|---|
| Sw≤1 | A | 未改变 |
| 1<Sw≤10 | B | 良好 |
| 10<Sw≤30 | C | 轻微退化 |
| 30<Sw≤50 | D | 中等退化 |
| Sw>50 | E | 严重退化 |
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