Research Progress on Diagnosis and Treatment for Building External Thermal Insulation Composite System

HUANG Youlu; XU Qingfeng; WANG Zhuolin

doi:10.3724/j.gyjzG26022502

Volume 56 Issue 5

May 2026

Turn off MathJax

Article Contents

Article Navigation > INDUSTRIAL CONSTRUCTION > 2026 > 56(5): 14-28

HUANG Youlu, XU Qingfeng, WANG Zhuolin. Research Progress on Diagnosis and Treatment for Building External Thermal Insulation Composite System[J]. INDUSTRIAL CONSTRUCTION, 2026, 56(5): 14-28. doi: 10.3724/j.gyjzG26022502

Citation:

HUANG Youlu, XU Qingfeng, WANG Zhuolin. Research Progress on Diagnosis and Treatment for Building External Thermal Insulation Composite System[J]. INDUSTRIAL CONSTRUCTION, 2026, 56(5): 14-28. doi: 10.3724/j.gyjzG26022502

Citation:

PDF( 1188 KB)

Research Progress on Diagnosis and Treatment for Building External Thermal Insulation Composite System

doi: 10.3724/j.gyjzG26022502

1. Shanghai Key Laboratory of Engineering Structure Safety, Shanghai Research Institute of Building Sci. Co., Ltd., Shanghai 200032, China

Received Date: 2026-02-25
Available Online: 2026-06-06
Publish Date: 2026-05-20

Abstract

Abstract

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.
- external thermal insulation composite system,
- detection,
- evaluation,
- repair,
- research progress

FullText(HTML)

References(156)

References

[1]	XU H T，WANG H，HUO Q N，et al. Comparative study of Chinese，European and ISO external thermal insulation composite system（ETICS）standards and technical recommendations［J］. Journal of Building Engineering，2023，68：105687.
[2]	中华人民共和囯住房和城乡建设部. 外墙外保温工程技术标准：JGJ 144—2019［S］. 北京：中国建筑工业出版社，2019.
[3]	CHEW M Y L，SAMARAKOON W，ASMONE A S. Tile delamination on facades of tall buildings［J］. Buildings，2025，15（7）：1054.
[4]	RUIZ F，AGUADO A，SERRAT C，et al. Condition assessment of building facades based on hazard to people［J］. Structure and Infrastructure Engineering，2019，15（10）：1346- 1365.
[5]	CHEW M Y，GAN V J. Long-standing themes and future prospects for the inspection and maintenance of facade falling objects from tall buildings［J］. Sensors，2022，22（16）：6070.
[6]	AMARO B，SARAIVA D，BRITO J D，et al. Inspection and diagnosis system of ETICS on walls［J］. Construction and Building Materials，2013，47：1257- 1267.
[7]	MASRI Y，RAKHA T. A scoping review of non-destructive testing（NDT）techniques in building performance diagnostic inspections［J］. Construction and Building Materials，2020，265：120542.
[8]	ZHANG Y S，CHOW C L，LAU D. Artificial intelligence-enhanced non-destructive defect detection for civil infrastructure［J］. Automation in Construction，2025，171：105996.
[9]	JIA K，LIU H C，DU W X，et al. Advances，applications and prospects of laser thermography nondestructive testing and evaluation：a review［J/OL］. Nondestructive Testing and Evaluation，2025［2026-02-25］. https://doi.org/10.1080/10589759.2025.2533389.
[10]	中国工程建设标准化协会. 既有外墙外保温工程检测与评价标准：T/ CECS 1675—2024［S］. 北京：中国建筑工业出版社，2024.
[11]	GUO J J，LIU P K，XIAO B，et al. Surface defect detection of civil structures using images:review from data perspective［J］. Automation in Construction，2024，158：105186.
[12]	夏子祺，马临原，单伽锃，等. 基于计算机视觉的建筑外墙剥落和裂缝两阶段检测方法［J］. 建筑结构学报，2023，44（2）：207- 216.
[13]	XIANG C，GUO J J，CAO R，et al. A crack-segmentation algorithm fusing transformers and convolutional neural networks for complex detection scenarios［J］. Automation in Construction，2023，152：104894.
[14]	KATSIGIANNIS S，SEYEDZADEH S，AGAPIOU A，et al. Deep learning for crack detection on masonry façades using limited data and transfer learning［J］. Journal of Building Engineering，2023，76：107105.
[15]	CHEN K W，REICHARD G，XU X，et al. Automated crack segmentation in close-range building façade inspection images using deep learning techniques［J］. Journal of Building Engineering，2021，43：102913.
[16]	ZHOU X L，TIONG R L K. Defects inspection system for building facades using drones and deep learning method［J］. Expert Systems with Applications，2026，298：129715.
[17]	GUO J J，WANG Q，LI Y T，et al. Facade defects classification from imbalanced dataset using meta learning-based convolutional neural network［J］. Computer-Aided Civil and Infrastructure Engineering，2020，35（12）：1403- 1418.
[18]	GUO J J，WANG Q，LI Y T，et al. Semi-supervised learning based on convolutional neural network and uncertainty filter for façade defects classification［J］. Computer-Aided Civil and Infrastructure Engineering，2021，36（3）：302- 317.
[19]	GUO J J，WANG Q，LI Y T，et al. Evaluation-oriented façade defects detection using rule-based deep learning method［J］. Automation in Construction，2021，131：103910.
[20]	CUI Z Y，WANG Q，GUO J J，et al. Few-shot classification of façade defects based on extensible classifier and contrastive learning［J］. Automation in Construction，2022，141：104381.
[21]	KARIMI N，MISHRA M，LOURENCO P B. Deep learning-based automated tile defect detection system for Portuguese cultural heritage buildings［J］. Journal of Cultural Heritage，2024，68：86- 98.
[22]	YU S，LI J Y，ZHENG H，et al. Research on predicting building façade deterioration in winter cities using diffusion model［J］. Journal of Building Engineering，2025，111：113365.
[23]	CHENG M Q，MA Z F，XIE J Y，et al. Specific defect detection for efficient building maintenance［J］. Journal of Building Engineering，2025，112：113710.
[24]	齐亚辉，蔺鹏臻. 点云技术在土木工程中的应用现状综述［J/OL］. 工程力学，2025.［2026-02-25］. https://link.cnki.net/urlid/11.2595.O3.20250930.0901.004.
[25]	STALOWSKA P，SUCHOCHI C，RUTKOWSKA M. Crack detection in building walls based on geometric and radiometric point cloud information［J］. Automation in Construction，2022，134：104065.
[26]	BOLOURIAN N，NASROLLAHI M，BAHREINI F，et al. Point cloud-based concrete surface defect semantic segmentation［J］. Journal of Computing in Civil Engineering，2023，37（2）：04022056.
[27]	XU Z，LI S H，LI H，et al. Modeling and problem solving of building defects using point clouds and enhanced case-based reasoning［J］. Automation in Construction，2018，96：40- 54.
[28]	KONG Q Z，GU J X，XIONG B，et al. Vision-aided three-dimensional damage quantification and finite element model geometric updating for reinforced concrete structures［J］. Computer-Aided Civil and Infrastructure Engineering，2023，38（17）：2378- 2390.
[29]	CHEN S H，FAN G，LI J，et al. Automatic complex concrete crack detection and quantification based on point clouds and deep learning［J］. Engineering Structures，2025，327：119635.
[30]	唐寅. 基于四足机器人的三维激光扫描技术在既有房屋检测中的应用研究［J］. 施工技术（中英文），2023，52（3）：35- 38.
[31]	CHOI M Y，KIM S Y，KIM S H. Semi-automated visualization method for visual inspection of buildings on BIM using 3D point cloud［J］. Journal of Building Engineering，2024，81：108017.
[32]	KIRIMTAT，A，KREJCAR O. A review of infrared thermography for the investigation of building envelopes:Advances and prospects［J］. Energy and Buildings，2018，176：390- 406.
[33]	LOURENCO T，MATIAS L，FARIA P. Anomalies detection in adhesive wall tiling systems by infrared thermography［J］. Construction and Building Materials，2017，148：419- 428.
[34]	冯力强，王欢祥，晏大玮，等. 红外热像法检测建筑外墙饰面层内部缺陷试验研究［J］. 土木工程学报，2014，47（6）：51- 56.
[35]	RESENDE M M，GAMBARE E B，SILVA L A，et al. Infrared thermal imaging to inspect pathologies on façades of historical buildings:a case study on the Municipal Market of São Paulo，Brazil［J］. Case Studies in Construction Materials，2022，16：e01122.
[36]	臧科宇，汤民，徐子涵. 无人设备用于外墙薄抹灰保温系统缺陷检测的技术研究［J］. 建设科技，2024（7）：77- 80.
[37]	LU Y C，LIN D M，ZHAI Z Q，et al. Application and improvement of Canny edge-detection algorithm for exterior wall hollowing detection using infrared thermal images［J］. Energy and Buildings，2022，274：112421.
[38]	LI Q X，PENG X，ZHONG X G，et al. Quantitative identification of debonding defects in building façades based on UAV-thermography using a two-stage network integrating dual attention mechanism［J］. Infrared Physics & Technology，2024，138：105241.
[39]	WANG P J，XIAO J Z，QIANG X X，et al. An automatic building façade deterioration detection system using infrared-visible image fusion and deep learning［J］. Journal of Building Engineering，2024，95：110122.
[40]	HUANG Y S，HUNG C C，CHIANG C H. Evaluating effects of glare on the monitoring of building facade health condition by analyzing the infrared thermal images collected under different weather conditions［J］. Infrared Physics & Technology，2025，146：105754.
[41]	HUANG Y S，SHIH P，HSU K T，et al. To identify the defects illustrated on building facades by employing infrared thermography under shadow［J］. NDT & E International，2020，111：102240.
[42]	HUANG Y S，CHEN C L，CHIANG C H. Analyzing a series of thermal infrared images to identify defects using a hybrid approach that combines robust principal component analysis and image segmentation［J］. NDT & E International，2023，137：102818.
[43]	CHEN J，ZHANG S H，ZHAO G，et al. Infrared thermography of facade delamination：quantifying environmental variability and heat transfer mechanisms［J］. Construction and Building Materials，2025，494：143177.
[44]	AGUILAR M，SÁTIRO D，ALVARENGA C，et al. Use of passive thermography to detect detachment and humidity in facades clad with ceramic materials of differing porosities［J］. Journal of Nondestructive Evaluation，2023，42（4）：92.
[45]	MA L Y，XIONG B，KONG Q Z，et al.，Impact of multiple factors on the use of an UAV-mounted infrared thermography method for detection of debonding in facade tiles［J］. Journal of Building Engineering，2024，96：110592.
[46]	MA L T，XU H，ZHAO S X，et al. Hollowing defect detection and risk assessment of facade tile shedding in high-rise residential buildings using the UAV-mounted infrared thermography method［J］. Journal of Building Engineering，2025，113：113840.
[47]	HE S D，ZHAO G，CHEN J，et al. Weakly-aligned cross-modal learning framework for subsurface defect segmentation on building facades using UAVs［J］. Automation in Construction，2025，170：105946.
[48]	PALLARÉS F J，BETTI M，BARTOLI G，et al. Structural health monitoring（SHM）and nondestructive testing（NDT）of slender masonry structures:a practical review［J］. Construction and Building Materials，2021，297：123768.
[49]	LAI W，DEROBERT X，ANNAN P. A review of ground penetrating radar application in civil engineering：a 30-year journey from locating and testing to imaging and diagnosis［J］. NDT & E International，2018，96：58- 78.
[50]	SOLLA M，MATÉ-GONZÁLEZ M，BLÁZQUEZ C，et al. Analysis of structural integrity through the combination of non-destructive testing techniques in heritage inspections:the study case of San Segundo's Hermitage（Ávila，Spain）［J］. Journal of Building Engineering，2024，89：109295.
[51]	GUADAGNUOLO M，FAELLA G，DONADIO A，et al. Integrated evaluation of the Church of S. Nicola di Mira：Conservation versus safety［J］. NDT & E International，2014，68：53- 65.
[52]	YALÇINER Ç，BÜYÜKSARAÇ A，KURBAN Y. Non-destructive damage analysis in Kariye（Chora）Museum as a cultural heritage building［J］. Journal of Applied Geophysics，2019，171：103874.
[53]	PÉREZ-GRACIA V，CASELLES J O，CLAPÉS J，et al. Non-destructive analysis in cultural heritage buildings:Evaluating the Mallorca cathedral supporting structures［J］. NDT & E International，2013，59：40- 47.
[54]	JOHNSTON B，RUFFELL A，MCKINLEY J，et al. Detecting voids within a historical building facade：a comparative study of three high frequency GPR antenna［J］. Journal of Cultural Heritage，2018，32：117- 123.
[55]	ZHANG D B，WANG Z L，SHI H，et al. Application of ground penetrating radar technique in defect detection for external wall thermal insulation system of inorganic thermal insulation mortar［C］// Proceedings of the 6th International Conference on Smart Monitoring，Assessment and Rehabilitation of Civil Structures. Singapore：Springer Nature Singapore，2021：177- 193.
[56]	LI Y H，YANG X P，GONG J B，et al. Intelligent detection of bonding status in external building insulation layers using ground-penetrating radar［J］. Automation in Construction，2025，173：106100.
[57]	CHENG D，ZENG Z，GE W，et al. A novel high-precision imaging radar for quality nspection of building insulation layers［J］. Applied Sciences，2025，15（11）：5991.
[58]	KOLKOORI S，WROBEL N，ZSCHERPEL U，et al. A new X-ray backscatter imaging technique for non-destructive testing of aerospace materials［J］. NDT & E International，2015，70：41- 52.
[59]	LU J，LUO J H，SHU S B，et al. Compton backscattering imaging for wall defect detection：A Geant4 simulation study［J/OL］. Nuclear Science and Engineering，2025［2026-02-25］. https://doi.org/10.1080/00295639.2025.2575420.
[60]	QIN X，YANG J B，DU Z C，et al. Study of a compton backscattering wall defects detection device using the Monte Carlo method［J］. Nukleonika，2023，68（2）：57- 63.
[61]	LUK B L，LIU K P，TONG F，et al. Impact-acoustics inspection of tile-wall bonding integrity via wavelet transform and hidden markov models［J］. Journal of Sound and Vibration，2010，329（10）：1954- 1967.
[62]	LUK B L，LIU K P，TONG F. Rapid evaluation of tile-wall bonding integrity using multiple-head impact acoustic method［J］. NDT & E International，2011，44（3）：297- 304.
[63]	LUK B L，LIU K P，JIANG Z D，et al. Robotic impact-acoustics system for tile-wall bonding integrity inspection［J］. Mechatronics，2009，19（8）：1251- 1260.
[64]	JIANG Z D，LUK B L，LIU K P. Bispectra-based impact acoustic non-destructive evaluation［J］. NDT & E International，2009，42（7）：652- 657.
[65]	TONG F，XU X M，LUK B L，et al. Evaluation of tile-wall bonding integrity based on impact acoustics and support vector machine［J］. Sensors and Actuators A：Physical，2008，144（1）：97- 104.
[66]	LIN T H，CHANG C T，ZHUANG T H，et al. Real-time hollow defect detection in tiles using on-device tiny machine learning［J］. Measurement Science and Technology，2024，35（5）：056006.
[67]	LIN T H，CHIANG P C，PUTRANTO A. Multispecies hybrid bioinspired climbing robot for wall tile inspection［J］. Automation in Construction，2024，164：105446.
[68]	周尹辉，丁勇，吴玉龙，等. 基于特征融合与贝叶斯算法优化SVM的墙面空鼓检测［J］. 中国安全科学学报，2025，35（11）：131- 138.
[69]	ITO A，KOIKE M，SAITO M，et al. Hammering test for tile wall using deep learning［J］. Applied Sciences，2025，15（3）：1500.
[70]	JI K Y，SONG Z G，YE Z X，et al. Understanding of tile hollow sound［J］. Journal of Sound and Vibration，2026，620：119462.
[71]	计柯妍，孔庆钊. 基于三维弹性理论修正的建筑外立面瓷砖空鼓声振弱耦合分析模型［J/OL］. 东南大学学报（自然科学版），2025［2026-02-25］. https://link.cnki.net/urlid/32.1178.N.20251224.1057.002.
[72]	KUCHIPUDI S T，GHOSH D. Automated detection and segmentation of internal defects in reinforced concrete using deep learning on ultrasonic images［J］. Construction and Building Materials，2024，411：134491.
[73]	YANG J J，FAN G P，XIANG Y X，et al. Low-frequency ultrasonic array imaging for detecting concrete structural defects in blind zones［J］. Construction and Building Materials，2024，425：135948.
[74]	CHEN S K，LU Y，SRIRAMADASU R C. An energy based enhanced imaging method for debonding evaluation in tile panels using Lamb wave time reversal with limited sensor numbers［J］. Ultrasonics，2025，155：107732.
[75]	CHEN S K，LU Y. Deep learning enhanced quantitative debonding evaluation in tile panels using Lamb waves［J］. Ultrasonics，2026，158：107821.
[76]	QIAN W，ZHU X J，ZHANG T，et al. Improving non-destructive testing methods for detecting cavity damage and internal defects in stone cultural relics:a focus on ultrasonic testing and acoustic tapping technology［J］. Journal of Cultural Heritage，2024，67：479- 487.
[77]	ZHANG X P，LI B，JIANG Y J，et al. Ambient vibration-based quantitative assessment on tunnel lining defect using laser doppler vibrometer［J］. Measurement，2025，239：115481.
[78]	AVCI O，ABDELJABER O，KIRANYAZ S，et al. A review of vibration-based damage detection in civil structures:from traditional methods to machine learning and deep learning applications［J］. Mechanical Systems and Signal Processing，2021，147：107077.
[79]	WANG Z D，LIU X G，CAO D K，et al. Detection and safety assessment of bonding defects in architectural decorative surface layer based on the variation of vibration acceleration amplitude［J］. Case Studies in Construction Materials，2025，22：e04278.
[80]	HOU X J，YAO B，CAO C，et al. A Study of a noncontact identification method of debonding damage in external thermal insulation composite systems based on nonlinear vibration［J］. Buildings，2025，15（20）：3728.
[81]	SHEN D H，LU Y，HUA L X，et al.，Numerical modelling and experimental testing of vibration-based debonding quantification on tile panels［J］. Journal of Sound and Vibration，2024，568：118074.
[82]	SHEN D H，LU Y，HUA L X. Automated debonding assessment of tile panels using convolutional neural network［J/OL］. Structural Health Monitoring，2025［2026-02-25］. https://sage.cnpereading.com/paragraph/article/?doi=10.1177/14759217251341437.
[83]	ZHAO Y，CHEN Y，YE L. A non-contact inspection method of tile debonding using tuned acoustic wave and laser doppler vibrometer［J］. Journal of Sound and Vibration，2023，564：117875.
[84]	PESCARI S，BUDĂU L，VILCEANU C. Rehabilitation and restauration of the main façade of historical masonry building-Romanian National Opera Timisoara［J］. Case Studies in Construction Materials，2023，18：e01838.
[85]	GACIEK P，GACZEK M，KRAUSE P. Bond strength of adhesive mortars to substrates in ETICS：comparison of testing methods［J］. Materials，2025，18（21）：4977.
[86]	中华人民共和囯住房和城乡建设部. 外墙保温用锚栓：JG/T 366—2012［S］. 北京：中国标准出版社，2012.
[87]	上海市住房和城乡建设管理委员会. 外墙外保温系统应用技术标准：DG/TJ 08-2126—2023［S］. 上海：同济大学出版社，2023.
[88]	GACIEK P，GACZEK M，KRAUSE P. Factors influencing adhesive bonding efficiency in ETICS application［J］. Materials，2025，18（17）：4043.
[89]	TEJEDOR B，LUCCHI E，HUERTAS D，et al. Non-destructive techniques（NDT）for the diagnosis of heritage buildings:traditional procedures and futures perspectives［J］. Energy and Buildings，2022，263：112029.
[90]	HE S D，ZHANG S H，MISHRA D，et al. Layered bilateral feature fusion network for end-to-end defect segmentation on aging tiled building façades［J］. Advanced Engineering Informatics，2026，70：104154.
[91]	CHEN K W，REICHARD G，XU X，et al. GIS-based information system for automated building facade assessment based on unmanned aerial vehicles and artificial intelligence［J］. Journal of Architectural Engineering，2023，29（4）：04023032.
[92]	LYU C，LIN S Q，LYNCH A，et al. UAV-based deep learning applications for automated inspection of civil infrastructure［J］. Automation in Construction，2025，177：106285.
[93]	TIAN Y D，CHEN C，CRENTSIL K，et al. Intelligent robotic systems for structural health monitoring：applications and future trends［J］. Automation in Construction，2022，139：104273.
[94]	FARAHZADI L，ODEH I，KIOUMARSI M，et al. Automated image-based condition assessment of built environment：a state-of-the-art investigation of damage characteristics and detection requirements［J］. Results in Engineering，2025，26：104978.
[95]	姜常玖，商登峰，朱玉华，等. 既有建筑外墙完损检测快速评估方法［J］. 施工技术（中英文），2023，52（4）：128- 132.
[96]	SILVA A，COELHO F，BRITO J，et al. Inspection，diagnosis，and repair system for architectural concrete surfaces［J］. Journal of Performance of Constructed Facilities，2017，31（5）：04017035.
[97]	SILVA A，COELHO F，BRITO J，et al. Statistical survey on inspection，diagnosis，and repair of architectural concrete surfaces［J］. Journal of Performance of Constructed Facilities，2017，31（6）：04017097.
[98]	SILVA A，BRITO J. Do we need a buildings’ inspection，diagnosis and service life prediction software?［J］. Journal of Building Engineering，2019，22：335- 348.
[99]	HAN B X，GAO C X，ZHAO Z Q，et al. A comprehensive framework for automated facade defect evaluation using deep learning［C］// The 19th International Conference on Control & Automation. Tallinn，Estonia：IEEE，2025：480- 485.
[100]	中国工程建设标准化协会. 建筑外墙外保温系统质量诊断与评估技术规程：T/ CECS 1029—2022［S］. 北京：中国计划出版社，2022.
[101]	FAQIH F，ZAYED T. A comparative review of building component rating systems［J］. Journal of Building Engineering，2021，33：101588.
[102]	XIMENNES S，BRITO J D，GASPAR P L，et al. Modelling the degradation and service life of ETICS in external walls［J］. Materials and Structures，2015，48（7）：2235- 2249.
[103]	GASPAR P，BRITO J. Limit states and service life of cement renders on facades［J］. Journal of Materials in Civil Engineering，2011，23（10）：1396- 1404.
[104]	BORDALO R，BRITO J，GASPAR P，et al. Service life prediction modelling of adhesive ceramic tiling systems［J］. Building Research & Information，2011，39（1）：66- 78.
[105]	SILVA A，BRITO J，GASPAR P. Service life prediction model applied to natural stone wall claddings（directly adhered to the substrate）［J］. Construction and Building Materials，2011，25（9）：3674- 3684.
[106]	CHAI C，BRITO J，GASPAR P，et al. Predicting the service life of exterior wall painting：techno-economic analysis of alternative maintenance strategies［J］. Journal of Construction Engineering and Management，2014，140（3）：04013057.
[107]	MARQUES C，BRITO J，SILVA A. Application of the factor method to the service life prediction of ETICS［J］. International Journal of Strategic Property Management，2018，22（3）：204- 222.
[108]	SILVA A，DIAS J，GASPAR P，et al. Service life prediction models for exterior stone cladding［J］. Building Research & Information，2011，39（6）：637- 653.
[109]	SILVA A，BRITO J. Service life of building envelopes:a critical literature review［J］. Journal of Building Engineering，2021，44：102646.
[110]	SERRALHEIRO M，BRITO J，SILVA A. Methodology for service life prediction of architectural concrete facades［J］. Construction and Building Materials，2017，133：261- 274.
[111]	MOUSAVI S，SILVA A，BRITO J，et al. Service life prediction of natural stone claddings with an indirect fastening system［J］. Journal of Performance of Constructed Facilities，2017，31（4）：04017014.
[112]	PRIETO A，SILVA A，BRITO J，et al. Serviceability of facade claddings［J］. Building Research & Information，2018，46（2）：179- 190.
[113]	SOUZA A，ROMEIRO T，BAUER E. Influence of the exposure degree on the degradation of facades of buildings in Brasília-Brazil［J］. Buildings，2024，14（1）：133.
[114]	SOUZA A，BAUER E. Differentiation of the evolutive behavior of facades degradation in ceramic cladding［J］. Construction and Building Materials，2025，489：142317.
[115]	MADUREIRA S，COLEN I，BRITO J，et al. Maintenance planning of facades in current buildings［J］. Construction and Building Materials，2017，147：790- 802.
[116]	上海市住房和城乡建设管理委员会. 外墙外保温系统修复技术标准：DG/TJ 08-2310—2019［S］. 上海：同济大学出版社，2019.
[117]	杨霞. 建筑外墙砖饰面安全风险评估模型［J］. 施工技术（中英文），2024，53（12）：167- 173.
[118]	梁轶循. 基于红外热像的外墙外保温系统缺陷识别判定与评价方法研究［D］. 哈尔滨：哈尔滨工业大学，2021.
[119]	RUIZ F，AGUADO A，SERRAT C. Methodology for calculating the severity index of buildings［J］. Structure and Infrastructure Engineering，2023，19（11）：1542- 1554.
[120]	FAQIH F，ZAYED T. Defect-based building condition assessment［J］. Building and Environment，2021，191：107575.
[121]	MATOS R，RODRIGUES F，RODRIGUES H，et al. Building condition assessment supported by Building Information Modelling［J］. Journal of Building Engineering，2021，38：102186.
[122]	HOSSEINI M，RAVANSHADNIA M，RAHIMZADEGAN M，et al. Next-generation building condition assessment：BIM and neural network integration［J］. Journal of Performance of Constructed Facilities，2024，38（6）：04024050.
[123]	WEST J，SIDDHPURA M，EVANGELISTA A，et al. Emergence of AI-impact on building condition index（BCI）［J］. Buildings，2024，14（12）：3868.
[124]	ALAVI H，BORTOLINI R，FORCADA N. BIM-based decision support for building condition assessment［J］. Automation in Construction，2022，135：104117.
[125]	中国工程建设标准化协会. 既有建筑外墙外保温改造技术规程：T/ CECS 574—2019［S］. 北京：中国建筑工业出版社，2019.
[126]	PEREIRA C，BRITO J，SILVESTRE J. Harmonized classification of repair techniques in a global inspection system：proposed methodology and analysis of fieldwork data［J］. Journal of Performance of Constructed Facilities，2021，35（1）：04020122.
[127]	刘晨. 基于粘锚法的既有建筑EPS板外保温“微创”维修研究［D］. 扬州：扬州大学，2024.
[128]	LYU G J，ZHENG M X，JI Y，et al. Interface agent modified by ternary polymers for ceramic tile of old walls based on grey relational analysis［J］. PloS One，2025，20（4）：e0320517.
[129]	AZEITEIRO L C，VELOSA A，PAIVA H，et al. Development of grouts for consolidation of old renders［J］. Construction and Building Materials，2014，50：352- 360.
[130]	ZHANG X J，DU M R，FANG H Y，et al. Polymer-modified cement mortars:their enhanced properties，applications，prospects，and challenges［J］. Construction and Building Materials，2021，299：124290.
[131]	PENG G，WU J W，HUANG K X，et al. Research on workability，mechanics，and durability of cementitious grout：a critical review［J］. Construction and Building Materials，2024，449：138374.
[132]	PANG B，YANG C，WANG P G，et al. Cement-based ductile rapid repair material modified with self-emulsifying waterborne epoxy［J］. Journal of Building Engineering，2023，79：107864.
[133]	CHEN B J，PANG L F，ZHAO Y M，et al. Effect of activated gold tailings replacing fly ash on the properties of cement-based grouting material［J］. Journal of Materials in Civil Engineering，2022，34（5）：04022066.
[134]	KUO W T，LIU M Y，JUANG C. Bonding behavior of repair material using fly-ash/ground granulated blast furnace slag-based geopolymer［J］. Materials，2019，12（10）：1697.
[135]	SHI C，ZOU X W，WANG P. Influences of EVA and methylcellulose on mechanical properties of Portland cement-calcium aluminate cement-gypsum ternary repair mortar［J］. Construction and Building Materials，2020，241：118035.
[136]	AATTACHE A，SOLTANI R，MAHI A. Investigations for properties improvement of recycled PE polymer particles-reinforced mortars for repair practice［J］. Construction and Building Materials，2017，146：603- 614.
[137]	ASSAAD J. Development and use of polymer-modified cement for adhesive and repair applications［J］. Construction and Building Materials，2018，163：139- 148.
[138]	GAO Y B，LUO J L，YUAN S K，et al. Fabrication of graphene oxide/fiber reinforced polymer cement mortar with remarkable repair and bonding properties［J］. Journal of Materials Research and Technology，2023，24：9413- 9433.
[139]	FU H，WANG P G，ZHENG H P，et al. Bionic repair protective coatings with high toughness and bond strength based on anionic waterborne polyurethane-modified cement［J］. Construction and Building Materials，2024，444：137861.
[140]	DEHGHANPOUR H，DOĞAN F，YILMAZ K. Development of CNT-CF-Al2O3-CMC gel-based cementitious repair composite［J］. Journal of Building Engineering，2022，45：103474.
[141]	李安起，李靖，韩志国，等. 粉煤灰砖砌体基层外保温锚栓荷载-位移特性试验研究［J］. 新型建筑材料，2025，52（5）：35- 41.
[142]	JI R，GUO S，WEI S. Evaluation of anchor bolt effects on the thermal performance of building insulation materials［J］. Journal of Building Engineering，2020，29：101200.
[143]	ZHANG Y B，LIU K，HUI Y，et al. Simulation calculation research on key indicators in pointin-place reinforcement technology for external thermal insulation［C］// International Conference on Advanced Materials and Structural Mechanics. Shenyang，China：IOP Publishing，2025.
[144]	COLEN I，BRITO J. Discussion of proactive maintenance strategies in façades’ coatings of social housing［J］. Journal of Building Appraisal，2010，5（3）：223- 240.
[145]	HU W，XIE Z H，CAI Y Y. A systemic survey towards predictive maintenance in the building industry based on network analysis［J］. Journal of Building Engineering，2025，112：113889.
[146]	NOWOGOŃSKA B. A methodology for determining the rehabilitation needs of buildings［J］. Applied Sciences，2020，10（11）：3873.
[147]	FERREIRA C，NEVES L，SILVA A，et al. Stochastic maintenance models for ceramic claddings［J］. Structure and Infrastructure Engineering，2020，16（2）：247- 265.
[148]	FERREIRA C，SILVA A，BRITO J，et al. Definition of a condition-based model for natural stone claddings［J］. Journal of Building Engineering，2021，33：101643.
[149]	FERREIRA C，SILVA A，BRITO J，et al. Condition-based maintenance strategies to enhance the durability of ETICS［J］. Sustainability，2021，13（12）：6677.
[150]	FERREIRA C，SILVA A，BRITO J，et al. The impact of imperfect maintenance actions on the degradation of buildings’ envelope components［J］. Journal of Building Engineering，2021，33：101571.
[151]	FERREIRA C，BARRELAS J，SILVA A，et al. Impact of environmental exposure conditions on the maintenance of facades’ claddings［J］. Buildings，2021，11（4）：138.
[152]	NYERS J，KAJTAR L，TOMIĆ S，et al. Investment-savings method for energy-economic optimization of external wall thermal insulation thickness［J］. Energy and Buildings，2015，86：268- 274.
[153]	FERREIRA C，SILVA A. Operationalisation of building inspections and repair：Systematisation-based approach［J］. Applied Sciences，2024，14（16）：6947.
[154]	ZHANG F，JU Y B，SANTIBANEZ G E D R，et al. A new framework to select energy-efficient retrofit schemes of external walls:a case study［J］. Journal of Cleaner Production，2021，289：125718.
[155]	DUAN D G，WU H B，WEI F，et al. Preparation，characterization，and rheological analysis of eco-friendly geopolymer grouting cementitious materials based on industrial solid wastes［J］. Journal of Building Engineering，2023，78：107451.
[156]	DELIKTAS D，ŞAHINÖZ Ö. A novel fuzzy group decision-making approach based on CCSD method for thermal insulation board selection problem：a case study［J］. Engineering Applications of Artificial Intelligence，2023，121：105986.