{"title":"Current Challenges and Advancements of Aerial Thermography for Outdoor Structural Health Monitoring: A Review","authors":"Yue Ma;Zhi Zeng;Zipei Luo;Ning Tao;Lei Deng;Yibin Tian","doi":"10.1109/JSEN.2025.3561200","DOIUrl":null,"url":null,"abstract":"In the rapid development of outdoor structural health monitoring (SHM), infrared thermal imaging and autonomous aerial vehicles (AAVs) have emerged as transformative tools, significantly enhancing maintenance efficiency in expansive outdoor structures. This review highlights the advancements in AAV-assisted thermography, focusing on its impact on the monitoring capabilities of outdoor engineering structures. It introduces AAV-assisted thermographic methods tailored for outdoor environments, explores current challenges influencing their efficacy, and thoroughly examines their integration with machine learning techniques, demonstrating their applications in identifying structural flaws and deformations. Furthermore, the review emphasizes the transformative potential of 3-D thermographic modeling to localize and characterize defects effectively. It contributes actionable insights to optimize AAV-assisted thermographic practices. The findings underscore the importance of integrating AAVs and thermography to overcome the existing limitations in outdoor SHM inspections, setting the stage for a paradigm shift in large-scale outdoor structural condition assessments.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"21000-21016"},"PeriodicalIF":4.3000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10971885/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
In the rapid development of outdoor structural health monitoring (SHM), infrared thermal imaging and autonomous aerial vehicles (AAVs) have emerged as transformative tools, significantly enhancing maintenance efficiency in expansive outdoor structures. This review highlights the advancements in AAV-assisted thermography, focusing on its impact on the monitoring capabilities of outdoor engineering structures. It introduces AAV-assisted thermographic methods tailored for outdoor environments, explores current challenges influencing their efficacy, and thoroughly examines their integration with machine learning techniques, demonstrating their applications in identifying structural flaws and deformations. Furthermore, the review emphasizes the transformative potential of 3-D thermographic modeling to localize and characterize defects effectively. It contributes actionable insights to optimize AAV-assisted thermographic practices. The findings underscore the importance of integrating AAVs and thermography to overcome the existing limitations in outdoor SHM inspections, setting the stage for a paradigm shift in large-scale outdoor structural condition assessments.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice