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Proceeding Paper

Concept of Computer Vision Based Algorithm for Detecting Thermal Anomalies in Reinforced Concrete Structures †

by
Michele De Filippo
1,*,‡,
Sasan Asadiabadi
1,‡,
Nigel Ko
2 and
Harris Sun
1
1
RaSpect Intelligence Inspection Ltd., 16F, 700 Nathan Road, Mong Kok, Kowloon, Hong Kong, China
2
Infrared Engineering & Consultants Ltd., Suite 1603, 16/F, Chinachem Johnston Plaza, 178-186 Johnston Road, Wanchai, Hong Kong, China
*
Author to whom correspondence should be addressed.
†
Presented at the 15th International Workshop on Advanced Infrared Technology and Applications (AITA 2019), Florence, Italy, 17–19 September 2019.
‡
These authors contributed equally to this work.
Proceedings 2019, 27(1), 18; https://doi.org/10.3390/proceedings2019027018
Published: 21 September 2019
(This article belongs to the Proceedings of The 15th International Workshop on Advanced Infrared Technology and Applications)
Versions Notes

Abstract

In Hong Kong, there is great abundancy of aged buildings and infrastructures for which a re-assessment of the current status is needed. Water exfiltrations/infiltrations, deteriorating insulations, thermal bridges and regions of failure are among the most recurrent symptoms to be found in existing Reinforced Concrete (RC) structures. Diagnosis of such symptoms, in the form of thermal infrared anomalies, is usually performed through infrared (IR) image capturing, followed by qualitative assessment. This paper presents a novel automated computer-vision-based method for detecting thermal anomalies. Such Computer-Vision (CV) algorithm is tested on different thermal scenarios including beam elements, roofs and entire façades of RC buildings. Thermal anomalies related to cases of water leakages, moisture trapping and debonding are successfully detected. The authors intend to undertake further research for successfully implementing the method for detecting also other thermal dissimilarities.
Keywords: AI; Civil Engineering; computer-vision; drone; infrared; reinforced concrete; thermography; water leakage AI; Civil Engineering; computer-vision; drone; infrared; reinforced concrete; thermography; water leakage

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MDPI and ACS Style

De Filippo, M.; Asadiabadi, S.; Ko, N.; Sun, H. Concept of Computer Vision Based Algorithm for Detecting Thermal Anomalies in Reinforced Concrete Structures. Proceedings 2019, 27, 18. https://doi.org/10.3390/proceedings2019027018

AMA Style

De Filippo M, Asadiabadi S, Ko N, Sun H. Concept of Computer Vision Based Algorithm for Detecting Thermal Anomalies in Reinforced Concrete Structures. Proceedings. 2019; 27(1):18. https://doi.org/10.3390/proceedings2019027018

Chicago/Turabian Style

De Filippo, Michele, Sasan Asadiabadi, Nigel Ko, and Harris Sun. 2019. "Concept of Computer Vision Based Algorithm for Detecting Thermal Anomalies in Reinforced Concrete Structures" Proceedings 27, no. 1: 18. https://doi.org/10.3390/proceedings2019027018

APA Style

De Filippo, M., Asadiabadi, S., Ko, N., & Sun, H. (2019). Concept of Computer Vision Based Algorithm for Detecting Thermal Anomalies in Reinforced Concrete Structures. Proceedings, 27(1), 18. https://doi.org/10.3390/proceedings2019027018

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