concept of a computer-vision-based algorithm for detecting thermal anomalies in reinforced concrete structures

Clicks: 291
ID: 147568
2019
Free PDF
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
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.
Reference Key
filippo2019proceedingsconcept Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Michele De Filippo;Sasan Asadiabadi;Nigel Ko;Harris Sun
Journal sotsiologicheskoe obozrenie
Year 2019
DOI
10.3390/proceedings2019027018
URL
https://www.mdpi.com/2504-3900/27/1/18
Keywords
drone ai infrared reinforced concrete thermography civil engineering

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.