Cavity Detection in Steel-Pipe Culverts Using Infrared Thermography

Finding efficient and less expensive techniques for different aspects of culvert inspection is in great demand. This study assesses the potential of infrared thermography (IRT) to detect the presence of cavities in the soil around a culvert, specifically for cavities adjacent to the pipe of galvaniz...

Full description

Bibliographic Details
Main Authors: Davood Kalhor, Samira Ebrahimi, Roger Booto Tokime, Farima Abdollahi Mamoudan, Yohan Bélanger, Alexandra Mercier, Xavier Maldague
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/9/4051
id doaj-71201a6cc2cb474887392e24f41611c9
record_format Article
spelling doaj-71201a6cc2cb474887392e24f41611c92021-04-29T23:02:13ZengMDPI AGApplied Sciences2076-34172021-04-01114051405110.3390/app11094051Cavity Detection in Steel-Pipe Culverts Using Infrared ThermographyDavood Kalhor0Samira Ebrahimi1Roger Booto Tokime2Farima Abdollahi Mamoudan3Yohan Bélanger4Alexandra Mercier5Xavier Maldague6Computer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, Quebec City, QC G1V 0A6, CanadaComputer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, Quebec City, QC G1V 0A6, CanadaComputer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, Quebec City, QC G1V 0A6, CanadaComputer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, Quebec City, QC G1V 0A6, CanadaComputer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, Quebec City, QC G1V 0A6, CanadaComputer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, Quebec City, QC G1V 0A6, CanadaComputer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, Quebec City, QC G1V 0A6, CanadaFinding efficient and less expensive techniques for different aspects of culvert inspection is in great demand. This study assesses the potential of infrared thermography (IRT) to detect the presence of cavities in the soil around a culvert, specifically for cavities adjacent to the pipe of galvanized culverts. To identify cavities, we analyze thermograms, generated via long pulse thermography, using absolute thermal contrast, principal components thermography, and a statistical approach along with a combination of different pre- and post-processing algorithms. Using several experiments, we evaluate the performance of IRT for accomplishing the given task. Empirical results show a promising future for the application of this approach in culvert inspection. The size and location of cavities are among the aspects that can be extracted from analyzing thermograms. The key finding of this research is that the proposed approach can provide useful information about a certain type of problem around a culvert pipe which may indicate the early stage of the cavity formation. Becoming aware of this process in earlier stages will certainly help to prevent any costly incidents later.https://www.mdpi.com/2076-3417/11/9/4051culvert inspectioncavity detectioninfrared thermographynondestructive testingprincipal components thermographypulse thermography
collection DOAJ
language English
format Article
sources DOAJ
author Davood Kalhor
Samira Ebrahimi
Roger Booto Tokime
Farima Abdollahi Mamoudan
Yohan Bélanger
Alexandra Mercier
Xavier Maldague
spellingShingle Davood Kalhor
Samira Ebrahimi
Roger Booto Tokime
Farima Abdollahi Mamoudan
Yohan Bélanger
Alexandra Mercier
Xavier Maldague
Cavity Detection in Steel-Pipe Culverts Using Infrared Thermography
Applied Sciences
culvert inspection
cavity detection
infrared thermography
nondestructive testing
principal components thermography
pulse thermography
author_facet Davood Kalhor
Samira Ebrahimi
Roger Booto Tokime
Farima Abdollahi Mamoudan
Yohan Bélanger
Alexandra Mercier
Xavier Maldague
author_sort Davood Kalhor
title Cavity Detection in Steel-Pipe Culverts Using Infrared Thermography
title_short Cavity Detection in Steel-Pipe Culverts Using Infrared Thermography
title_full Cavity Detection in Steel-Pipe Culverts Using Infrared Thermography
title_fullStr Cavity Detection in Steel-Pipe Culverts Using Infrared Thermography
title_full_unstemmed Cavity Detection in Steel-Pipe Culverts Using Infrared Thermography
title_sort cavity detection in steel-pipe culverts using infrared thermography
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2021-04-01
description Finding efficient and less expensive techniques for different aspects of culvert inspection is in great demand. This study assesses the potential of infrared thermography (IRT) to detect the presence of cavities in the soil around a culvert, specifically for cavities adjacent to the pipe of galvanized culverts. To identify cavities, we analyze thermograms, generated via long pulse thermography, using absolute thermal contrast, principal components thermography, and a statistical approach along with a combination of different pre- and post-processing algorithms. Using several experiments, we evaluate the performance of IRT for accomplishing the given task. Empirical results show a promising future for the application of this approach in culvert inspection. The size and location of cavities are among the aspects that can be extracted from analyzing thermograms. The key finding of this research is that the proposed approach can provide useful information about a certain type of problem around a culvert pipe which may indicate the early stage of the cavity formation. Becoming aware of this process in earlier stages will certainly help to prevent any costly incidents later.
topic culvert inspection
cavity detection
infrared thermography
nondestructive testing
principal components thermography
pulse thermography
url https://www.mdpi.com/2076-3417/11/9/4051
work_keys_str_mv AT davoodkalhor cavitydetectioninsteelpipeculvertsusinginfraredthermography
AT samiraebrahimi cavitydetectioninsteelpipeculvertsusinginfraredthermography
AT rogerboototokime cavitydetectioninsteelpipeculvertsusinginfraredthermography
AT farimaabdollahimamoudan cavitydetectioninsteelpipeculvertsusinginfraredthermography
AT yohanbelanger cavitydetectioninsteelpipeculvertsusinginfraredthermography
AT alexandramercier cavitydetectioninsteelpipeculvertsusinginfraredthermography
AT xaviermaldague cavitydetectioninsteelpipeculvertsusinginfraredthermography
_version_ 1721500203708579840