Automatic Identification and Location of Tunnel Lining Cracks
The lining crack is common for the tunnel in the stage of operation, which has seriously influenced the service life and safety of tunnel engineering. It is a new trend to use computer vision to detect tunnel cracks over the past few years in China and foreign countries. By image processing technolo...
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2021-01-01
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Series: | Advances in Civil Engineering |
Online Access: | http://dx.doi.org/10.1155/2021/8846442 |
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doaj-efe8d7aad6934f60866d31a18d90ace02021-04-05T00:01:50ZengHindawi LimitedAdvances in Civil Engineering1687-80942021-01-01202110.1155/2021/8846442Automatic Identification and Location of Tunnel Lining CracksPengyu Wang0Shuhong Wang1Alipujiang Jierula2School of Resources and Civil EngineeringSchool of Resources and Civil EngineeringSchool of Resources and Civil EngineeringThe lining crack is common for the tunnel in the stage of operation, which has seriously influenced the service life and safety of tunnel engineering. It is a new trend to use computer vision to detect tunnel cracks over the past few years in China and foreign countries. By image processing technology and intelligent algorithm, the computer has a hominine visual perception system which understands, analyzes, and determines input image information, thus recognizing and detecting specific objectives. However, the effect of image recognition for tunnel crack now cannot satisfy the demands of practical engineering. SSD algorithm has been used when analyzing features of lining surface image, while comparison analysis has been made from image recognition results, error rate, and running time. The results indicate that the SSD algorithm can accurately and rapidly detect and mark the position of the tunnel crack. The tunnel information obtained from image recognition is subsequently imported into the team independently developed software GeoSMA-3D, which is useful for determining tunnel grade.http://dx.doi.org/10.1155/2021/8846442 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pengyu Wang Shuhong Wang Alipujiang Jierula |
spellingShingle |
Pengyu Wang Shuhong Wang Alipujiang Jierula Automatic Identification and Location of Tunnel Lining Cracks Advances in Civil Engineering |
author_facet |
Pengyu Wang Shuhong Wang Alipujiang Jierula |
author_sort |
Pengyu Wang |
title |
Automatic Identification and Location of Tunnel Lining Cracks |
title_short |
Automatic Identification and Location of Tunnel Lining Cracks |
title_full |
Automatic Identification and Location of Tunnel Lining Cracks |
title_fullStr |
Automatic Identification and Location of Tunnel Lining Cracks |
title_full_unstemmed |
Automatic Identification and Location of Tunnel Lining Cracks |
title_sort |
automatic identification and location of tunnel lining cracks |
publisher |
Hindawi Limited |
series |
Advances in Civil Engineering |
issn |
1687-8094 |
publishDate |
2021-01-01 |
description |
The lining crack is common for the tunnel in the stage of operation, which has seriously influenced the service life and safety of tunnel engineering. It is a new trend to use computer vision to detect tunnel cracks over the past few years in China and foreign countries. By image processing technology and intelligent algorithm, the computer has a hominine visual perception system which understands, analyzes, and determines input image information, thus recognizing and detecting specific objectives. However, the effect of image recognition for tunnel crack now cannot satisfy the demands of practical engineering. SSD algorithm has been used when analyzing features of lining surface image, while comparison analysis has been made from image recognition results, error rate, and running time. The results indicate that the SSD algorithm can accurately and rapidly detect and mark the position of the tunnel crack. The tunnel information obtained from image recognition is subsequently imported into the team independently developed software GeoSMA-3D, which is useful for determining tunnel grade. |
url |
http://dx.doi.org/10.1155/2021/8846442 |
work_keys_str_mv |
AT pengyuwang automaticidentificationandlocationoftunnelliningcracks AT shuhongwang automaticidentificationandlocationoftunnelliningcracks AT alipujiangjierula automaticidentificationandlocationoftunnelliningcracks |
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