An Improved GPR Method Based on BP and RPCA for Tunnel Lining Defects Detection and Its Application in Qiyue Mountain Tunnel, China

Tunnel lining defects are one of the most common problems that tunnels experience during operation, and they can pose severe safety risks. The most popular nondestructive testing method for detecting tunnel lining defects is ground penetrating radar (GPR), one of the basic geophysical applications....

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Autores principales:	Dongli Li, Echuan Yan
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	tunnel lining detection ground penetrating radar back projection imaging robust principal component analysis Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/50620e92f4c04bea8d247b7b51fa2c7e
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spelling	oai:doaj.org-article:50620e92f4c04bea8d247b7b51fa2c7e2021-11-11T15:16:48ZAn Improved GPR Method Based on BP and RPCA for Tunnel Lining Defects Detection and Its Application in Qiyue Mountain Tunnel, China10.3390/app1121102342076-3417https://doaj.org/article/50620e92f4c04bea8d247b7b51fa2c7e2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10234https://doaj.org/toc/2076-3417Tunnel lining defects are one of the most common problems that tunnels experience during operation, and they can pose severe safety risks. The most popular nondestructive testing method for detecting tunnel lining defects is ground penetrating radar (GPR), one of the basic geophysical applications. However, detection responses might differ significantly from the real shape of tunnel lining defects, making it challenging to identify and interpret. When data quality is poor, interpretation and identification become more challenging, resulting in a high cost of tunnel repairs. The improved back projection (BP) imaging and robust principal component analysis (RPCA) are used in this work to offer a GPR data processing method. Even in the event of poor data quality, our method could recover GPR responses, allowing the shapes and locations of tunnel lining flaws to be clearly depicted. With BP imaging, this approach recovers the tunnel defects’ responses to better forms and positions, and with RPCA, it further isolates the target imaging from clutters. Several synthetic data demonstrate that the approach presented in this work may successfully repair and extract the positions and forms of lining defects, making them easier to identify and comprehend. Furthermore, our technique was used to GPR data gathered from the Qiyue Mountain Tunnel in China, yielding more accurate findings than the traditional method, which was validated by the actual scenario to illustrate the efficiency of our method on real data.Dongli LiEchuan YanMDPI AGarticletunnel liningdetectionground penetrating radarback projection imagingrobust principal component analysisTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10234, p 10234 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	tunnel lining detection ground penetrating radar back projection imaging robust principal component analysis Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	tunnel lining detection ground penetrating radar back projection imaging robust principal component analysis Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Dongli Li Echuan Yan An Improved GPR Method Based on BP and RPCA for Tunnel Lining Defects Detection and Its Application in Qiyue Mountain Tunnel, China
description	Tunnel lining defects are one of the most common problems that tunnels experience during operation, and they can pose severe safety risks. The most popular nondestructive testing method for detecting tunnel lining defects is ground penetrating radar (GPR), one of the basic geophysical applications. However, detection responses might differ significantly from the real shape of tunnel lining defects, making it challenging to identify and interpret. When data quality is poor, interpretation and identification become more challenging, resulting in a high cost of tunnel repairs. The improved back projection (BP) imaging and robust principal component analysis (RPCA) are used in this work to offer a GPR data processing method. Even in the event of poor data quality, our method could recover GPR responses, allowing the shapes and locations of tunnel lining flaws to be clearly depicted. With BP imaging, this approach recovers the tunnel defects’ responses to better forms and positions, and with RPCA, it further isolates the target imaging from clutters. Several synthetic data demonstrate that the approach presented in this work may successfully repair and extract the positions and forms of lining defects, making them easier to identify and comprehend. Furthermore, our technique was used to GPR data gathered from the Qiyue Mountain Tunnel in China, yielding more accurate findings than the traditional method, which was validated by the actual scenario to illustrate the efficiency of our method on real data.
format	article
author	Dongli Li Echuan Yan
author_facet	Dongli Li Echuan Yan
author_sort	Dongli Li
title	An Improved GPR Method Based on BP and RPCA for Tunnel Lining Defects Detection and Its Application in Qiyue Mountain Tunnel, China
title_short	An Improved GPR Method Based on BP and RPCA for Tunnel Lining Defects Detection and Its Application in Qiyue Mountain Tunnel, China
title_full	An Improved GPR Method Based on BP and RPCA for Tunnel Lining Defects Detection and Its Application in Qiyue Mountain Tunnel, China
title_fullStr	An Improved GPR Method Based on BP and RPCA for Tunnel Lining Defects Detection and Its Application in Qiyue Mountain Tunnel, China
title_full_unstemmed	An Improved GPR Method Based on BP and RPCA for Tunnel Lining Defects Detection and Its Application in Qiyue Mountain Tunnel, China
title_sort	improved gpr method based on bp and rpca for tunnel lining defects detection and its application in qiyue mountain tunnel, china
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/50620e92f4c04bea8d247b7b51fa2c7e
work_keys_str_mv	AT donglili animprovedgprmethodbasedonbpandrpcafortunnelliningdefectsdetectionanditsapplicationinqiyuemountaintunnelchina AT echuanyan animprovedgprmethodbasedonbpandrpcafortunnelliningdefectsdetectionanditsapplicationinqiyuemountaintunnelchina AT donglili improvedgprmethodbasedonbpandrpcafortunnelliningdefectsdetectionanditsapplicationinqiyuemountaintunnelchina AT echuanyan improvedgprmethodbasedonbpandrpcafortunnelliningdefectsdetectionanditsapplicationinqiyuemountaintunnelchina
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An Improved GPR Method Based on BP and RPCA for Tunnel Lining Defects Detection and Its Application in Qiyue Mountain Tunnel, China

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