Shield subway tunnel deformation detection based on mobile laser scanning

Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Here...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Cui, Hao [verfasserIn] Ren, Xiaochun [verfasserIn] Mao, Qingzhou [verfasserIn] Hu, Qingwu [verfasserIn] Wang, Wei [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Mobile laser scanning Shield subway tunnel Deformation detection Cross section Wavelet filtering Ellipse fitting

Übergeordnetes Werk:	Enthalten in: Automation in construction - Amsterdam [u.a.] : Elsevier Science Publ., 1992, 106
Übergeordnetes Werk:	volume:106

DOI / URN:	10.1016/j.autcon.2019.102889

Katalog-ID:	ELV002803224

Internformat


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520			\|a Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Herein, detailed analysis is given to prove that profiles from the laser scanner can be seen as cross-sections of the tunnel and that the corresponding error can be ignored. A wavelet filtering algorithm was developed to filter the point cloud of tunnel ancillary facilities in the cross-section points. A subsequent ellipse fitting and deformation detection method is proposed. A cross-section location method for subway tunnels is also presented based on the greyscale image converted from the tunnel's point cloud. A tunnel ring segments seams detection method is proposed to detect tunnel ring segments dislocation. The accuracy of the system was verified in a subway tunnel in Wuhan, China with a total station. The accuracy of cross-section measurement was 1.5 mm, the repeatability of the overall and local deformation measurement was 0.5 and 0.9 mm, respectively. This system completely fulfils the accuracy requirement of railway tunnels deformation detection and its efficiency is significantly higher than that of the traditional method.
650		4	\|a Mobile laser scanning
650		4	\|a Shield subway tunnel
650		4	\|a Deformation detection
650		4	\|a Cross section
650		4	\|a Wavelet filtering
650		4	\|a Ellipse fitting
700	1		\|a Ren, Xiaochun \|e verfasserin \|4 aut
700	1		\|a Mao, Qingzhou \|e verfasserin \|4 aut
700	1		\|a Hu, Qingwu \|e verfasserin \|0 (orcid)0000-0003-0866-6678 \|4 aut
700	1		\|a Wang, Wei \|e verfasserin \|4 aut
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Indexfelder

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matchkey_str	cuihaorenxiaochunmaoqingzhouhuqingwuwang:2019----:heduwyunleomtodtcinaeomb
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publishDate	2019
allfields	10.1016/j.autcon.2019.102889 doi (DE-627)ELV002803224 (ELSEVIER)S0926-5805(18)30973-7 DE-627 ger DE-627 rda eng 690 DE-600 56.03 bkl Cui, Hao verfasserin (orcid)0000-0002-5121-3669 aut Shield subway tunnel deformation detection based on mobile laser scanning 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Herein, detailed analysis is given to prove that profiles from the laser scanner can be seen as cross-sections of the tunnel and that the corresponding error can be ignored. A wavelet filtering algorithm was developed to filter the point cloud of tunnel ancillary facilities in the cross-section points. A subsequent ellipse fitting and deformation detection method is proposed. A cross-section location method for subway tunnels is also presented based on the greyscale image converted from the tunnel's point cloud. A tunnel ring segments seams detection method is proposed to detect tunnel ring segments dislocation. The accuracy of the system was verified in a subway tunnel in Wuhan, China with a total station. The accuracy of cross-section measurement was 1.5 mm, the repeatability of the overall and local deformation measurement was 0.5 and 0.9 mm, respectively. This system completely fulfils the accuracy requirement of railway tunnels deformation detection and its efficiency is significantly higher than that of the traditional method. Mobile laser scanning Shield subway tunnel Deformation detection Cross section Wavelet filtering Ellipse fitting Ren, Xiaochun verfasserin aut Mao, Qingzhou verfasserin aut Hu, Qingwu verfasserin (orcid)0000-0003-0866-6678 aut Wang, Wei verfasserin aut Enthalten in Automation in construction Amsterdam [u.a.] : Elsevier Science Publ., 1992 106 Online-Ressource (DE-627)320422259 (DE-600)2002703-5 (DE-576)094478813 nnns volume:106 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 56.03 Methoden im Bauingenieurwesen AR 106
spelling	10.1016/j.autcon.2019.102889 doi (DE-627)ELV002803224 (ELSEVIER)S0926-5805(18)30973-7 DE-627 ger DE-627 rda eng 690 DE-600 56.03 bkl Cui, Hao verfasserin (orcid)0000-0002-5121-3669 aut Shield subway tunnel deformation detection based on mobile laser scanning 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Herein, detailed analysis is given to prove that profiles from the laser scanner can be seen as cross-sections of the tunnel and that the corresponding error can be ignored. A wavelet filtering algorithm was developed to filter the point cloud of tunnel ancillary facilities in the cross-section points. A subsequent ellipse fitting and deformation detection method is proposed. A cross-section location method for subway tunnels is also presented based on the greyscale image converted from the tunnel's point cloud. A tunnel ring segments seams detection method is proposed to detect tunnel ring segments dislocation. The accuracy of the system was verified in a subway tunnel in Wuhan, China with a total station. The accuracy of cross-section measurement was 1.5 mm, the repeatability of the overall and local deformation measurement was 0.5 and 0.9 mm, respectively. This system completely fulfils the accuracy requirement of railway tunnels deformation detection and its efficiency is significantly higher than that of the traditional method. Mobile laser scanning Shield subway tunnel Deformation detection Cross section Wavelet filtering Ellipse fitting Ren, Xiaochun verfasserin aut Mao, Qingzhou verfasserin aut Hu, Qingwu verfasserin (orcid)0000-0003-0866-6678 aut Wang, Wei verfasserin aut Enthalten in Automation in construction Amsterdam [u.a.] : Elsevier Science Publ., 1992 106 Online-Ressource (DE-627)320422259 (DE-600)2002703-5 (DE-576)094478813 nnns volume:106 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 56.03 Methoden im Bauingenieurwesen AR 106
allfields_unstemmed	10.1016/j.autcon.2019.102889 doi (DE-627)ELV002803224 (ELSEVIER)S0926-5805(18)30973-7 DE-627 ger DE-627 rda eng 690 DE-600 56.03 bkl Cui, Hao verfasserin (orcid)0000-0002-5121-3669 aut Shield subway tunnel deformation detection based on mobile laser scanning 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Herein, detailed analysis is given to prove that profiles from the laser scanner can be seen as cross-sections of the tunnel and that the corresponding error can be ignored. A wavelet filtering algorithm was developed to filter the point cloud of tunnel ancillary facilities in the cross-section points. A subsequent ellipse fitting and deformation detection method is proposed. A cross-section location method for subway tunnels is also presented based on the greyscale image converted from the tunnel's point cloud. A tunnel ring segments seams detection method is proposed to detect tunnel ring segments dislocation. The accuracy of the system was verified in a subway tunnel in Wuhan, China with a total station. The accuracy of cross-section measurement was 1.5 mm, the repeatability of the overall and local deformation measurement was 0.5 and 0.9 mm, respectively. This system completely fulfils the accuracy requirement of railway tunnels deformation detection and its efficiency is significantly higher than that of the traditional method. Mobile laser scanning Shield subway tunnel Deformation detection Cross section Wavelet filtering Ellipse fitting Ren, Xiaochun verfasserin aut Mao, Qingzhou verfasserin aut Hu, Qingwu verfasserin (orcid)0000-0003-0866-6678 aut Wang, Wei verfasserin aut Enthalten in Automation in construction Amsterdam [u.a.] : Elsevier Science Publ., 1992 106 Online-Ressource (DE-627)320422259 (DE-600)2002703-5 (DE-576)094478813 nnns volume:106 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 56.03 Methoden im Bauingenieurwesen AR 106
allfieldsGer	10.1016/j.autcon.2019.102889 doi (DE-627)ELV002803224 (ELSEVIER)S0926-5805(18)30973-7 DE-627 ger DE-627 rda eng 690 DE-600 56.03 bkl Cui, Hao verfasserin (orcid)0000-0002-5121-3669 aut Shield subway tunnel deformation detection based on mobile laser scanning 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Herein, detailed analysis is given to prove that profiles from the laser scanner can be seen as cross-sections of the tunnel and that the corresponding error can be ignored. A wavelet filtering algorithm was developed to filter the point cloud of tunnel ancillary facilities in the cross-section points. A subsequent ellipse fitting and deformation detection method is proposed. A cross-section location method for subway tunnels is also presented based on the greyscale image converted from the tunnel's point cloud. A tunnel ring segments seams detection method is proposed to detect tunnel ring segments dislocation. The accuracy of the system was verified in a subway tunnel in Wuhan, China with a total station. The accuracy of cross-section measurement was 1.5 mm, the repeatability of the overall and local deformation measurement was 0.5 and 0.9 mm, respectively. This system completely fulfils the accuracy requirement of railway tunnels deformation detection and its efficiency is significantly higher than that of the traditional method. Mobile laser scanning Shield subway tunnel Deformation detection Cross section Wavelet filtering Ellipse fitting Ren, Xiaochun verfasserin aut Mao, Qingzhou verfasserin aut Hu, Qingwu verfasserin (orcid)0000-0003-0866-6678 aut Wang, Wei verfasserin aut Enthalten in Automation in construction Amsterdam [u.a.] : Elsevier Science Publ., 1992 106 Online-Ressource (DE-627)320422259 (DE-600)2002703-5 (DE-576)094478813 nnns volume:106 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 56.03 Methoden im Bauingenieurwesen AR 106
allfieldsSound	10.1016/j.autcon.2019.102889 doi (DE-627)ELV002803224 (ELSEVIER)S0926-5805(18)30973-7 DE-627 ger DE-627 rda eng 690 DE-600 56.03 bkl Cui, Hao verfasserin (orcid)0000-0002-5121-3669 aut Shield subway tunnel deformation detection based on mobile laser scanning 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Herein, detailed analysis is given to prove that profiles from the laser scanner can be seen as cross-sections of the tunnel and that the corresponding error can be ignored. A wavelet filtering algorithm was developed to filter the point cloud of tunnel ancillary facilities in the cross-section points. A subsequent ellipse fitting and deformation detection method is proposed. A cross-section location method for subway tunnels is also presented based on the greyscale image converted from the tunnel's point cloud. A tunnel ring segments seams detection method is proposed to detect tunnel ring segments dislocation. The accuracy of the system was verified in a subway tunnel in Wuhan, China with a total station. The accuracy of cross-section measurement was 1.5 mm, the repeatability of the overall and local deformation measurement was 0.5 and 0.9 mm, respectively. This system completely fulfils the accuracy requirement of railway tunnels deformation detection and its efficiency is significantly higher than that of the traditional method. Mobile laser scanning Shield subway tunnel Deformation detection Cross section Wavelet filtering Ellipse fitting Ren, Xiaochun verfasserin aut Mao, Qingzhou verfasserin aut Hu, Qingwu verfasserin (orcid)0000-0003-0866-6678 aut Wang, Wei verfasserin aut Enthalten in Automation in construction Amsterdam [u.a.] : Elsevier Science Publ., 1992 106 Online-Ressource (DE-627)320422259 (DE-600)2002703-5 (DE-576)094478813 nnns volume:106 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 56.03 Methoden im Bauingenieurwesen AR 106
language	English
source	Enthalten in Automation in construction 106 volume:106
sourceStr	Enthalten in Automation in construction 106 volume:106
format_phy_str_mv	Article
bklname	Methoden im Bauingenieurwesen
institution	findex.gbv.de
topic_facet	Mobile laser scanning Shield subway tunnel Deformation detection Cross section Wavelet filtering Ellipse fitting
dewey-raw	690
isfreeaccess_bool	false
container_title	Automation in construction
authorswithroles_txt_mv	Cui, Hao @@aut@@ Ren, Xiaochun @@aut@@ Mao, Qingzhou @@aut@@ Hu, Qingwu @@aut@@ Wang, Wei @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
hierarchy_top_id	320422259
dewey-sort	3690
id	ELV002803224
language_de	englisch
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author	Cui, Hao
spellingShingle	Cui, Hao ddc 690 bkl 56.03 misc Mobile laser scanning misc Shield subway tunnel misc Deformation detection misc Cross section misc Wavelet filtering misc Ellipse fitting Shield subway tunnel deformation detection based on mobile laser scanning
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topic_title	690 DE-600 56.03 bkl Shield subway tunnel deformation detection based on mobile laser scanning Mobile laser scanning Shield subway tunnel Deformation detection Cross section Wavelet filtering Ellipse fitting
topic	ddc 690 bkl 56.03 misc Mobile laser scanning misc Shield subway tunnel misc Deformation detection misc Cross section misc Wavelet filtering misc Ellipse fitting
topic_unstemmed	ddc 690 bkl 56.03 misc Mobile laser scanning misc Shield subway tunnel misc Deformation detection misc Cross section misc Wavelet filtering misc Ellipse fitting
topic_browse	ddc 690 bkl 56.03 misc Mobile laser scanning misc Shield subway tunnel misc Deformation detection misc Cross section misc Wavelet filtering misc Ellipse fitting
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title	Shield subway tunnel deformation detection based on mobile laser scanning
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title_full	Shield subway tunnel deformation detection based on mobile laser scanning
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title_sort	shield subway tunnel deformation detection based on mobile laser scanning
title_auth	Shield subway tunnel deformation detection based on mobile laser scanning
abstract	Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Herein, detailed analysis is given to prove that profiles from the laser scanner can be seen as cross-sections of the tunnel and that the corresponding error can be ignored. A wavelet filtering algorithm was developed to filter the point cloud of tunnel ancillary facilities in the cross-section points. A subsequent ellipse fitting and deformation detection method is proposed. A cross-section location method for subway tunnels is also presented based on the greyscale image converted from the tunnel's point cloud. A tunnel ring segments seams detection method is proposed to detect tunnel ring segments dislocation. The accuracy of the system was verified in a subway tunnel in Wuhan, China with a total station. The accuracy of cross-section measurement was 1.5 mm, the repeatability of the overall and local deformation measurement was 0.5 and 0.9 mm, respectively. This system completely fulfils the accuracy requirement of railway tunnels deformation detection and its efficiency is significantly higher than that of the traditional method.
abstractGer	Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Herein, detailed analysis is given to prove that profiles from the laser scanner can be seen as cross-sections of the tunnel and that the corresponding error can be ignored. A wavelet filtering algorithm was developed to filter the point cloud of tunnel ancillary facilities in the cross-section points. A subsequent ellipse fitting and deformation detection method is proposed. A cross-section location method for subway tunnels is also presented based on the greyscale image converted from the tunnel's point cloud. A tunnel ring segments seams detection method is proposed to detect tunnel ring segments dislocation. The accuracy of the system was verified in a subway tunnel in Wuhan, China with a total station. The accuracy of cross-section measurement was 1.5 mm, the repeatability of the overall and local deformation measurement was 0.5 and 0.9 mm, respectively. This system completely fulfils the accuracy requirement of railway tunnels deformation detection and its efficiency is significantly higher than that of the traditional method.
abstract_unstemmed	Shield subway tunnels are critical urban infrastructure and precise, rapid deformation detection method is required for the maintenance of these tunnels. A tunnel deformation detection system called Railway Mobile Measurement System (RMMS) was developed based on mobile laser scanning technique. Herein, detailed analysis is given to prove that profiles from the laser scanner can be seen as cross-sections of the tunnel and that the corresponding error can be ignored. A wavelet filtering algorithm was developed to filter the point cloud of tunnel ancillary facilities in the cross-section points. A subsequent ellipse fitting and deformation detection method is proposed. A cross-section location method for subway tunnels is also presented based on the greyscale image converted from the tunnel's point cloud. A tunnel ring segments seams detection method is proposed to detect tunnel ring segments dislocation. The accuracy of the system was verified in a subway tunnel in Wuhan, China with a total station. The accuracy of cross-section measurement was 1.5 mm, the repeatability of the overall and local deformation measurement was 0.5 and 0.9 mm, respectively. This system completely fulfils the accuracy requirement of railway tunnels deformation detection and its efficiency is significantly higher than that of the traditional method.
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title_short	Shield subway tunnel deformation detection based on mobile laser scanning
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author2	Ren, Xiaochun Mao, Qingzhou Hu, Qingwu Wang, Wei
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up_date	2024-07-06T17:30:16.794Z
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Shield subway tunnel deformation detection based on mobile laser scanning

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