Impact of tessellation surface model generation process on acoustical tire features

Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identificati...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Leupolz, Michael [verfasserIn] Radler, Timotheus [verfasserIn] Gauterin, Frank [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Photogrammetry Structure from motion Structured light Tread pattern Tire/road noise (TRN) Noise-related features

Übergeordnetes Werk:	Enthalten in: Measurement - Amsterdam [u.a.] : Elsevier Science, 1983, 219
Übergeordnetes Werk:	volume:219

DOI / URN:	10.1016/j.measurement.2023.113225

Katalog-ID:	ELV06069159X

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520			\|a Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. This paves the way for more accessible models that accelerate the statistical coupling of tire tread characteristics and their acoustic, handling or braking behavior.
650		4	\|a Photogrammetry
650		4	\|a Structure from motion
650		4	\|a Structured light
650		4	\|a Tread pattern
650		4	\|a Tire/road noise (TRN)
650		4	\|a Noise-related features
700	1		\|a Radler, Timotheus \|e verfasserin \|4 aut
700	1		\|a Gauterin, Frank \|e verfasserin \|4 aut
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matchkey_str	leupolzmichaelradlertimotheusgauterinfra:2023----:matfeslainufcmdleeainrcsoao
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bklnumber	50.21
publishDate	2023
allfields	10.1016/j.measurement.2023.113225 doi (DE-627)ELV06069159X (ELSEVIER)S0263-2241(23)00789-3 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Leupolz, Michael verfasserin aut Impact of tessellation surface model generation process on acoustical tire features 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. This paves the way for more accessible models that accelerate the statistical coupling of tire tread characteristics and their acoustic, handling or braking behavior. Photogrammetry Structure from motion Structured light Tread pattern Tire/road noise (TRN) Noise-related features Radler, Timotheus verfasserin aut Gauterin, Frank verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 219 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 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_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_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 219
spelling	10.1016/j.measurement.2023.113225 doi (DE-627)ELV06069159X (ELSEVIER)S0263-2241(23)00789-3 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Leupolz, Michael verfasserin aut Impact of tessellation surface model generation process on acoustical tire features 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. This paves the way for more accessible models that accelerate the statistical coupling of tire tread characteristics and their acoustic, handling or braking behavior. Photogrammetry Structure from motion Structured light Tread pattern Tire/road noise (TRN) Noise-related features Radler, Timotheus verfasserin aut Gauterin, Frank verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 219 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 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_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_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 219
allfields_unstemmed	10.1016/j.measurement.2023.113225 doi (DE-627)ELV06069159X (ELSEVIER)S0263-2241(23)00789-3 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Leupolz, Michael verfasserin aut Impact of tessellation surface model generation process on acoustical tire features 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. This paves the way for more accessible models that accelerate the statistical coupling of tire tread characteristics and their acoustic, handling or braking behavior. Photogrammetry Structure from motion Structured light Tread pattern Tire/road noise (TRN) Noise-related features Radler, Timotheus verfasserin aut Gauterin, Frank verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 219 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 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_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_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 219
allfieldsGer	10.1016/j.measurement.2023.113225 doi (DE-627)ELV06069159X (ELSEVIER)S0263-2241(23)00789-3 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Leupolz, Michael verfasserin aut Impact of tessellation surface model generation process on acoustical tire features 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. This paves the way for more accessible models that accelerate the statistical coupling of tire tread characteristics and their acoustic, handling or braking behavior. Photogrammetry Structure from motion Structured light Tread pattern Tire/road noise (TRN) Noise-related features Radler, Timotheus verfasserin aut Gauterin, Frank verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 219 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 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_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_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 219
allfieldsSound	10.1016/j.measurement.2023.113225 doi (DE-627)ELV06069159X (ELSEVIER)S0263-2241(23)00789-3 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Leupolz, Michael verfasserin aut Impact of tessellation surface model generation process on acoustical tire features 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. This paves the way for more accessible models that accelerate the statistical coupling of tire tread characteristics and their acoustic, handling or braking behavior. Photogrammetry Structure from motion Structured light Tread pattern Tire/road noise (TRN) Noise-related features Radler, Timotheus verfasserin aut Gauterin, Frank verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 219 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 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_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_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 219
language	English
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topic_facet	Photogrammetry Structure from motion Structured light Tread pattern Tire/road noise (TRN) Noise-related features
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container_title	Measurement
authorswithroles_txt_mv	Leupolz, Michael @@aut@@ Radler, Timotheus @@aut@@ Gauterin, Frank @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320404927
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id	ELV06069159X
language_de	englisch
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author	Leupolz, Michael
spellingShingle	Leupolz, Michael ddc 660 bkl 50.21 misc Photogrammetry misc Structure from motion misc Structured light misc Tread pattern misc Tire/road noise (TRN) misc Noise-related features Impact of tessellation surface model generation process on acoustical tire features
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topic_title	660 VZ 50.21 bkl Impact of tessellation surface model generation process on acoustical tire features Photogrammetry Structure from motion Structured light Tread pattern Tire/road noise (TRN) Noise-related features
topic	ddc 660 bkl 50.21 misc Photogrammetry misc Structure from motion misc Structured light misc Tread pattern misc Tire/road noise (TRN) misc Noise-related features
topic_unstemmed	ddc 660 bkl 50.21 misc Photogrammetry misc Structure from motion misc Structured light misc Tread pattern misc Tire/road noise (TRN) misc Noise-related features
topic_browse	ddc 660 bkl 50.21 misc Photogrammetry misc Structure from motion misc Structured light misc Tread pattern misc Tire/road noise (TRN) misc Noise-related features
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title	Impact of tessellation surface model generation process on acoustical tire features
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title_full	Impact of tessellation surface model generation process on acoustical tire features
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author_browse	Leupolz, Michael Radler, Timotheus Gauterin, Frank
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title_sort	impact of tessellation surface model generation process on acoustical tire features
title_auth	Impact of tessellation surface model generation process on acoustical tire features
abstract	Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. This paves the way for more accessible models that accelerate the statistical coupling of tire tread characteristics and their acoustic, handling or braking behavior.
abstractGer	Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. This paves the way for more accessible models that accelerate the statistical coupling of tire tread characteristics and their acoustic, handling or braking behavior.
abstract_unstemmed	Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. This paves the way for more accessible models that accelerate the statistical coupling of tire tread characteristics and their acoustic, handling or braking behavior.
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title_short	Impact of tessellation surface model generation process on acoustical tire features
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doi_str	10.1016/j.measurement.2023.113225
up_date	2024-07-06T16:42:33.740Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV06069159X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230928151708.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230721s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.measurement.2023.113225</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV06069159X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0263-2241(23)00789-3</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">660</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.21</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Leupolz, Michael</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Impact of tessellation surface model generation process on acoustical tire features</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Due to the electrification of vehicles, the focus of vehicle noise is shifting to the tires. Since tire noise is dependent of the tread pattern, methods to characterize tread patterns are required. This research investigates the effects of different processes of tire digitization on the identification of tread pattern features. An open source digitization pipeline is built to extract a tessellation surface model. This model is compared to one, generated with a commercial photogrammetric system. The comparison is based on three acoustically relevant tire features. Fully automated algorithms are introduced to extract these features from any 3D tire tessellation model. The research finds that although the resolution of the mesh surface of the proposed model is lower, feature recognition is not affected by this change. 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Impact of tessellation surface model generation process on acoustical tire features

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