Automated runway groove measurement and evaluation
Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimension...
Ausführliche Beschreibung
Autor*in: |
Li, Lin [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2016 |
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Schlagwörter: |
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Anmerkung: |
© Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017 |
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Übergeordnetes Werk: |
Enthalten in: KSCE journal of civil engineering - Seoul : Korean Soc. of Civil Engineers, 1997, 21(2016), 3 vom: 06. Juni, Seite 758-765 |
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Übergeordnetes Werk: |
volume:21 ; year:2016 ; number:3 ; day:06 ; month:06 ; pages:758-765 |
Links: |
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DOI / URN: |
10.1007/s12205-016-0789-6 |
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Katalog-ID: |
SPR025271520 |
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245 | 1 | 0 | |a Automated runway groove measurement and evaluation |
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520 | |a Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. | ||
650 | 4 | |a airport runway |7 (dpeaa)DE-He213 | |
650 | 4 | |a groove |7 (dpeaa)DE-He213 | |
650 | 4 | |a groove measurement |7 (dpeaa)DE-He213 | |
650 | 4 | |a groove evaluation |7 (dpeaa)DE-He213 | |
650 | 4 | |a moving average filter |7 (dpeaa)DE-He213 | |
650 | 4 | |a beam filter |7 (dpeaa)DE-He213 | |
700 | 1 | |a Wang, Kelvin C. P. |4 aut | |
700 | 1 | |a Li, Qiang Joshua |4 aut | |
700 | 1 | |a Luo, Wenting |4 aut | |
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10.1007/s12205-016-0789-6 doi (DE-627)SPR025271520 (SPR)s12205-016-0789-6-e DE-627 ger DE-627 rakwb eng Li, Lin verfasserin aut Automated runway groove measurement and evaluation 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. airport runway (dpeaa)DE-He213 groove (dpeaa)DE-He213 groove measurement (dpeaa)DE-He213 groove evaluation (dpeaa)DE-He213 moving average filter (dpeaa)DE-He213 beam filter (dpeaa)DE-He213 Wang, Kelvin C. P. aut Li, Qiang Joshua aut Luo, Wenting aut Enthalten in KSCE journal of civil engineering Seoul : Korean Soc. of Civil Engineers, 1997 21(2016), 3 vom: 06. Juni, Seite 758-765 (DE-627)57517238X (DE-600)2446036-9 1976-3808 nnns volume:21 year:2016 number:3 day:06 month:06 pages:758-765 https://dx.doi.org/10.1007/s12205-016-0789-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 21 2016 3 06 06 758-765 |
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10.1007/s12205-016-0789-6 doi (DE-627)SPR025271520 (SPR)s12205-016-0789-6-e DE-627 ger DE-627 rakwb eng Li, Lin verfasserin aut Automated runway groove measurement and evaluation 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. airport runway (dpeaa)DE-He213 groove (dpeaa)DE-He213 groove measurement (dpeaa)DE-He213 groove evaluation (dpeaa)DE-He213 moving average filter (dpeaa)DE-He213 beam filter (dpeaa)DE-He213 Wang, Kelvin C. P. aut Li, Qiang Joshua aut Luo, Wenting aut Enthalten in KSCE journal of civil engineering Seoul : Korean Soc. of Civil Engineers, 1997 21(2016), 3 vom: 06. Juni, Seite 758-765 (DE-627)57517238X (DE-600)2446036-9 1976-3808 nnns volume:21 year:2016 number:3 day:06 month:06 pages:758-765 https://dx.doi.org/10.1007/s12205-016-0789-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 21 2016 3 06 06 758-765 |
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10.1007/s12205-016-0789-6 doi (DE-627)SPR025271520 (SPR)s12205-016-0789-6-e DE-627 ger DE-627 rakwb eng Li, Lin verfasserin aut Automated runway groove measurement and evaluation 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. airport runway (dpeaa)DE-He213 groove (dpeaa)DE-He213 groove measurement (dpeaa)DE-He213 groove evaluation (dpeaa)DE-He213 moving average filter (dpeaa)DE-He213 beam filter (dpeaa)DE-He213 Wang, Kelvin C. P. aut Li, Qiang Joshua aut Luo, Wenting aut Enthalten in KSCE journal of civil engineering Seoul : Korean Soc. of Civil Engineers, 1997 21(2016), 3 vom: 06. Juni, Seite 758-765 (DE-627)57517238X (DE-600)2446036-9 1976-3808 nnns volume:21 year:2016 number:3 day:06 month:06 pages:758-765 https://dx.doi.org/10.1007/s12205-016-0789-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 21 2016 3 06 06 758-765 |
allfieldsGer |
10.1007/s12205-016-0789-6 doi (DE-627)SPR025271520 (SPR)s12205-016-0789-6-e DE-627 ger DE-627 rakwb eng Li, Lin verfasserin aut Automated runway groove measurement and evaluation 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. airport runway (dpeaa)DE-He213 groove (dpeaa)DE-He213 groove measurement (dpeaa)DE-He213 groove evaluation (dpeaa)DE-He213 moving average filter (dpeaa)DE-He213 beam filter (dpeaa)DE-He213 Wang, Kelvin C. P. aut Li, Qiang Joshua aut Luo, Wenting aut Enthalten in KSCE journal of civil engineering Seoul : Korean Soc. of Civil Engineers, 1997 21(2016), 3 vom: 06. Juni, Seite 758-765 (DE-627)57517238X (DE-600)2446036-9 1976-3808 nnns volume:21 year:2016 number:3 day:06 month:06 pages:758-765 https://dx.doi.org/10.1007/s12205-016-0789-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 21 2016 3 06 06 758-765 |
allfieldsSound |
10.1007/s12205-016-0789-6 doi (DE-627)SPR025271520 (SPR)s12205-016-0789-6-e DE-627 ger DE-627 rakwb eng Li, Lin verfasserin aut Automated runway groove measurement and evaluation 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. airport runway (dpeaa)DE-He213 groove (dpeaa)DE-He213 groove measurement (dpeaa)DE-He213 groove evaluation (dpeaa)DE-He213 moving average filter (dpeaa)DE-He213 beam filter (dpeaa)DE-He213 Wang, Kelvin C. P. aut Li, Qiang Joshua aut Luo, Wenting aut Enthalten in KSCE journal of civil engineering Seoul : Korean Soc. of Civil Engineers, 1997 21(2016), 3 vom: 06. Juni, Seite 758-765 (DE-627)57517238X (DE-600)2446036-9 1976-3808 nnns volume:21 year:2016 number:3 day:06 month:06 pages:758-765 https://dx.doi.org/10.1007/s12205-016-0789-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 21 2016 3 06 06 758-765 |
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Li, Lin @@aut@@ Wang, Kelvin C. P. @@aut@@ Li, Qiang Joshua @@aut@@ Luo, Wenting @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR025271520</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230403064946.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s12205-016-0789-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR025271520</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12205-016-0789-6-e</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">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Li, Lin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Automated runway groove measurement and evaluation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</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="500" ind1=" " ind2=" "><subfield code="a">© Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. 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Li, Lin |
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Li, Lin misc airport runway misc groove misc groove measurement misc groove evaluation misc moving average filter misc beam filter Automated runway groove measurement and evaluation |
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automated runway groove measurement and evaluation |
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Automated runway groove measurement and evaluation |
abstract |
Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. © Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017 |
abstractGer |
Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. © Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017 |
abstract_unstemmed |
Abstract Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. © Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2017 |
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3 |
title_short |
Automated runway groove measurement and evaluation |
url |
https://dx.doi.org/10.1007/s12205-016-0789-6 |
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author2 |
Wang, Kelvin C. P. Li, Qiang Joshua Luo, Wenting |
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Wang, Kelvin C. P. Li, Qiang Joshua Luo, Wenting |
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57517238X |
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doi_str |
10.1007/s12205-016-0789-6 |
up_date |
2024-07-03T14:57:14.430Z |
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score |
7.398575 |