Dynamic measurement of stay-cable force using digital image techniques

Measurement - Tập 151 - Trang 107211 - 2020
Wenkang Du1, Dong Lei1, Pengxiang Bai1, Feipeng Zhu1, Zhentian Huang1
1College of Mechanics and Materials, Hohai University, Nanjing 211100, PR China

Tài liệu tham khảo

Zui, 1996, Practical formula for estimation of cable tension by vibration method, ASCE J. Struct. Eng., 122, 651, 10.1061/(ASCE)0733-9445(1996)122:6(651) Shimada, 1995 Wen-hwa, 2018, Tension determination for suspenders of arch bridge based on multiple vibration measurements concentrated at one end, Measurement, 123, 254 Chen, 2016, Tension determination of stay cable or external tendon with complicated constraints using multiple vibration measurements, Measurement, 86, 182, 10.1016/j.measurement.2016.02.053 Chen, 2016, Identification of spatio-temporal distribution of vehicle loads on long-span bridges using computer vision technology, Struct. Control Health Monit., 23, 517, 10.1002/stc.1780 Spencer, 2019, Advances in computer vision-based civil infrastructure inspection and monitoring, Engineering, 5, 199, 10.1016/j.eng.2018.11.030 Bigger, 2018, Dynamic response of aluminum 5083 during Taylor impact using digital image correlation, Exp. Mech., 58, 951, 10.1007/s11340-018-0392-5 Nam, 2013, An efficient image-based damage detection for cable surface in cable-stayed bridges, NDT E Int., 58, 18, 10.1016/j.ndteint.2013.04.006 Mahal, 2015, Using digital image correlation to evaluate fatigue behavior of strengthened reinforced concrete beams, Eng. Struct., 105, 277, 10.1016/j.engstruct.2015.10.017 Chang, 2007, Flexible videogrammetric technique for three-dimensional structural vibration, Measurement, 133, 656 Lee, 2006, Real-time displacement measurement of a flexible bridge using digital image processing techniques, Exp. Mech., 46, 105, 10.1007/s11340-006-6124-2 Choi, 2011, Structural dynamic displacement vision system using digital image processing, NDT E Int., 44, 597, 10.1016/j.ndteint.2011.06.003 Sung-wan, 2013, Dynamic characteristics of suspension bridge hanger cables using digital image processing, NDT E Int., 59, 25, 10.1016/j.ndteint.2013.05.002 Sung-wan, 2013, Vision-based monitoring system for evaluating cable tensile forces on a cable-stayed bridge, Struct. Healthy Monitor., 12, 440 Tian, 2016, Remote bridge deflection measurement using an advanced video deflectometer and actively illuminated LED targets, Sensors (Basel, Switzerland)., 16, 1344, 10.3390/s16091344 Feng, 2017, Cable tension force estimate using novel noncontact vision-based sensor, Measurement, 99, 44, 10.1016/j.measurement.2016.12.020 Li, 2019, Cable surface damage detection in cable-stayed bridges using optical techniques and image mosaicking, Opt. Laser Technol., 110, 36, 10.1016/j.optlastec.2018.07.012 Ellenberg, 2014, Use of unmanned aerial vehicle for quantitative infrastructure evaluation, J. Infrastruct. Syst., 21, 04014054, 10.1061/(ASCE)IS.1943-555X.0000246 Morgenthal, 2014, Quality assessment of unmanned aerial vehicle (UAV) based visual inspection of structures, Adv. Struct. Eng., 17, 289, 10.1260/1369-4332.17.3.289 Rathinam, 2008, Vision-based monitoring of locally linear structures using an unmanned aerial vehicle, J. Infrastruct. Syst., 14, 52, 10.1061/(ASCE)1076-0342(2008)14:1(52) Omar, 2017, Remote sensing of concrete bridge decks using unmanned aerial vehicle infrared thermography, Autom. Constr., 83, 360, 10.1016/j.autcon.2017.06.024 Pereira, 2017, Embedded image processing systems for automatic recognition of cracks using UAVs, IFAC-Papers OnLine, 48, 16, 10.1016/j.ifacol.2015.08.101 Lei, 2018, New crack detection method for bridge inspection using UAV incorporating image processing, J. Aerosp. Eng., 31, 04018058, 10.1061/(ASCE)AS.1943-5525.0000879 Reagan, 2018, Feasibility of using digital image correlation for unmanned aerial vehicle structural health monitoring of bridges, Struct. Health Monitor., 17, 10.1177/1475921717735326 Hang, 2017, Split-brain autoencoders: unsupervised learning by cross-channel prediction, 645 Zhang, 2016, Road crack detection using deep convolutional neural network, 3708 Huang, 2019, Modified moving least square collocation method for solving wave equations, Adv. Appl. Math. Mech., 10, 1 Cha, 2017, Deep learning-based crack damage detection using convolution alneural networks, Comput.-Aided Civ. Infrastruct. Eng., 32, 361, 10.1111/mice.12263 Gao, 2018, Deep transfer learning for image-based structural damage recognition, Comput.-Aided Civ. Infrastruct. Eng., 33, 748, 10.1111/mice.12363 Spencer, 2019, Advances in computer vision-based civil infrastructure inspection and monitoring, Engineering, 5, 199, 10.1016/j.eng.2018.11.030 Feng, 2018, Computer vision for SHM of civil infrastructure: from dynamic response measurement to damage detection – a review, Eng. Struct., 156, 105, 10.1016/j.engstruct.2017.11.018 Pan, 2016, Real-time, non-contact and targetless measurement of vertical deflection of bridges using off-axis digital image correlation, NDT E Int., 79, 73, 10.1016/j.ndteint.2015.12.006 Helfrick, 2011, 3D digital image correlation methods for full-field vibration measurement, Mech. Syst. Sig. Process., 25, 917, 10.1016/j.ymssp.2010.08.013 Mas, 2016, Methods and algorithms for video-based multi-point frequency measuring and mapping, Measurement, 85, 164, 10.1016/j.measurement.2016.02.042 Sutton, 2017, Recent progress in digital image correlation: background and developments since the 2013 W M Murray lecture, Exp. Mech., 57, 1, 10.1007/s11340-016-0233-3 Pan, 2018, Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals, Meas. Sci. Technol., 29, 10.1088/1361-6501/aac55b Lei, 2017, Experimental research on impact damage of Xiaowan arch dam model by digital image correlation, Constr. Build. Mater., 147, 168, 10.1016/j.conbuildmat.2017.04.143 Zhu, 2018, Accurate measurement of elastic modulus of specimen with initial bending using two-dimensional DIC and dual-reflector imaging technique, Measurement, 119, 18, 10.1016/j.measurement.2018.01.043 Zhao, 2019, Experimental study on micro-damage identification in reinforced concrete beam with wavelet packet and DIC method, Constr. Build. Mater., 210, 338, 10.1016/j.conbuildmat.2019.03.175 Zhu, 2019, A novel in situ calibration of object distance of an imaging lens based on optical refraction and two-dimensional DIC, Opt. Lasers Eng., 120, 110, 10.1016/j.optlaseng.2019.03.023 Ghorbani, 2015, Full-field deformation measurement and crack mapping on confined masonry walls using digital image correlation, Exp. Mech., 55, 227, 10.1007/s11340-014-9906-y J.P. Lewis, Fast normalized cross-correlation. Research Gate, 2013. https://www.researchgate.net/publication/2378357. Huang, 2019, Boundary moving least square method for numerical evaluation of two-dimensional elastic membrane and plate dynamics problems, Eng. Anal. Boundary Elem., 108, 41, 10.1016/j.enganabound.2019.08.002