混凝土裂缝监测与检测技术发展动态综述
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摘要
混凝土裂缝的监测与检测工作对于基础设施的养护管理和性能评价具有重要意义,然而,传统监测技术难以感知新裂缝的产生,传统检测技术高度依赖检测人员的经验。针对以上问题,分别介绍了基于柔性导电涂料、长标距光纤光栅的混凝土裂缝监测技术及基于机器视觉的混凝土裂缝检测技术,分析其工作原理与应用案例,为混凝土裂缝监测技术和检测技术的研究提供参考。
Crack monitoring and detection have importance sense to the maintenance management and performance evaluation of civil infrastructure. However, the conventional monitoring methods are difficult to perceive the generation of new cracks. Besides, the reliability of conventional detection methods are highly dependent on the inspectors' experience. To solve these problems, the crack monitoring technology of flexible conductive paint, the crack detection technologies of long-scale fiber grating and computer vision based methods are discussed. Their principles and application cases are introduced to provide reference for the research of concrete crack monitoring and detection technologies.
Crack monitoring and detection have importance sense to the maintenance management and performance evaluation of civil infrastructure. However, the conventional monitoring methods are difficult to perceive the generation of new cracks. Besides, the reliability of conventional detection methods are highly dependent on the inspectors' experience. To solve these problems, the crack monitoring technology of flexible conductive paint, the crack detection technologies of long-scale fiber grating and computer vision based methods are discussed. Their principles and application cases are introduced to provide reference for the research of concrete crack monitoring and detection technologies.
引文
[1] 中华人民共和国住房和城乡建设部.混凝土结构设计规范:GB 50010—2010[S].北京:人民交通出版社,2010.
[2] 于百勇,赵启林,邓安仲,等.基于柔性导电涂料的地铁隧道混凝土裂缝监测元件辊涂成型工艺:CN ■
[3] 邓安仲,赵启林,李胜波,等.基于导电膜电阻拉-敏效应的混凝土裂缝分布式监测技术[J].解放军理工大学学报(自然科学版),2010,11(2):162-167.
[4] HOLDER D S,DJAJAPUTRA D.Electrical impedance tomography:methods,history and applications[J].Medical physics,2005,32(8):27-31.
[5] BROWN B H.Electrical impedance tomography (EIT):a review[J].Journal of medical engineering & technology,2003,27(3):97-108.
[6] HALLAJI M,SEPPANEN A,POUR G M.Electrical impedance tomography-based sensing skin for quantitative imaging of damage in concrete[J].Smart materials and structures,2014,23(8):85-90.
[7] HALLAJI M,POUR G M.A new sensing skin for qualitative damage detection in concrete elements:rapid difference imaging with electrical resistance tomography[J].NDT & E international,2014(68):13-21.
[8] 李超.导电薄膜在桥梁结构表面应变及裂缝监测中的应用[D].吉林:吉林大学,2016.
[9] HILL K O,FUJII Y,JOHNSON D C,et al.Photosensitivity in optical fiber waveguides:application to reflection filter fabrication[J].Applied physics letters,1978,32(10):647-649.
[10] 魏洋,卢海鹏,刘小明,等.基于长标距光纤光栅传感器的连续梁桥监测技术[J].铁道科学与工程学报,2017,14(10):2231-2238.
[11] 张丹,施斌,吴智深,等.BOTDR分布式光纤传感器及其在结构健康监测中的应用[J].土木工程学报,2003(11):83-87.
[12] CHEN S Z,WU G,XING T,et al.Prestressing force monitoring method for a box girder through distributed long-gauge FBG sensors[J].Smart materials & structures,2017,27(1):27-30.
[13] ZHANG Q Q,XIA Q,ZHANG J,et al.Optimal layout of long-gauge sensors for deformation distribution identification[J].Smart structures and systems,2016,18(3):1222-1228
[14] 李水扬,李峰,马青那,等.动态监测技术在FRP试验中的应用[J].现代交通技术,2015,12(5):35-39.
[15] 杨丹.基于分布式传感的中小型桥梁荷载识别技术研究[D].南京:东南大学,2013.
[16] 郭余根.基于长标距分布式布拉格光纤光栅(FBG)传感的地铁基坑施工监测[J].城市轨道交通研究,2013,16(7):26-29,34.
[17] IKEDA T,YASUI S,MINAMIYAMA S,et al.Stable impact and contact force control by UAV for inspection of floor slab of bridge[J].Advanced robotics,2018,32(19):1061-1076.
[18] PEDRO J S,PABLO R,BEGORIA A,et al.Robotic system for inspection by contact of bridge beams using UAVS[J].Sensors,2019,19(2):17-21.
[19] MYEONG W,MYUNG H.Development of a wall-climbing drone capable of vertical soft landing using a tilt-rotor mechanism[J].IEEE access,2019(7):4868-4879.
[20] 赵启林,冯兆祥,吉林,等.基于数码摄像技术的桥梁检测仪系统:CN.■
[21] 陈克.桥梁检测爬壁机器人区域覆盖问题研究[D].南京:南京理工大学,2018.
[22] SINTOV A,AVRAMOVICH T,SHAPIRO A.Design and motion planning of an autonomous climbing robot with claws[J].Robotics & autonomous systems,2011,59(11):1008-1019.
[23] LEE J H,LEE J M,KIM H J,et al.Machine vision system for automatic inspection of bridges[C]// Image and signal processing,2008.New York:IEEE,2008:363-366.
[24] VICTORES J G,MARTINEZ S,JARDON A,et al.Robot-aided tunnel inspection and maintenance system by vision and proximity sensor integration[J].Automation in construction,2011,20(5):629-636.
[25] 庞娜,赵启林,芮挺,等.基于机器视觉的桥梁检测技术现状及发展[J].现代交通技术,2015,12(6):25-31.
[26] 范宇鑫.智能化桥检车在混凝土桥梁裂缝自动检测中的关键技术研究[D].南京:南京工业大学,2018.
[27] 彭博,蒋阳升,韩世凡,等.路面裂缝图像自动识别算法综述[J].公路交通科技,2014,31(7):19-25.
[28] OHTSU N.A threshold selection method from gray-level histograms[J].IEEE trans.syst.man.cybern,1979,9(1):62-66.
[29] JITPRASITHSIRI S,LEE H,SORCIC R,et al.Development of digital image-processing algorithm to compute unified crack index for salt lake city[J].Transportation research record journal of the transportation research board,1996,1526(1):142-148.
[30] TONG X,GUO J,LING Y,et al.A new image-based method for concrete bridge bottom crack detection[C]// International conference on image analysis and signal processing.New York:IEEE,2011:568-571.
[31] 徐志刚,赵祥模,宋焕生,等.基于直方图估计和形状分析的沥青路面裂缝识别算法[J].仪器仪表学报,2010,31(10):2260-2266.
[32] 马方园.桥梁毁伤非接触快速检测系统研制[D].南京:解放军理工大学,2010.
[33] FANY X,ZHAO Q L,NI S D,et al.Crack detection based on the meso-scale geometric features for visual concrete bridge inspection[J].Journal of electronic imaging,2018,27(5):1552-1555.
[34] 彭博,蒋阳升,韩世凡,等.路面裂缝图像自动识别算法综述[J].公路交通科技,2014,31(7):19-25.
[35] XU G,MA J,LIU F,et al.Automatic recognition of pavement surface crack based on BP neural network[C]// International conference on computer and electrical engineering.New York:IEEE Computer society,2008.
[36] 樊瑶.基于图像处理的路面裂缝检测关键技术研究[D].西安:长安大学,2016.
[37] 马卫飞.基于深度学习的桥梁裂缝检测算法研究[D].西安:陕西师范大学,2018.
[38] YEUM C M,DYKE S J,RAMIREZ J.Visual data classification in post-event building reconnaissance[J].Engineering structures,2018(155):16-24.
[39] ZHANG A,WANG K C P,LI B,et al.Automated pixel-level pavement crack detection on 3D asphalt surfaces using a deep-Learning network:pixel-level pavement crack detection on 3D asphalt surfaces[J].Computer-aided civil and infrastructure engineering,2017,32(5):361-378.
[40] CHEN F C,JAHANSHAHI R M R.NB-CNN:deep learning-based crack detection using convolutional neural network and na?ve bayes data fusion[J].IEEE transactions on industrial electronics,2017(99):1-4.
[41] CHA Y J,CHOI W,SUH G,et al.Autonomous structural visual inspection using region-based deep learning for detecting multiple damage types[J].Computer-aided civil and infrastructure engineering,2017(4):1-17.
[2] 于百勇,赵启林,邓安仲,等.基于柔性导电涂料的地铁隧道混凝土裂缝监测元件辊涂成型工艺:CN ■
[3] 邓安仲,赵启林,李胜波,等.基于导电膜电阻拉-敏效应的混凝土裂缝分布式监测技术[J].解放军理工大学学报(自然科学版),2010,11(2):162-167.
[4] HOLDER D S,DJAJAPUTRA D.Electrical impedance tomography:methods,history and applications[J].Medical physics,2005,32(8):27-31.
[5] BROWN B H.Electrical impedance tomography (EIT):a review[J].Journal of medical engineering & technology,2003,27(3):97-108.
[6] HALLAJI M,SEPPANEN A,POUR G M.Electrical impedance tomography-based sensing skin for quantitative imaging of damage in concrete[J].Smart materials and structures,2014,23(8):85-90.
[7] HALLAJI M,POUR G M.A new sensing skin for qualitative damage detection in concrete elements:rapid difference imaging with electrical resistance tomography[J].NDT & E international,2014(68):13-21.
[8] 李超.导电薄膜在桥梁结构表面应变及裂缝监测中的应用[D].吉林:吉林大学,2016.
[9] HILL K O,FUJII Y,JOHNSON D C,et al.Photosensitivity in optical fiber waveguides:application to reflection filter fabrication[J].Applied physics letters,1978,32(10):647-649.
[10] 魏洋,卢海鹏,刘小明,等.基于长标距光纤光栅传感器的连续梁桥监测技术[J].铁道科学与工程学报,2017,14(10):2231-2238.
[11] 张丹,施斌,吴智深,等.BOTDR分布式光纤传感器及其在结构健康监测中的应用[J].土木工程学报,2003(11):83-87.
[12] CHEN S Z,WU G,XING T,et al.Prestressing force monitoring method for a box girder through distributed long-gauge FBG sensors[J].Smart materials & structures,2017,27(1):27-30.
[13] ZHANG Q Q,XIA Q,ZHANG J,et al.Optimal layout of long-gauge sensors for deformation distribution identification[J].Smart structures and systems,2016,18(3):1222-1228
[14] 李水扬,李峰,马青那,等.动态监测技术在FRP试验中的应用[J].现代交通技术,2015,12(5):35-39.
[15] 杨丹.基于分布式传感的中小型桥梁荷载识别技术研究[D].南京:东南大学,2013.
[16] 郭余根.基于长标距分布式布拉格光纤光栅(FBG)传感的地铁基坑施工监测[J].城市轨道交通研究,2013,16(7):26-29,34.
[17] IKEDA T,YASUI S,MINAMIYAMA S,et al.Stable impact and contact force control by UAV for inspection of floor slab of bridge[J].Advanced robotics,2018,32(19):1061-1076.
[18] PEDRO J S,PABLO R,BEGORIA A,et al.Robotic system for inspection by contact of bridge beams using UAVS[J].Sensors,2019,19(2):17-21.
[19] MYEONG W,MYUNG H.Development of a wall-climbing drone capable of vertical soft landing using a tilt-rotor mechanism[J].IEEE access,2019(7):4868-4879.
[20] 赵启林,冯兆祥,吉林,等.基于数码摄像技术的桥梁检测仪系统:CN.■
[21] 陈克.桥梁检测爬壁机器人区域覆盖问题研究[D].南京:南京理工大学,2018.
[22] SINTOV A,AVRAMOVICH T,SHAPIRO A.Design and motion planning of an autonomous climbing robot with claws[J].Robotics & autonomous systems,2011,59(11):1008-1019.
[23] LEE J H,LEE J M,KIM H J,et al.Machine vision system for automatic inspection of bridges[C]// Image and signal processing,2008.New York:IEEE,2008:363-366.
[24] VICTORES J G,MARTINEZ S,JARDON A,et al.Robot-aided tunnel inspection and maintenance system by vision and proximity sensor integration[J].Automation in construction,2011,20(5):629-636.
[25] 庞娜,赵启林,芮挺,等.基于机器视觉的桥梁检测技术现状及发展[J].现代交通技术,2015,12(6):25-31.
[26] 范宇鑫.智能化桥检车在混凝土桥梁裂缝自动检测中的关键技术研究[D].南京:南京工业大学,2018.
[27] 彭博,蒋阳升,韩世凡,等.路面裂缝图像自动识别算法综述[J].公路交通科技,2014,31(7):19-25.
[28] OHTSU N.A threshold selection method from gray-level histograms[J].IEEE trans.syst.man.cybern,1979,9(1):62-66.
[29] JITPRASITHSIRI S,LEE H,SORCIC R,et al.Development of digital image-processing algorithm to compute unified crack index for salt lake city[J].Transportation research record journal of the transportation research board,1996,1526(1):142-148.
[30] TONG X,GUO J,LING Y,et al.A new image-based method for concrete bridge bottom crack detection[C]// International conference on image analysis and signal processing.New York:IEEE,2011:568-571.
[31] 徐志刚,赵祥模,宋焕生,等.基于直方图估计和形状分析的沥青路面裂缝识别算法[J].仪器仪表学报,2010,31(10):2260-2266.
[32] 马方园.桥梁毁伤非接触快速检测系统研制[D].南京:解放军理工大学,2010.
[33] FANY X,ZHAO Q L,NI S D,et al.Crack detection based on the meso-scale geometric features for visual concrete bridge inspection[J].Journal of electronic imaging,2018,27(5):1552-1555.
[34] 彭博,蒋阳升,韩世凡,等.路面裂缝图像自动识别算法综述[J].公路交通科技,2014,31(7):19-25.
[35] XU G,MA J,LIU F,et al.Automatic recognition of pavement surface crack based on BP neural network[C]// International conference on computer and electrical engineering.New York:IEEE Computer society,2008.
[36] 樊瑶.基于图像处理的路面裂缝检测关键技术研究[D].西安:长安大学,2016.
[37] 马卫飞.基于深度学习的桥梁裂缝检测算法研究[D].西安:陕西师范大学,2018.
[38] YEUM C M,DYKE S J,RAMIREZ J.Visual data classification in post-event building reconnaissance[J].Engineering structures,2018(155):16-24.
[39] ZHANG A,WANG K C P,LI B,et al.Automated pixel-level pavement crack detection on 3D asphalt surfaces using a deep-Learning network:pixel-level pavement crack detection on 3D asphalt surfaces[J].Computer-aided civil and infrastructure engineering,2017,32(5):361-378.
[40] CHEN F C,JAHANSHAHI R M R.NB-CNN:deep learning-based crack detection using convolutional neural network and na?ve bayes data fusion[J].IEEE transactions on industrial electronics,2017(99):1-4.
[41] CHA Y J,CHOI W,SUH G,et al.Autonomous structural visual inspection using region-based deep learning for detecting multiple damage types[J].Computer-aided civil and infrastructure engineering,2017(4):1-17.
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