基于图像处理技术的房屋裂缝宽度变化实时监测研究
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摘要
基于MATLAB数字图像处理技术,对房屋裂缝宽度变化进行实时监测,依次对采集裂缝图像进行灰度化、图像滤波、二值化、目标区域分割标记和像素标定等处理,计算获得图像裂缝最大宽度值及单次变化值、人工标志间距离变化值。通过与实测数据相比,运用本文提出的计算方法获得房屋裂缝检测数据的识别精度为99.19%。利用MATLAB图像处理技术获得人工标志间距离变化值与最大裂缝宽度变化值累计相对误差为0.16%,人工标志间距离变化能够反映裂缝宽度变化情况。对于实际情况中无法寻找裂缝最大宽度处,而进行裂缝宽度变化实时监测时,可用人工标志间距离变化反映裂缝宽度变化情况。
Based on MATLAB digital image processing technology,real-time monitoring of housing crack width change is carried out. In turn,the collected images are processed with grayscale,image filtering,binarization,segmentation of the target area and pixel calibration. The maximum width of the crack and the single change value of the image and the distance change between the artificial markers are calculated. Compared with the measured data,the accuracy of the crack detection data obtained by the proposed method is99. 19%. By using MATLAB image processing technology,the accumulative relative error between the change of distance between artificial markers and the maximum crack width is 0. 16%. The change of distance between artificial markers can reflect the change of crack width. When the maximum width of the crack can not be found in the actual situation,the monitoring of the crack width is carried out in real time. Changes in the distance between available artificial markers reflect changes in crack width.
Based on MATLAB digital image processing technology,real-time monitoring of housing crack width change is carried out. In turn,the collected images are processed with grayscale,image filtering,binarization,segmentation of the target area and pixel calibration. The maximum width of the crack and the single change value of the image and the distance change between the artificial markers are calculated. Compared with the measured data,the accuracy of the crack detection data obtained by the proposed method is99. 19%. By using MATLAB image processing technology,the accumulative relative error between the change of distance between artificial markers and the maximum crack width is 0. 16%. The change of distance between artificial markers can reflect the change of crack width. When the maximum width of the crack can not be found in the actual situation,the monitoring of the crack width is carried out in real time. Changes in the distance between available artificial markers reflect changes in crack width.
引文
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[24]房屋裂缝检测与处理技术规程:CECS293:2011[S].北京:中国计划出版社,2011.
[2]佚名.韩国三丰百货大楼倒塌之谜[J].中国减灾,2007(7):42-43.
[3]邱青青.在建房屋墙体倒塌7人被砸[EB/OL].(2009-03-09)[2017-11-13].http://ah.anhuinews.com/system/2009/03/09/002223241.shtml.
[4]张燕翔.房屋裂缝居者难安[EB/OL].(2016-06-30)[2017-11-13].https://www.sohu.com/a/100048219_258863.
[5]杨茜.夫妇发现楼房开裂喊出全部邻居半小时后楼坍塌[EB/OL].(2015-06-10)[2017-11-13].https://news.qq.com/a/20150609/046876.htm?tu_biz=1.114.2.1.
[6]ITO A,AOKI Y,HASHIMOTO S.Accurate extraction and measurement of fine cracks from concrete block surface image[C]//IECON,2002,3:2202-2207.
[7]YAMAGUCHI T,HASHIMOTO S.Automated crack detection for concrete surface image using percolation model and edge information[C]//IEEE Industrial Electronics,IECON 2006-Conference on,2007:3355-3360.
[8]SOHN H G,LIM Y M,YUN K H,et al.Monitoring crack changes in concrete structures[J].Computer-Aided Civil and Infrastructure Engineering,2010,20(1):52-61.
[9]杨美玲.基于图像处理的混凝土桥梁裂缝测量与分析[D].武汉:华中科技大学,2009.
[10]徐兵.基于图像处理技术的桥梁病害检查和裂缝测量研究[D].西安:长安大学,2009.
[11]乔岳强,吴建超,冯谦,等.巴东Ms5.1地震震害分布特征[J].大地测量与地球动力学,2014,34(3):15-19.
[12]周军学,聂高众,谭劲先,等.2016年7月31日广西苍梧5.4级地震灾害特征分析[J].地震地质,2017,39(4):780-792.
[13]李文波,杨保春.基于图像处理技术的混凝土桥梁裂缝宽度检测[J].湖南交通科技,2015,41(1):119-122.
[14]冯洋.基于MATLAB GUI的裂缝宽度测量系统设计[J].河南科学,2013,31(10):1652-1654.
[15]彭海涛.基于图像分析技术的混凝土结构外观质量检测与评定[D].长沙:湖南大学,2011.
[16]夏日诚.基于彩色和灰度图像的色图设计[D].成都:电子科技大学,2007.
[17]张强,王正林.精通MATLAB图像处理[M].北京:电子工业出版社,2012.
[18]卢晓霞.基于图像处理的混凝土裂缝宽度检测技术的研究[D].成都:电子科技大学,2010.
[19]王耀南,李树涛,毛建旭.计算机图像处理与识别技术[M].北京:高等教育出版社,2001.
[20]罗希平,田捷,诸葛婴,等.图像分割方法综述[J].模式识别与人工智能,1999,12(3):300-312.
[21]章毓晋.图像分割[M].北京:科学出版社,2001.
[22]郭艳平,侯凤贞.纸币面值识别系统图像分割技术的算法[J].重庆理工大学学报(自然科学版),2008,22(11):124-126.
[23]刘超.MATLAB基础与实践教程[M].北京:机械工业出版社,2016.
[24]房屋裂缝检测与处理技术规程:CECS293:2011[S].北京:中国计划出版社,2011.