摘要
混凝土衬砌的渠道、隧洞及渡槽等输水结构都需要测量糙率以估计过流能力和水头损失,而混凝土表面粗糙度是考量其糙率的重要参数之一。依据数字图像技术,提出一种混凝土表面粗糙度新表征方法。利用智能手机采集混凝土粗糙面像素特征,研究图像预处理对像素分布特征的影响,构建表面粗糙度与灰度均值及相对最大凸起高度的函数关系。图像预处理对像素分布特征影响显著,粗糙度与最大凸起高度正相关,与灰度均值负相关,拟合计算值与实测结果吻合,平均绝对百分比误差MAPE、平均绝对误差MAE和均方根误差RMSE分别为4.04%、0.203mm和0.271mm。将所提出的表征方法应用于某渠道混凝土壁面粗糙度测量,综合糙率公式计算得到该渠段糙率为0.01429,小于综合设计糙率0.01500。该混凝土表面粗糙度表征方法合理,以期为水泥砂浆及混凝土表面粗糙度估算提供新途径。
Water conveyance structures such as concrete lined canals,tunnels and aqueducts need to be measured for the surface roughness to estimate the flow capacity and head loss.The surface roughness of concrete is one of the important parameters in considering its roughness coefficient.Based on the digital image processing technology,an innovative characterization method for surface roughness of concrete was presented.The pixel distribution characteristics of the rough surface of concrete were collected by a smart phone.The influence of image preprocessing process on pixel distribution characteristics was analyzed.The functional relationship between the surface roughness of concrete and the mean value of digital image pixels,the relative maximum bulge height was proposed.The results show that the pixel distribution characteristics are significantly affected by image preprocessing process.The surface roughness of the concrete is positively correlated with the relative maximum bulge height,and negatively correlated with the mean value of the digital image pixels.The roughness of the concrete calculated by the fitting formula is consistent with the measured values.The mean absolute percentage(MAPE),error mean absolute error(MAE)and root mean square error(RMSE)were 4.04%,0.203 mm and 0.271 mm,respectively.The proposed characterization method was applied to the measurement of concrete wall roughness of a channel.Combined with the comprehensive roughness formula,it was calculated that the roughness of the channel section was 0.01429,which was less than the comprehensive design roughness of 0.01500.The proposed roughness characterization method is reasonable,which provides an innovation approach of estimating the surface roughness of cement mortar and concrete materials.
作者
甘磊
金洪杰
沈振中
Gan Lei;Jin Hongjie;Shen Zhenzhong(College of Water Conservancy and Hydropower Engineering,Hohai University,Nanjing 210098,China)
出处
《土木工程学报》
EI
CSCD
北大核心
2022年第8期67-76,共10页
China Civil Engineering Journal
基金
国家自然科学基金(51609073)
江苏省自然科学基金(BK20201312)
水利部堤防安全与病害防治工程技术研究中心项目(DFZX2020003)。
关键词
糙率系数
数字图像
混凝土
粗糙度
表征方法
roughness coefficient
digital image
concrete
roughness
characterization method
