水利水电技术（中英文）2024，Vol.55Issue(12)：217-227,11.DOI:10.13928/j.cnki.wrahe.2024.12.018
基于图像识别的土石坝坝料颗粒级配检测方法
Image recognition based particle gradation detection method for earth and rockfill dam materials
摘要
Abstract
[Objective]The grading of earth and rock dam materials directly affects the compaction,permeability,compressibili-ty,and stress-strain relationship of gravelly soil,which is an important criterion to ensure the stability and safety of the dam body.At present,the measurement of dam material gradation mainly adopts the sieving method,but this method has great limita-tions in terms of low construction efficiency and large error.In order to realize the intelligent detection of dam material gradation parameters,[Methods]a dam material particle gradation identification system is established by using DIP technology and artifi-cial intelligence algorithm and big data theory.Relying on the dam materials of Lianghekou Hydropower Station,a standardized sampling criterion was adopted to obtain a representative digital picture of the dam material samples,and contrast enhancement and wavelet transform as a whole were used to provide technical support for the fast and accurate segmentation of the dam materi-als,and then the threshold segmentation algorithm was used for the image segmentation of the dam materials to obtain the grada-tion curves of the dam materials based on the image recognition technology,and the corrected gradation curves were obtained by the BP neural network-based the corrected dam material gradation characteristic curve was obtained by the BP neural network based error correction model.[Results]The gradation curve obtained by this method is compared with the measured gradation curve,and it is found that both of them have a high degree of agreement,and the gradation curve obtained by this method can be used to detect the indexes of the dam material arbitrarily.[Conclusion]The established dam material particle gradation identifi-cation system can quickly and accurately obtain the gradation curve of particles,overcoming the problem of low practicality of the sieving method,and realizing the rapid detection of complex dam materials of earth and rock dams.关键词
土石坝料级配检测/数字图像处理/级配修正模型/BP神经网络/水利工程Key words
earth and rock dam material gradation testing/digital image processing/gradation correction model/BP neural net-work/water conservancy engineering分类
建筑与水利引用本文复制引用
罗枭雄,金伟,赵鹏远,钟志鸿,李海波,胡宇翔..基于图像识别的土石坝坝料颗粒级配检测方法[J].水利水电技术（中英文）,2024,55(12):217-227,11.基金项目
国家自然科学基金(42102316) （42102316）
水利部水库大坝安全重点实验室开放研究基金(YK323002) （YK323002）
