摘要
针对由特殊截面形状的金属棒所组成的理想二维粒状材料,基于数字图像技术,提出了一种细观组构特征分析方法,并编制了程序IPFA,实现了颗粒识别、接触搜索与组构分析等功能。该方法首先对粒状材料试样的原始数字图像进行增强,以消除噪声干扰。在此基础上采用模板匹配技术进行颗粒识别,并将识别结果用于颗粒间的接触搜索,最后给出试样内颗粒长轴方向与接触法线方向等组构特征的统计分析结果。该方法特别适用于由规则颗粒组成的二维粒状材料,识别精度与效率均较高,可作为粒状材料的细观组构特征及其演化规律分析的有效工具。
Based on the digital image processing technique, a method was presented for microfabric analysis for ideal granular materials composed of metal bars with specified sections. A code named IPFA was then developed to implement the functions such as particle detection, contact searching and microfabric analysis. By use of this method, the digital images of dense samples were firstly enhanced to clear the noises. The particles were then detected from the enhanced images using template matching algorithm presented here, and contact normals between particles were searched based on the particle detection results. Finally, the statistical analysis could be processed on two important elements of microscopic fabric, including directions of the long axis Of particles and the contact normals between particles. The proposed method was especially suitable for ideal two-dimensional granular materials, and could be used as a powerful tool for the analysis of microfabric of granular materials and its evaluation because of its high precision and efficiency of particle detection.
出处
《岩土工程学报》
EI
CAS
CSCD
北大核心
2008年第10期1555-1559,共5页
Chinese Journal of Geotechnical Engineering
基金
国家自然科学基金项目(50478016)
北京市自然科学基金重点项目(8061003)
关键词
粒状材料
细观组构
数字图像
颗粒识别
granular material
microfabric
digital image
particle detection
