基于图像处理的Q3黄土的微观结构变化研究

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (0 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Loess geological disaster is closely related to its microstructural characteristics. For the issues now existing in quantitative analysis of scanning electron microscope(SEM) image，the microstructural characteristics of intact and cyclic loaded Q3 losses are studied. Firstly，noise reduction and segmentation method in the scanning electron microscope(SEM) image processing are discussed. A SEM image analysis method is presented by applying Lee image enhancement algorithm to image noise reduction and applying the fuzzy C-means clustering method to gray-scale image segmentation. With the presented SEM image analysis method，the pore area，pore size，roundness，shape ratio and other parameters of Q3 losses before and after cyclic loading are calculated. The results indicate as follows：(1) Large pores number of loess decreases，loess particles gradually arrange densely，and their contact relationship changes from point contact to surface contact under dynamic stress by analyzing the appearance features of SEM images. (2) The deformation produced by cyclic loading is mainly due to damage of large pores by analyzing pore area and its number changes. (3) Loess pores get a directional feature and the features change after damage of soil structure due to cyclic loading by analyzing loess pore directional distribution characteristics. (4) Based on the study of pore shape distribution characteristics，the soil particles may rotate and narrow pore of loess changes greatly，which resultantly result in the damage of pore connectivity. The study can provide basis for soil macroscopic deformation mechanism.

Key words： soil mechanics loess microstructure scanning electron microscope(SEM) image analysis pore change

Received: 25 February 2010

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors

Cite this article:

URL:

https://rockmech.whrsm.ac.cn/EN/Y2011/V30/IS1/3185

[1] 赵景波，陈云. 黄土的孔隙与湿陷性研究[J]. 工程地质学报，1994，2(2)：76–83.(ZHAO Jingbo，CHEN Yun. Study on pores and collapsibility of loess[J]. Journal of Engineering Geology，1994，2(2)：76–83.(in Chinese)) [2] 王兰民，刘红玫，李兰，等. 饱和黄土液化机制与特性的试验研究[J]. 岩土工程学报，2000，22(1)：92–97.(WANG Lanmin，LIU Hongmei，LI Lan，et al. Experimental study on the mechanism and behaviors of saturated loess liquefaction[J]. Chinese Journal of Geotechnical Engineering，2000，22(1)：92–97.(in Chinese)) [3] 任权，王家鼎，袁中夏，等. 高速铁路地基黄土微结构的分形研究[J]. 水文地质工程地质，2007，34(6)：76–78.(REN Quan，WANG Jiading，YUAN Zhongxia，et al. Fractal study on loess microstructure of one high-speed railway foundation[J]. Hydrogeology and Engineering Geology，2007，34(6)：76–78.(in Chinese)) [4] 王家鼎，白铭学，肖树芳. 强震作用下低角度黄土斜坡滑移的复合机制研究[J]. 岩土工程学报，2001，23(4)：445–449.(WANG Jiading，BAI Mingxue，XIAO Shufang. A study on compound mechanism of earthquake-related sliding displacements on gently inclined loess slope[J]. Chinese Journal of Geotechnical Engineering，2001，23(4)：445–449.(in Chinese)) [5] 王家鼎，袁中夏，任权. 高速铁路地基黄土液化前后微观结构变化研究[J]. 西北大学学报：自然科学版，2009，39(3)：480–483.(WANG Jiading，YUAN Zhongxia，REN Quan. A study on loess microstructure pre-liquefaction and post-liquefaction of high-speed railway foundation[J]. Journal of Northwest University：Natural Science，2009，39(3)：480–483.(in Chinese)) [6] LIU Z，SHI B，YANG H I，et al. Magnification effects on the interpretation of SEM images of expansive soils[J]. Engineering Geology，2005，78(1/2)：89–94. [7] DATHE A，EINS S，NIEMEYER J，et al. The surface fractal dimension of the soil-pore interface as measured by image analysis[J]. Geoderma，2001，103(1/2)：203–229. [8] CALERO J，DELGADO R，DELGADO G，et al. SEM image analysis in the study of a soil chronosequence on fluvial terraces of the middle Guadalquivir(southern Spain)[J]. European Journal of Soil Science，2009，60(3)：465–480. [9] 孔令荣，黄宏伟，HICHER P Y，等. 上海淤泥质黏土微结构特性及固结过程中的结构变化研究[J]. 岩土力学，2008，29(12)：3 287–3 292. (KONG Lingrong，HUANG Hongwei，HICHER P Y，et al. The microstructure property on Shanghai mucky clay and its structural evolution during one-dimensional consolidation test[J]. Rock and Soil Mechanics，2008，29(12)：3 287–3 292.(in Chinese)) [10] 王兰民，邓津，黄媛. 黄土震陷性的微观结构量化分析[J]. 岩石力学与工程学报，2007，26(增1)：3 025–3 031.(WANG Lanmin，DENG Jin，HUANG Yuan. Quantitative analysis of microstructure of loess seismic subsidence[J]. Chinese Journal of Rock Mechanics and Engineering，2007，26(Supp.1)：3 025–3 031.(in Chinese)) [11] 耿妍，张端金. 自适应滤波算法综述[J]. 信息与电子工程，2008，6(4)：315–320.(GENG Yan，Zhang Duanjin. Survey of adaptive filtering algorithms[J]. Information and Electronic Engineering，2008，6(4)：315–320.(in Chinese)) [12] 屈稳太，诸静. 图像小波变换中的两个关键技术——滤波器的正则性与信号的边界处理[J]. 浙江大学学报：工学版，2003，37(2)：59–63.(QU Wentai，CHU Jing. Two key technologies for image wavelet transform—the regularity of filters and the process of signal boundary[J]. Journal of Zhejiang University：Engineering Science，2003，37(2)：59–63.(in Chinese)) [13] 孙宏琦，施维颖，巨永锋. 利用中值滤波进行图像处理[J]. 长安大学学报：自然科学版，2003，23(2)：104–106.(SUN Hongqi，SHI Weiying，JU Yongfeng. Image processing with medium value filter[J]. Journal of Chang?an University：Natural Science，2003，23(2)：104–106.(in Chinese)) [14] 宋宇，李满天，孙立宁. 基于相似度函数的图像椒盐噪声自适应滤除算法[J]. 自动化学报，2007，33(5)：474–479.(SONG Yu，LI Mantian，SUN Lining. Image salt and pepper noise self-adaptive suppression algorithm based on similarity function[J]. Acta Automatica Sinica，2007，33(5)：474–479.(in Chinese)) [15] LEE J S. Digital image enhancement and noise filtering by use of local statistics[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence，1980，2(2)：165–168. [16] 唐朝生，施斌，王宝军. 基于SEM土体微观结构研究中的影响因素分析[J]. 岩土工程学报，2008，30(4)：560–565.(TANG Chaosheng， SHI Bin， WANG Baojun. Influencing factor analysis of soil microstructure using SEM[J]. Chinese Journal of Geotechnical Engineering，2008，30(4)：560–565.(in Chinese)) [17] OTSU N. A threshold selection method from gray-level histograms[J]. IEEE Transactions on System，Man and Cybernetics，1979，9(1)：62–66. [18] PHAM D L，PRINCE J L. An adaptive fuzzy c-means algorithm for image segmentation in the presence of intensity inhomogeneities[J]. Pattern Recognition Letters，1999，20(1)：57–68. [19] GRAU V，MEWES A U，ALCANIZ M，et al. Improved watershed transform for medical image segmentation using prior information[J]. IEEE Transactions on Medical Imaging，2004，23(4)：447–458. [20] 雷祥义. 中国黄土的孔隙类型与湿陷性[J]. 中国科学：B辑，1987，17(12)：1 309–1 318.(LEI Xiangyi. The types of loess pores in China and their relationship with collapsibility[J]. Science in China：Series B，17(12)：1 309–1 318.(in Chinese)) [21] 郭飞，徐绍辉，刘建立. 土壤图像孔隙轮廓线分形特征及其应用[J]. 农业工程学报，2005，21(7)：6–10.(GUO Fei，XU Shaohui，LIU Jianli. Characteristics of pore profile fractal dimension of soil images and its application[J]. Transactions of the Chinese Society of Agricultural Engineering，2005，21(7)：6–10.(in Chinese)) [22] BÉRUBÉ D，JÉBRAK M. High precision boundary fractal analysis for shape characterization[J]. Computers and Geosciences，1999，25(9)：1 059–1 071. [23] HOLGADO M A，FERNÁNDEZ-HERVÁS M J，FERNÁNDEZ- ARÉVALO M，et al. Use of fractal dimensions in the study of excipients：application to the characterization of modified lactoses[J]. International Journal of Pharmaceutics，1995，121(2)：187–193. [24] ALLEN M，BROWN G J，MILES N J. Measurement of boundary fractal dimensions：review of current techniques[J]. Powder Technology，1995，84(1)：1–14.