Abstract
Weak muddy intercalations (WMI) are a type of geo-material with highly unstable mechanical properties, and thus they pose a great threat to the stability of rock slopes and in other rock engineering situations. In this paper, microstructure similarity-based clustering together with image fusion and reconstruction are used to study the microstructures of shallow weathered WMI. The study aims to obtain a reconstructed image of microstructure features that can represent a region to provide the basis for subsequent studies on WMI mechanical properties. The similarity of each microscopic WMI image is calculated using a similarity calculation model based on the microstructure parameters, and images are clustered based on their similarities. Then, image fusion technology is used to combine images in the same cluster. The results are as follows: (1) Similarity corresponding to a cumulative distribution probability of 80% is used as the clustering threshold; (2) The fused WMI microstructure image can represent the microstructure of a layer in the sample. In view of these findings, WMI microstructure clustering and feature reconstruction can provide evidence for studies on WMI lamina structures and failures involving these, which formed the basis for the assessment of the stability of slopes and other situations in which WMI are present.
Similar content being viewed by others
References
Biswas A, Rai A, Ahmad T, Sahoo PM (2017) Spatial estimation and rescaled spatial bootstrap approach for finite population. Commun Stat Theory Methods 46(1):373–388
Chen J, Dai F, Xu L, Chen S, Wang P, Long W, Shen N (2014) Properties and micro-structure of a natural slip zone in loose deposits of red beds, southwestern China. Eng Geol 183:53–64
Cotecchia F, Cafaro F, Guglielmi S (2016) Microstructural changes in clays generated by compression explored by means of SEM and image processing. Procedia Engineer 158:57–62
Deza MM, Deza E (2009) Encyclopedia of distances. Springer, Berlin, p 1–583
Dhanachandra N, Manglem K, Chanu YJ (2015) Image segmentation using K-means clustering algorithm and subtractive clustering algorithm. Procedia Comput Sci 54:764–771
Dudoignon P, Gélard D, Sammartino S (2004) Cam-clay and hydraulic conductivity diagram relations in consolidated and sheared clay-matrices. Clay Miner 39(3):267–279
Gerke KM, Karsanina MV, Mallants D (2015) Universal stochastic multiscale image fusion: an example application for shale rock. Sci Rep 5:15880
Gutierrez NHM, de Nobrega MT, Vilar OM (2009) Influence of the micro-structure in the collapse of a residual clayey tropical soil. Bull Eng Geol Environ 68(1):107–116
Gylland AS, Rueslåtten H, Jostad HP, Nordal S (2013) Microstructural observations of shear zones in sensitive clay. Eng Geol 163:75–88
Houben M, Desbois G, Urai J (2014) A comparative study of representative 2D micro-structures in shaly and sandy facies of Opalinus clay (Mont Terri, Switzerland) inferred form BIB-SEM and MIP methods. Mar Pet Geol 49:143–161
Jiang M, Zhang F, Hu H, Cui Y, Peng J (2014) Structural characterization of natural loess and remolded loess under triaxial tests. Eng Geol 181:249–260
Jiang C, Zhou X, Tao G, Chen D (2016) Experimental study on the performance and micro-structure of cementitious materials made with dune sand. Adv Mater Sci Eng. https://doi.org/10.1155/2016/2158706
Kawamura K, Ogawa Y, Oyagi N, Kitahara T, Anma R (2007) Structural and fabric analyses of basal slip zone of the Jin’nosuke-dani landslide, northern Central Japan: its application to the slip mechanism of décollement. Landslides 4(4):371–380
Keller LM, Schuetz P, Erni R, Rossell MD, Lucas F, Gasser P, Holzer L (2013) Characterization of multi-scale microstructural features in Opalinus clay. Microporous Mesoporous Mater 170:83–94
Kim SK, Kang ST, Kim JK, Jang IY (2017) Effects of particle size and cement replacement of LCD glass powder in concrete. Adv Mater Sci Eng. https://doi.org/10.1155/2017/3928047
Li H, Liu X, Yu Z, Zhang Y (2016) Performance improvement scheme of multifocus image fusion derived by difference images. Signal Process 128:474–493
Lin S-z, Wang D-j, Wang X-x, Zhu X-h (2016) Multi-band texture image fusion based on the embedded multi-scale decomposition andpossibility theory. Spectrosc Spectr Anal 36(7):2337–2343
Liu C, Shi B, Zhou J, Tang C (2011) Quantification and characterization of microporosity by image processing, geometric measurement and statistical methods: application on SEM images of clay materials. Appl Clay Sci 54(1):97–106
Mishnaevsky LL, Schmauder S (2001) Continuum mesomechanical finite element modeling in materials development: a state-of-the-art review. Appl Mech Rev 54(1):49–67
Ng AY, Jordan MI, Weiss Y (2002) On spectral clustering: analysis and an algorithm. In: Jordan MI, LeCun Y, Solla SA (eds) Advances in neural information processing systems. MIT Press, Cambridge, pp 849–856
Pandey S, Khanna P (2016) Content-based image retrieval embedded with agglomerative clustering built on information loss. Comput Electr Eng 54:506–521
Pusch R, Weston R (2003) Microstructural stability controls the hydraulic conductivity of smectitic buffer clay. Appl Clay Sci 23(1):35–41
Sivakumar V, Doran I, Graham J (2002) Particle orientation and its influence on the mechanical behaviour of isotropically consolidated reconstituted clay. Eng Geol 66(3):197–209
Tang Y-q, Zhou J, Hong J, Yang P, Wang J-x (2012) Quantitative analysis of the micro-structure of shanghai muddy clay before and after freezing. Bull Eng Geol Environ 71(2):309–316
Van Mier JGM, Van Vliet MRA (2003) Influence of microstructure of concrete on size/scale effects in tensile fracture. Eng Fract Mech 70(16):2281–2306
Wang C-l, Wang H-W, Hu B-l, Wen J, Xu J, Li X-J (2016) A novel spatial-spectral sparse representation for hyperspectral image classification based on neighborhood segmentation. Spectrosc Spectr Anal 36(9):2919–2924
Xu B, Yan C, Xu S (2013) Analysis of the bedding landslide due to the presence of the weak intercalated layer in the limestone. Environ Earth Sci 70:2817–2825
Zheng L-N (2012) Reaserch of failure mechanism and the local failure zones for consequent slope based on strain softening theory. Southwest Jiao Tong University, Chengdu
Zheng Y, Liu J, Hu Q, Cai Q (2014) Study on micro-structure of muddy intercalation using SEM method. Electron J Geotech Eng 19:9953–9963
Acknowledgments
The work was supported by the National Natural Science Foundation of China (Nos. 51574201) and the State Key Laboratory of Geo-hazard Prevention and Geo-environment Protection (Chengdu University of Technology) (SKLGP2015K006). Additional support was provided by the Scientific and Technical Youth Innovation Group (Southwest Petroleum University) (2015CXTD05).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that there is no conflict of interest regarding the publication of this paper.
Rights and permissions
About this article
Cite this article
Hu, Q., He, T., Ye, T. et al. A method for microstructure similarity clustering and feature reconstruction for weathered weak muddy intercalations. Bull Eng Geol Environ 78, 3531–3539 (2019). https://doi.org/10.1007/s10064-018-1353-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10064-018-1353-z