首页|A deformation measurement method based on surface texture information of rocks and its application

A deformation measurement method based on surface texture information of rocks and its application

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Users of the digital image correlation method are faced with the problem of poor operability,low repeata-bility,and lack of standardized specifications for spraying speckles.To solve the problem,the research proposed a rock deformation measurement method that obviates the need to spray speckles.A local bin-ary model was established by using the local binary pattern(LBP)operator based on deep texture features on rock surfaces.The resulting LBP digital speckle pattern can substitute artificial speckle patterns and demonstrates high quality and strong applicability.Based on the LBP digital speckle pattern,the target tracking algorithm was employed to achieve non-contact measurement of the dynamic displacements of rocks.The feasibility and effectiveness of the algorithm in practical application were verified by con-ducting shear tests on granite and siltstone.Test results show that the deformation characteristics in the displacement nephograms are in line with the measured data pertaining to rock fracturing and conform to the basic characteristics of the shear failure of rocks.The deformation measurement method based on surface texture information can realize non-contact displacement measurement of rocks under condi-tions without speckles:this obviates the influence of the quality of sprayed speckles on the accuracy of the measurement of deformation.

Deformation measurementTexture informationDigital speckleLocal binary modelTarget tracking algorithm

Yanbo Zhang、Xin Han、Peng Liang、Xulong Yao、Qun Li、Guangyuan Yu、Qi Wang

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College of Mining Engineering,North China University of Science and Technology,Tangshan 063210,China

Green Intelligent Mining Technology Innovation Center of Hebei Province,Tangshan 063210,China

Key Laboratory for Geo-mechanics and Deep Underground Engineering,China University of Mining and Technology-Beijing,Beijing 100083,China

国家自然科学基金河北省自然科学基金河北省自然科学基金河北省自然科学基金

52074123E2022209143E2021209148E2021209052

2023

矿业科学技术学报(英文版)
中国矿业大学

矿业科学技术学报(英文版)

CSTPCDCSCDEI
影响因子:1.222
ISSN:2095-2686
年,卷(期):2023.33(9)
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