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Comparative analysis of twelve transfer learning models for the prediction and crack detection in concrete dams,based on borehole images

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Frontiers of Structural and Civil Engineering 2024年第10期18卷 1507-1523页

作者： Umer Sadiq KHAN muhammad ishfaque Saif Ur Rehman KHAN Fang Xu Lerui CHEN Yi LEI School of Computer and Information Science Hubei Engineering UniversityXiaogan 432000China Institute for AI Industrial Technology Research Hubei Engineering UniversityXiaogan 432000China College of Water Conservancy and Hydropower Engineering Hohai UniversityNanjing 210098China School of Computer Science and Engineering Central South UniversityChangsha 410083China College of Aviation Zhongyuan University of TechnologyZhengzhou 451191China School of Civil Engineering Central South UniversityChangsha 410083China

Disaster-resilient dams require accurate crack detection,but machine learning methods cannot capture dam structural reaction temporal patterns and *** research uses deep learning,convolutional neural networks,and transfer learning to improve dam crack *** deep-learning models are trained on 192 crack *** research aims to provide up-to-date detecting techniques to solve dam crack *** finding shows that the EfficientNetB0 model performed better than others in classifying borehole concrete crack surface tiles and normal(undamaged)surface tiles with 91%*** study’s pre-trained designs help to identify and to determine the specific locations of cracks.

关键词： concrete dam borehole closed-circuit television deep learning models crack detection water resources management management

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Deep metallogenic mechanism in southeastern China based on receiver function data

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Transactions of Nonferrous Metals Society of China 2022年第1期32卷 273-284页

作者： Jian-xin LIU Syed muzyan SHAHZAD Ya SUN Asim SHAHZAD Chuan LI Meryem FANIDI ishfaque muhammad School of Geosciences and Info-physic Central South UniversityChangsha 410083China Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of EducationCentral South UniversityChangsha 410083China Hunan Provincial Key Laboratory of Nonferrous Resources and Geological Hazard Detection Central South UniversityChangsha 410083China College of Earth Sciences Guilin University of TechnologyGuilin 541006China

Crustal deformation and deep metallogenic mechanisms in southeastern(SE)China are still *** this study,we applied the receiver function method to measure crustal thickness and Poisson’s ratio for crustal rock using teleseismic data recorded at 207 seismic stations from China Earthquake Administration *** results showed that crustal thickness varied from~27 km in the eastern part to~43 km in the western part of the study area,with an average crustal thickness of 31 *** crust is thick in the west and thin in the *** observed Poisson’s ratio for crustal rock was relatively high in the southern Cathaysia Block(CB),with an average of 0.295,while in the Qinling—Dabie terrane,it was relatively low,with an average of *** the middle of the Yangtze craton and central east of the CB,Poisson’s ratio for crustal rock varied from 0.257 to *** comparing Poisson’s ratio of the intrusive deposits with that of igneous rocks in volcanic complexes,we deduced that the metallic mineral system might be associated with orogenic and hydrothermal *** results indicated that multistage magma and mineralization in the study area might be attributed to the tectonic-magma-thermal *** high Poisson’s ratio for crustal rock in the southeastern margin of the CB and northeastern Upper Yangtze Craton might be related to Mesozoic lower crustal mafic partial melt,which provides an important environment for various magmatic intrusions and metallogenies.

关键词： deep metallogenic mechanism Poisson’s ratio southeastern China crustal thickness

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