Artículos de revistas sobre el tema "Artificial crack"
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Raihan, Prodhan Md Safiq, Anik Md Shahjahan, Shamima Akter Shimky, et al. "Pavement Crack Detection and Solution with Artificial Intelligence." European Journal of Theoretical and Applied Sciences 2, no. 4 (2024): 277–314. http://dx.doi.org/10.59324/ejtas.2024.2(4).25.
Texto completoProdhan, Md Safiq Raihan, Md Shahjahan Anik, Akter Shimky Shamima, et al. "Pavement Crack Detection and Solution with Artificial Intelligence." European Journal of Theoretical and Applied Sciences 2, no. 4 (2024): 277–314. https://doi.org/10.59324/ejtas.2024.2(4).25.
Texto completoDania, Rita, Adebisi Bamgbade, and Abdulmajid Isiaka. "EVALUATION OF BUILDING CRACKS USING ARTIFICIAL INTELLIGENCE BASED CRACK DETECTION SOFTWARE (ABECIS)." Nile Journal of Engineering and Applied Science 2, no. 2 (2025): 1. https://doi.org/10.5455/njeas.197737.
Texto completoKuttimarks, Dr M. S. "Crack Detection of Structures using Artificial Intelligence System." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 1894–901. http://dx.doi.org/10.22214/ijraset.2024.61958.
Texto completoWang, Zi Zhen, Ri He Wang, Yu Huan Bu, and Xun Shan. "A New Method of Preparing Artificial Cores with Certain Cracks for Experiment Study of Elastic Wave Propagation." Advanced Materials Research 356-360 (October 2011): 2954–57. http://dx.doi.org/10.4028/www.scientific.net/amr.356-360.2954.
Texto completoWu, Zhenkai, Xizhe Li, Hanmin Xiao, et al. "The Establishment and Evaluation Method of Artificial Microcracks in Rocks." Energies 14, no. 10 (2021): 2780. http://dx.doi.org/10.3390/en14102780.
Texto completoSakamoto, Junji, Yoshimasa Takahashi, and Hiroshi Noguchi. "Small Fatigue Crack Growth Behavior from Artificial Notch with Focused Ion Beam in Annealed 0.45% Carbon Steel." Key Engineering Materials 488-489 (September 2011): 319–22. http://dx.doi.org/10.4028/www.scientific.net/kem.488-489.319.
Texto completoFathalla, Eissa, Yasushi Tanaka, Koichi Maekawa, and Akito Sakurai. "Quantitative Deterioration Assessment of Road Bridge Decks Based on Site Inspected Cracks." Applied Sciences 8, no. 7 (2018): 1197. http://dx.doi.org/10.3390/app8071197.
Texto completoHendroprasetyo, Wing, and Henry Haidar Jati Andrian. "Analysis of Eddy Current Testing Detection Ability to the Varied Longitudinal Cracks on Coated Weld Metal Tee Joint of 5083 Aluminum Ship Structure." IOP Conference Series: Earth and Environmental Science 972, no. 1 (2022): 012041. http://dx.doi.org/10.1088/1755-1315/972/1/012041.
Texto completoKim, Jung Jin, Ah-Ram Kim, and Seong-Won Lee. "Artificial Neural Network-Based Automated Crack Detection and Analysis for the Inspection of Concrete Structures." Applied Sciences 10, no. 22 (2020): 8105. http://dx.doi.org/10.3390/app10228105.
Texto completoM N, Sumaiya, Prajwal K, Rao Shravan Vasudev, Shreya K A, Thrishul R, and R. Manjunath Prasad. "Comparative Analysis of Concrete Crack Detection using Image Processing and Artificial Intelligence." Journal of Image Processing and Artificial Intelligence 9, no. 1 (2023): 8–15. http://dx.doi.org/10.46610/joipai.2023.v09i01.002.
Texto completoZhang, Yue, Xuemin Zhang, Yun Su, et al. "Tunnel Lining Crack Detection Method Based on Polarization 3D Imaging." Photonics 10, no. 10 (2023): 1085. http://dx.doi.org/10.3390/photonics10101085.
Texto completoSun, Xichen, Jie Chen, Siyi Lu, et al. "Ureolytic MICP-Based Self-Healing Mortar under Artificial Seawater Incubation." Sustainability 13, no. 9 (2021): 4834. http://dx.doi.org/10.3390/su13094834.
Texto completoRifdah Mufiidah Harahap, Darlina Tanjung, M Husni Malik Hasibuan, and Marwan Lubis. "Analisis Deteksi Kedalaman Retak Pada Beton Mengunakan Metode UPV Testing." Konstruksi: Publikasi Ilmu Teknik, Perencanaan Tata Ruang dan Teknik Sipil 2, no. 2 (2024): 112–20. http://dx.doi.org/10.61132/konstruksi.v2i2.236.
Texto completoJiang, Sheng, Mansour Sharafisafa, and Luming Shen. "Using Artificial Neural Networks to Predict Influences of Heterogeneity on Rock Strength at Different Strain Rates." Materials 14, no. 11 (2021): 3042. http://dx.doi.org/10.3390/ma14113042.
Texto completoYang, Gang, Jianchao Wu, and Qing Hu. "Rapid detection of building cracks based on image processing technology with double square artificial marks." Advances in Structural Engineering 22, no. 5 (2018): 1186–93. http://dx.doi.org/10.1177/1369433218810183.
Texto completoShehata, Hesham M., Yasser S. Mohamed, Mohamed Abdellatif, and Taher H. Awad. "Crack Width Estimation Using Feed and Cascade Forward Back Propagation Artificial Neural Networks." Key Engineering Materials 786 (October 2018): 293–301. http://dx.doi.org/10.4028/www.scientific.net/kem.786.293.
Texto completoCui, Zhendong, and Weige Han. "In SituScanning Electron Microscope (SEM) Observations of Damage and Crack Growth of Shale." Microscopy and Microanalysis 24, no. 2 (2018): 107–15. http://dx.doi.org/10.1017/s1431927618000211.
Texto completoHu, Guo X., Bao L. Hu, Zhong Yang, Li Huang, and Ping Li. "Pavement Crack Detection Method Based on Deep Learning Models." Wireless Communications and Mobile Computing 2021 (May 15, 2021): 1–13. http://dx.doi.org/10.1155/2021/5573590.
Texto completoLiu, Yifan, Weiliang Gao, Tingting Zhao, Zhiyong Wang, and Zhihua Wang. "A Rapid Bridge Crack Detection Method Based on Deep Learning." Applied Sciences 13, no. 17 (2023): 9878. http://dx.doi.org/10.3390/app13179878.
Texto completoZheng, Mu Lin, Zhang Wei Ling, Min Wang, Shuai Kong, and Wei Can Guo. "The Experimental Research on Horizontal Underground Tank Magnetic Flux Leakage Testing." Applied Mechanics and Materials 752-753 (April 2015): 1236–39. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1236.
Texto completoZhu, Yantao, and Hongwu Tang. "Automatic Damage Detection and Diagnosis for Hydraulic Structures Using Drones and Artificial Intelligence Techniques." Remote Sensing 15, no. 3 (2023): 615. http://dx.doi.org/10.3390/rs15030615.
Texto completoWu, Dongling, Hongxiang Zhang, and Yiying Yang. "Deep Learning-Based Crack Monitoring for Ultra-High Performance Concrete (UHPC)." Journal of Advanced Transportation 2022 (June 15, 2022): 1–10. http://dx.doi.org/10.1155/2022/4117957.
Texto completoAbdollahzadeh Jamalabadi, Mohammad Yaghoub. "The Use of Artificial Intelligence for Image Processing of Crack Patterns in Panel Painting." Sumerianz Journal of Scientific Research, no. 51 (January 24, 2022): 1–12. http://dx.doi.org/10.47752/sjsr.51.1.12.
Texto completoLiu, Qi, Shancheng Cao, and Zhiwen Lu. "An Improved Crack Breathing Model and Its Application in Crack Identification for Rotors." Machines 11, no. 5 (2023): 569. http://dx.doi.org/10.3390/machines11050569.
Texto completoKim, Jae-Seong, Bo-Young Lee, Woong-Gi Hwang, and Sung-Sik Kang. "The Effect of Welding Residual Stress for Making Artificial Stress Corrosion Crack in the STS 304 Pipe." Advances in Materials Science and Engineering 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/932512.
Texto completoLi, You Tang, and Huai Qing Li. "Analysis of Stress Singularity near the Tip of Artificial Crack." Key Engineering Materials 525-526 (November 2012): 445–48. http://dx.doi.org/10.4028/www.scientific.net/kem.525-526.445.
Texto completoBuffière, Jean Yves, Emilie Ferrié, Wolfgang Ludwig, and Anthony Gravouil. "Characterisation and Modelling of the Three Dimensional Propagation of Short Fatigue Cracks." Materials Science Forum 519-521 (July 2006): 997–1004. http://dx.doi.org/10.4028/www.scientific.net/msf.519-521.997.
Texto completoWu, Yangxu, Wanting Yang, Jinxiao Pan, and Ping Chen. "Asphalt pavement crack detection based on multi-scale full convolutional network." Journal of Intelligent & Fuzzy Systems 40, no. 1 (2021): 1495–508. http://dx.doi.org/10.3233/jifs-191105.
Texto completoAman, Alexandra-Teodora, Cristian Tufisi, Gilbert-Rainer Gillich, and Tiberiu Manescu. "Damage detection in variable temperature conditions using artificial intelligence." Vibroengineering Procedia 51 (October 20, 2023): 186–92. http://dx.doi.org/10.21595/vp.2023.23679.
Texto completoBarrarat, F., B. Helifa, I. K. Lefkaier, S. Bensaid, and K. Rayane. "Defect Reconstruction Using Multilayer Perceptron for Regression and Classification Tasks Based On Eddy Current Signatures." Materials Evaluation 82, no. 10 (2024): 47–56. http://dx.doi.org/10.32548/2024.me-04439.
Texto completoHer, Shiuh Chuan, and Sheng Tung Lin. "Characterization of Surface Crack Using Surface Waves." Applied Mechanics and Materials 166-169 (May 2012): 1931–34. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.1931.
Texto completoTheocaris, P. S. "Peculiarities of the artificial crack." Engineering Fracture Mechanics 38, no. 1 (1991): 37–54. http://dx.doi.org/10.1016/0013-7944(91)90205-f.
Texto completoHu, Jue, Weiping Xu, Bin Gao, et al. "Pattern Deep Region Learning for Crack Detection in Thermography Diagnosis System." Metals 8, no. 8 (2018): 612. http://dx.doi.org/10.3390/met8080612.
Texto completoGao, Xin Wen, ShuaiQing Li, Bang Yang Jin, Min Hu, and Wei Ding. "Intelligent crack damage detection system in shield tunnel using combination of retinanet and optimal adaptive selection." Journal of Intelligent & Fuzzy Systems 40, no. 3 (2021): 4453–69. http://dx.doi.org/10.3233/jifs-201296.
Texto completoKnorr, Alain Franz, and Michael Marx. "Calculating the Resistance of a Grain Boundary against Fatigue Crack Growth." Advanced Materials Research 891-892 (March 2014): 929–35. http://dx.doi.org/10.4028/www.scientific.net/amr.891-892.929.
Texto completoChen, Juntao, Yi Zhang, Kai Ma, Daozeng Tang, Hao Li, and Chengxiang Zhang. "Analysis of Mining Crack Evolution in Deep Floor Rock Mass with Fault." Geofluids 2021 (December 3, 2021): 1–15. http://dx.doi.org/10.1155/2021/5583877.
Texto completoLuo, Mian, Ye Liu, Xu Li, and Junjie Dai. "Crack Self-Healing of Cement Mortar Containing Ureolytic Bacteria Immobilized in Artificial Functional Carrier under Different Exposure Environments." Buildings 12, no. 9 (2022): 1348. http://dx.doi.org/10.3390/buildings12091348.
Texto completoGomera, Mufaro, and Yunus Ballim. "An artificial intelligence approach to detection and assessment of concrete cracks based on visual inspection photographs." MATEC Web of Conferences 364 (2022): 05020. http://dx.doi.org/10.1051/matecconf/202236405020.
Texto completoChen, Zhenmao, Ladislav Janousek, Noritaka Yusa, and Kenzo Miya. "A Nondestructive Strategy for the Distinction of Natural Fatigue and Stress Corrosion Cracks Based on Signals From Eddy Current Testing." Journal of Pressure Vessel Technology 129, no. 4 (2006): 719–28. http://dx.doi.org/10.1115/1.2767365.
Texto completoWu, Zihao, Yunchao Tang, Bo Hong, Bingqiang Liang, and Yuping Liu. "Enhanced Precision in Dam Crack Width Measurement: Leveraging Advanced Lightweight Network Identification for Pixel-Level Accuracy." International Journal of Intelligent Systems 2023 (September 2, 2023): 1–16. http://dx.doi.org/10.1155/2023/9940881.
Texto completoJu, Xiaochen, Xinxin Zhao, and Shengsheng Qian. "TransMF: Transformer-Based Multi-Scale Fusion Model for Crack Detection." Mathematics 10, no. 13 (2022): 2354. http://dx.doi.org/10.3390/math10132354.
Texto completoBehera, Sanjay Kumar, Dayal R. Parhi, and Harish C. Das. "Approach to establish a hybrid intelligent model for crack diagnosis in a fix-hinge beam structure." International Journal of Structural Integrity 10, no. 2 (2019): 208–29. http://dx.doi.org/10.1108/ijsi-05-2018-0029.
Texto completoWang, Li, and Zhenmao Chen. "Sizing of natural crack using multi-output support vector regression method from multi-frequency eddy current testing signals." International Journal of Applied Electromagnetics and Mechanics 64, no. 1-4 (2020): 721–28. http://dx.doi.org/10.3233/jae-209383.
Texto completoAbhijeet H. Kekan et al.,, Abhijeet H. Kekan et al ,. "Crack Depth and Crack Location Identification using Artificial Neural Network." International Journal of Mechanical and Production Engineering Research and Development 9, no. 2 (2019): 699–708. http://dx.doi.org/10.24247/ijmperdapr201970.
Texto completoDoğanay Katı, Hilal, Jamilu Buhari, Arturo Francese, Feiyang He, and Muhammad Khan. "Numerical Analysis of Crack Path Effects on the Vibration Behaviour of Aluminium Alloy Beams and Its Identification via Artificial Neural Networks." Sensors 25, no. 3 (2025): 838. https://doi.org/10.3390/s25030838.
Texto completoLee, Sang Eon, and Jung-Wuk Hong. "Effect of Crack Closure on Magnitude of Modulated Wave." International Journal of Structural Stability and Dynamics 20, no. 13 (2020): 2041018. http://dx.doi.org/10.1142/s0219455420410187.
Texto completoBai, Xiaotian, Zhaonan Zhang, Huaitao Shi, Zhong Luo, and Tao Li. "Identification of Subsurface Mesoscale Crack in Full Ceramic Ball Bearings Based on Strain Energy Theory." Applied Sciences 13, no. 13 (2023): 7783. http://dx.doi.org/10.3390/app13137783.
Texto completoBian, Ziyan. "Identification of Concrete Crack Using Deep Learning Based Approach." Advances in Research 25, no. 5 (2024): 272–80. http://dx.doi.org/10.9734/air/2024/v25i51160.
Texto completoSong, Dowon, Taeseup Song, Ungyu Paik, et al. "Crack-Resistance Behavior of an Encapsulated, Healing Agent Embedded Buffer Layer on Self-Healing Thermal Barrier Coatings." Coatings 9, no. 6 (2019): 358. http://dx.doi.org/10.3390/coatings9060358.
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