Artykuły w czasopismach na temat „Artificial crack”
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Raihan, Prodhan Md Safiq, Anik Md Shahjahan, Shamima Akter Shimky, Toki Thamid Zim, Summa Parven, Abdul Ali Khan i Mir Fazle Rabbi. "Pavement Crack Detection and Solution with Artificial Intelligence". European Journal of Theoretical and Applied Sciences 2, nr 4 (1.07.2024): 277–314. http://dx.doi.org/10.59324/ejtas.2024.2(4).25.
Pełny tekst źródłaKuttimarks, Dr M. S. "Crack Detection of Structures using Artificial Intelligence System". International Journal for Research in Applied Science and Engineering Technology 12, nr 5 (31.05.2024): 1894–901. http://dx.doi.org/10.22214/ijraset.2024.61958.
Pełny tekst źródłaWang, Zi Zhen, Ri He Wang, Yu Huan Bu i Xun Shan. "A New Method of Preparing Artificial Cores with Certain Cracks for Experiment Study of Elastic Wave Propagation". Advanced Materials Research 356-360 (październik 2011): 2954–57. http://dx.doi.org/10.4028/www.scientific.net/amr.356-360.2954.
Pełny tekst źródłaWu, Zhenkai, Xizhe Li, Hanmin Xiao, Xuewei Liu, Wei Lin, Yuan Rao, Yang Li i Jie Zhang. "The Establishment and Evaluation Method of Artificial Microcracks in Rocks". Energies 14, nr 10 (12.05.2021): 2780. http://dx.doi.org/10.3390/en14102780.
Pełny tekst źródłaSakamoto, Junji, Yoshimasa Takahashi i 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 (wrzesień 2011): 319–22. http://dx.doi.org/10.4028/www.scientific.net/kem.488-489.319.
Pełny tekst źródłaFathalla, Eissa, Yasushi Tanaka, Koichi Maekawa i Akito Sakurai. "Quantitative Deterioration Assessment of Road Bridge Decks Based on Site Inspected Cracks". Applied Sciences 8, nr 7 (21.07.2018): 1197. http://dx.doi.org/10.3390/app8071197.
Pełny tekst źródłaHendroprasetyo, Wing, i 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, nr 1 (1.01.2022): 012041. http://dx.doi.org/10.1088/1755-1315/972/1/012041.
Pełny tekst źródłaKim, Jung Jin, Ah-Ram Kim i Seong-Won Lee. "Artificial Neural Network-Based Automated Crack Detection and Analysis for the Inspection of Concrete Structures". Applied Sciences 10, nr 22 (16.11.2020): 8105. http://dx.doi.org/10.3390/app10228105.
Pełny tekst źródłaM N, Sumaiya, Prajwal K, Rao Shravan Vasudev, Shreya K A, Thrishul R i R. Manjunath Prasad. "Comparative Analysis of Concrete Crack Detection using Image Processing and Artificial Intelligence". Journal of Image Processing and Artificial Intelligence 9, nr 1 (11.01.2023): 8–15. http://dx.doi.org/10.46610/joipai.2023.v09i01.002.
Pełny tekst źródłaSun, Xichen, Jie Chen, Siyi Lu, Miaomiao Liu, Siyu Chen, Yifei Nan, Yang Wang i Jun Feng. "Ureolytic MICP-Based Self-Healing Mortar under Artificial Seawater Incubation". Sustainability 13, nr 9 (25.04.2021): 4834. http://dx.doi.org/10.3390/su13094834.
Pełny tekst źródłaZhang, Yue, Xuemin Zhang, Yun Su, Xuan Li, Shiwei Ma, Su Zhang, Weihe Ren i Kang Li. "Tunnel Lining Crack Detection Method Based on Polarization 3D Imaging". Photonics 10, nr 10 (27.09.2023): 1085. http://dx.doi.org/10.3390/photonics10101085.
Pełny tekst źródłaRifdah Mufiidah Harahap, Darlina Tanjung, M Husni Malik Hasibuan i Marwan Lubis. "Analisis Deteksi Kedalaman Retak Pada Beton Mengunakan Metode UPV Testing". Konstruksi: Publikasi Ilmu Teknik, Perencanaan Tata Ruang dan Teknik Sipil 2, nr 2 (22.03.2024): 112–20. http://dx.doi.org/10.61132/konstruksi.v2i2.236.
Pełny tekst źródłaJiang, Sheng, Mansour Sharafisafa i Luming Shen. "Using Artificial Neural Networks to Predict Influences of Heterogeneity on Rock Strength at Different Strain Rates". Materials 14, nr 11 (3.06.2021): 3042. http://dx.doi.org/10.3390/ma14113042.
Pełny tekst źródłaYang, Gang, Jianchao Wu i Qing Hu. "Rapid detection of building cracks based on image processing technology with double square artificial marks". Advances in Structural Engineering 22, nr 5 (1.11.2018): 1186–93. http://dx.doi.org/10.1177/1369433218810183.
Pełny tekst źródłaShehata, Hesham M., Yasser S. Mohamed, Mohamed Abdellatif i Taher H. Awad. "Crack Width Estimation Using Feed and Cascade Forward Back Propagation Artificial Neural Networks". Key Engineering Materials 786 (październik 2018): 293–301. http://dx.doi.org/10.4028/www.scientific.net/kem.786.293.
Pełny tekst źródłaHu, Guo X., Bao L. Hu, Zhong Yang, Li Huang i Ping Li. "Pavement Crack Detection Method Based on Deep Learning Models". Wireless Communications and Mobile Computing 2021 (15.05.2021): 1–13. http://dx.doi.org/10.1155/2021/5573590.
Pełny tekst źródłaCui, Zhendong, i Weige Han. "In SituScanning Electron Microscope (SEM) Observations of Damage and Crack Growth of Shale". Microscopy and Microanalysis 24, nr 2 (kwiecień 2018): 107–15. http://dx.doi.org/10.1017/s1431927618000211.
Pełny tekst źródłaLiu, Yifan, Weiliang Gao, Tingting Zhao, Zhiyong Wang i Zhihua Wang. "A Rapid Bridge Crack Detection Method Based on Deep Learning". Applied Sciences 13, nr 17 (31.08.2023): 9878. http://dx.doi.org/10.3390/app13179878.
Pełny tekst źródłaZheng, Mu Lin, Zhang Wei Ling, Min Wang, Shuai Kong i Wei Can Guo. "The Experimental Research on Horizontal Underground Tank Magnetic Flux Leakage Testing". Applied Mechanics and Materials 752-753 (kwiecień 2015): 1236–39. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1236.
Pełny tekst źródłaZhu, Yantao, i Hongwu Tang. "Automatic Damage Detection and Diagnosis for Hydraulic Structures Using Drones and Artificial Intelligence Techniques". Remote Sensing 15, nr 3 (20.01.2023): 615. http://dx.doi.org/10.3390/rs15030615.
Pełny tekst źródłaAbdollahzadeh Jamalabadi, Mohammad Yaghoub. "The Use of Artificial Intelligence for Image Processing of Crack Patterns in Panel Painting". Sumerianz Journal of Scientific Research, nr 51 (24.01.2022): 1–12. http://dx.doi.org/10.47752/sjsr.51.1.12.
Pełny tekst źródłaWu, Dongling, Hongxiang Zhang i Yiying Yang. "Deep Learning-Based Crack Monitoring for Ultra-High Performance Concrete (UHPC)". Journal of Advanced Transportation 2022 (15.06.2022): 1–10. http://dx.doi.org/10.1155/2022/4117957.
Pełny tekst źródłaLiu, Qi, Shancheng Cao i Zhiwen Lu. "An Improved Crack Breathing Model and Its Application in Crack Identification for Rotors". Machines 11, nr 5 (20.05.2023): 569. http://dx.doi.org/10.3390/machines11050569.
Pełny tekst źródłaKim, Jae-Seong, Bo-Young Lee, Woong-Gi Hwang i 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.
Pełny tekst źródłaAman, Alexandra-Teodora, Cristian Tufisi, Gilbert-Rainer Gillich i Tiberiu Manescu. "Damage detection in variable temperature conditions using artificial intelligence". Vibroengineering Procedia 51 (20.10.2023): 186–92. http://dx.doi.org/10.21595/vp.2023.23679.
Pełny tekst źródłaBuffière, Jean Yves, Emilie Ferrié, Wolfgang Ludwig i Anthony Gravouil. "Characterisation and Modelling of the Three Dimensional Propagation of Short Fatigue Cracks". Materials Science Forum 519-521 (lipiec 2006): 997–1004. http://dx.doi.org/10.4028/www.scientific.net/msf.519-521.997.
Pełny tekst źródłaLi, You Tang, i Huai Qing Li. "Analysis of Stress Singularity near the Tip of Artificial Crack". Key Engineering Materials 525-526 (listopad 2012): 445–48. http://dx.doi.org/10.4028/www.scientific.net/kem.525-526.445.
Pełny tekst źródłaTheocaris, P. S. "Peculiarities of the artificial crack". Engineering Fracture Mechanics 38, nr 1 (styczeń 1991): 37–54. http://dx.doi.org/10.1016/0013-7944(91)90205-f.
Pełny tekst źródłaWu, Yangxu, Wanting Yang, Jinxiao Pan i Ping Chen. "Asphalt pavement crack detection based on multi-scale full convolutional network". Journal of Intelligent & Fuzzy Systems 40, nr 1 (4.01.2021): 1495–508. http://dx.doi.org/10.3233/jifs-191105.
Pełny tekst źródłaBarrarat, F., B. Helifa, I. K. Lefkaier, S. Bensaid i K. Rayane. "Defect Reconstruction Using Multilayer Perceptron for Regression and Classification Tasks Based On Eddy Current Signatures". Materials Evaluation 82, nr 10 (1.10.2024): 47–56. http://dx.doi.org/10.32548/2024.me-04439.
Pełny tekst źródłaHer, Shiuh Chuan, i Sheng Tung Lin. "Characterization of Surface Crack Using Surface Waves". Applied Mechanics and Materials 166-169 (maj 2012): 1931–34. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.1931.
Pełny tekst źródłaHu, Jue, Weiping Xu, Bin Gao, Gui Tian, Yizhe Wang, Yingchun Wu, Ying Yin i Juan Chen. "Pattern Deep Region Learning for Crack Detection in Thermography Diagnosis System". Metals 8, nr 8 (6.08.2018): 612. http://dx.doi.org/10.3390/met8080612.
Pełny tekst źródłaKnorr, Alain Franz, i Michael Marx. "Calculating the Resistance of a Grain Boundary against Fatigue Crack Growth". Advanced Materials Research 891-892 (marzec 2014): 929–35. http://dx.doi.org/10.4028/www.scientific.net/amr.891-892.929.
Pełny tekst źródłaGao, Xin Wen, ShuaiQing Li, Bang Yang Jin, Min Hu i Wei Ding. "Intelligent crack damage detection system in shield tunnel using combination of retinanet and optimal adaptive selection". Journal of Intelligent & Fuzzy Systems 40, nr 3 (2.03.2021): 4453–69. http://dx.doi.org/10.3233/jifs-201296.
Pełny tekst źródłaAbhijeet 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, nr 2 (2019): 699–708. http://dx.doi.org/10.24247/ijmperdapr201970.
Pełny tekst źródłaGomera, Mufaro, i 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.
Pełny tekst źródłaLuo, Mian, Ye Liu, Xu Li i Junjie Dai. "Crack Self-Healing of Cement Mortar Containing Ureolytic Bacteria Immobilized in Artificial Functional Carrier under Different Exposure Environments". Buildings 12, nr 9 (1.09.2022): 1348. http://dx.doi.org/10.3390/buildings12091348.
Pełny tekst źródłaChen, Juntao, Yi Zhang, Kai Ma, Daozeng Tang, Hao Li i Chengxiang Zhang. "Analysis of Mining Crack Evolution in Deep Floor Rock Mass with Fault". Geofluids 2021 (3.12.2021): 1–15. http://dx.doi.org/10.1155/2021/5583877.
Pełny tekst źródłaChen, Zhenmao, Ladislav Janousek, Noritaka Yusa i 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, nr 4 (7.09.2006): 719–28. http://dx.doi.org/10.1115/1.2767365.
Pełny tekst źródłaBehera, Sanjay Kumar, Dayal R. Parhi i 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, nr 2 (8.04.2019): 208–29. http://dx.doi.org/10.1108/ijsi-05-2018-0029.
Pełny tekst źródłaJu, Xiaochen, Xinxin Zhao i Shengsheng Qian. "TransMF: Transformer-Based Multi-Scale Fusion Model for Crack Detection". Mathematics 10, nr 13 (5.07.2022): 2354. http://dx.doi.org/10.3390/math10132354.
Pełny tekst źródłaWu, Zihao, Yunchao Tang, Bo Hong, Bingqiang Liang i Yuping Liu. "Enhanced Precision in Dam Crack Width Measurement: Leveraging Advanced Lightweight Network Identification for Pixel-Level Accuracy". International Journal of Intelligent Systems 2023 (2.09.2023): 1–16. http://dx.doi.org/10.1155/2023/9940881.
Pełny tekst źródłaWang, Li, i 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, nr 1-4 (10.12.2020): 721–28. http://dx.doi.org/10.3233/jae-209383.
Pełny tekst źródłaHwu, Chyan Bin, i Ying Chun Liang. "Crack Identification by Artificial Neural Network". Key Engineering Materials 145-149 (październik 1997): 405–10. http://dx.doi.org/10.4028/www.scientific.net/kem.145-149.405.
Pełny tekst źródłaLee, Sang Eon, i Jung-Wuk Hong. "Effect of Crack Closure on Magnitude of Modulated Wave". International Journal of Structural Stability and Dynamics 20, nr 13 (grudzień 2020): 2041018. http://dx.doi.org/10.1142/s0219455420410187.
Pełny tekst źródłaBai, Xiaotian, Zhaonan Zhang, Huaitao Shi, Zhong Luo i Tao Li. "Identification of Subsurface Mesoscale Crack in Full Ceramic Ball Bearings Based on Strain Energy Theory". Applied Sciences 13, nr 13 (30.06.2023): 7783. http://dx.doi.org/10.3390/app13137783.
Pełny tekst źródłaBian, Ziyan. "Identification of Concrete Crack Using Deep Learning Based Approach". Advances in Research 25, nr 5 (1.10.2024): 272–80. http://dx.doi.org/10.9734/air/2024/v25i51160.
Pełny tekst źródłaSong, Dowon, Taeseup Song, Ungyu Paik, Guanlin Lyu, Yeon-Gil Jung, Baig-Gyu Choi, In-Soo Kim i Jing Zhang. "Crack-Resistance Behavior of an Encapsulated, Healing Agent Embedded Buffer Layer on Self-Healing Thermal Barrier Coatings". Coatings 9, nr 6 (31.05.2019): 358. http://dx.doi.org/10.3390/coatings9060358.
Pełny tekst źródłaur-Rehman, A., i P. F. Thomason. "THE EFFECT OF ARTIFICIAL FATIGUE-CRACK CLOSURE ON FATIGUE-CRACK GROWTH". Fatigue & Fracture of Engineering Materials and Structures 16, nr 10 (październik 1993): 1081–90. http://dx.doi.org/10.1111/j.1460-2695.1993.tb00079.x.
Pełny tekst źródłaLee, Taehee, Jung-Ho Kim, Sung-Jin Lee, Seung-Ki Ryu i Bong-Chul Joo. "Improvement of Concrete Crack Segmentation Performance Using Stacking Ensemble Learning". Applied Sciences 13, nr 4 (12.02.2023): 2367. http://dx.doi.org/10.3390/app13042367.
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