Results 51 to 60 of about 1,151 (212)
Research on Defect Detection on Steel Rails Based on Improved YOLO11n Algorithm
Applied SciencesAiming at the core issues of the traditional YOLO11n model in rail surface defect detection—fine-grained feature loss of small defects, insufficient micro-target recognition accuracy, and the mismatch of existing downsampling/fusion methods for micro ...
Hongyu Wang, Junmei Zhao
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Surface Defect System for Long Product Manufacturing Using Differential Topographic Images
Sensors, 2020 Current industrial products must meet quality requirements defined by international standards. Most commercial surface inspection systems give qualitative detections after a long, cumbersome and very expensive configuration process made by the seller ...
F.J. delaCalle Herrero +2 more
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Carbon emission assessment of tunnel infrastructures: From construction to operation
Deep Underground Science and Engineering, EarlyView.This study develops a lifecycle carbon accounting framework for tunnel infrastructures, covering design, construction, operation, maintenance, and dismantling. Applied to a subsea tunnel case, the framework reveals the carbon emission distribution among four typical tunnel types and highlights potential carbon offset methods for low‐carbon tunnel ...
Luyuan Long +4 more
wiley +1 more source
Highly Nonlinear Solitary Waves for Rail Buckling Prevention [PDF]
, 2013 One of the major structural problems in the railroads made of continuous welded rails is buckling in hot weather and breakage or pulling apart in cold weather.
Cai, Luyao
core
Deep Learning (Fast R-CNN)-Based Evaluation of Rail Surface Defects
Applied SciencesIn current railway rails, trains are propelled by the rolling contact between iron wheels and iron rails, and the high frequency of train repetition on rails results in a significant load exertion on a very small area where the wheel and rail come into ...
Jung-Youl Choi, Jae-Min Han
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Simulation of Eddy Current Rail Testing Data for Neural Networks
e-Journal of Nondestructive Testing, 2023 The present work is part of the AIFRI project (Artificial Intelligence For Rail Inspection), where we and our project partners train a neural network for defect detection and classification.
Alexander Friedrich
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ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.First integration of ZnO nanorods with aerosol‐printed 3D Ag meshes for UV photodetector. 3D Ag/ZnO enhances light absorption and charge separation by providing a large active surface area for efficient charge generation and a strong UV response.
Elius Hossain +3 more
wiley +1 more source
Applied SciencesThe rail is an important factor in railway traffic safety. Surface defects in the rail head comprise a common type of rail damage, and magnetic flux leakage (MFL) technology is applied for its detection.
Yinliang Jia +3 more
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Review on Processing Control Strategy for Electrochemical Additive Manufacturing
MetalMat, EarlyView.This review systematically summarizes recent progress in processing control strategies for ECAM, with three key regulation dimensions: current monitoring and closed‐loop control, temperature regulation, and electrolyte flow/nozzle design. The roles of these parameters in governing electrochemical kinetics, mass transport, deposition stability, and ...
Xin Li, Yu Xie, Wangping Wu
wiley +1 more source
Zero-Shot Texture Analysis and Regression-Based Deformation Recognition for Rail Anomaly Detection
IEEE AccessThis paper presents a novel anomaly detection framework for rail systems, integrating zero-shot texture analysis and regression-based deformation recognition to monitor rail defects effectively.
Mikel Lainsa, Daeyoung Kim
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