Results 101 to 110 of about 1,151 (212)

Steel Surface Defect Detection Method Based on Improved YOLOX

IEEE Access
Steel is a crucial material that is extensively utilized in various aspects of daily life and holds significant importance. However, during its production, there is a possibility of certain defects arising that could have a negative impact on the quality
Chengfei Li, Ao Xu, Qibo Zhang, Yufei Cai   +3 more
doaj   +1 more source

Hybrid deep learning architecture for rail surface segmentation and surface defect detection

Computer-Aided Civil and Infrastructure Engineering, 2022
Yunpeng Wu, Yong Qin 0002, Yu Qian, Feng Guo, Zhipeng Wang 0002, Limin Jia 0002   +5 more
openaire   +1 more source

EHA-YOLOv5: An Efficient and Highly Accurate Improved YOLOv5 Model for Workshop Bearing Rail Defect Detection Application

IEEE Access
Addressing the challenge of surface defect detection in load-bearing rails within auto-motive assembly workshops, which operate in complex environments and under long-term service, this paper proposes an innovative detection framework based on an ...
Jiyong Hu, Hongfei Yang, Jiatang He, Dongxu Bai, Hongda Chen   +4 more
doaj   +1 more source

On-line high-speed rail defect detection : part II. [PDF]

FR-RRD-0001-10-01-00The objectives of this project were (1) to improve the defect detection reliability and (2) to improve the inspection speed of conventional rail defect detection methods.
Lanza di Scalea, Francesco, Salamone, Salvatore, Bartoli, Ivan, Phillips, Robert, University of California, San Diego, Coccia, Stefano, Rizzo, Piervincenzo   +6 more
core  

Dynamic Rail Inspection by Vision System

, 2007
Current in-field rail track ultrasonic inspection technologies, requiring contact between the probes and the rail surface, show limitations as defect detection is affected by rail surface condition, rail head geometry and defect geometry and orientation.
Nigrelli, V., Cerniglia, D., Prior, F.
core   +1 more source

PerMSCA-YOLO: A Perceptual Multi-Scale Convolutional Attention Enhanced YOLOv8 Model for Rail Defect Detection

Applied Sciences
With the widespread application of high-speed and heavy-load railways, the real-time detection of track surface defects has become increasingly crucial. To address the challenges in rail defect detection, this study proposes the PerMSCA-YOLO model, which
Jialiang Zhang, Ruiqi Zhang, Fengkai Luan, Hu Zhang   +3 more
doaj   +1 more source

Edge-Aware Illumination Enhancement for Fine-Grained Defect Detection on Railway Surfaces

Mathematics
Fine-grained defects on rail surfaces are often inadequately detected by conventional vision-based object detection models in low-light environments.
Geuntae Bae, Sungan Yoon, Jeongho Cho
doaj   +1 more source

Ultrasonic rail defect inspection-technology and applications

, 2020
U suvremenim željezničkim sustavima, tračnice su izložene stalnom porastu brzine i opterećenja s osovina vozila te stalnom porastu naprezanja u zavarenim spojevima.
Pavić-Brčić, Ante
core  

Defect Detection on Rail Base Area Using Infrared Thermography

, 2020
This research aims to investigate the application of infrared thermography (IRT) as a method of nondestructive evaluation (NDE) for the detection of defects in the rail base area.
Shrestha, Survesh Bahadur
core  

Tools for detection and classification Application to the diagnosis of rail surface defect

, 2004
The works concern with detection and classification problems for fault diagnosis. Two approaches are treated. The first one, where the K-classes global problem is splitted into sub problems, is called simultaneous detection and classification. Each sub problem is solved by a block that links together pre-processing phase, choice of the representation ...
openaire   +2 more sources