Results 121 to 130 of about 326,783 (293)

LabelImg: CNN-Based Surface Defect Detection

In the journey of computer vision system development, the acquisition and utilization of annotated images play a central role, providing information about object identity, spatial extent, and viewpoint in depicted scenes. However, thermal manufacturing processes like Laser Powder Bed Fusion (LPBF) often yield surfaces with defects such as Spatter ...
Ilani, Mohsen Asghari, Banad, Yaser Mike
openaire   +2 more sources

Multimodal Mechanical Testing of Additively Manufactured Ti6Al4V Lattice Structures: Compression, Bending, and Fatigue

Advanced Engineering Materials, EarlyView.
In this experimental study, the mechanical properties of additively manufactured Ti‐6Al‐4V lattice structures of different geometries are characterized using compression, four point bending and fatigue testing. While TPMS designs show superior fatigue resistance, SplitP and Honeycomb lattice structures combine high stiffness and strength. The resulting
Klaus Burkart, Jonas Schmidt, Anastasiya Toenjes, Johanna Eisenträger   +3 more
wiley   +1 more source

Experimental Study on YOLO-Based Leather Surface Defect Detection

IEEE Access
Accurate, reliable, and fast intelligent detection of leather surface defects has become an important subject in industrial inspection, which aims at improving production efficiency and increasing automation levels.
Zhiqiang Chen, Qirui Zhu, Xiaofan Zhou, Jiehang Deng, Wei Song   +4 more
doaj   +1 more source

Laser Metal Deposition of Aluminum Alloys 7075 and 5083 with the Addition of Volatile Alloying Elements through Powder Blending

Advanced Engineering Materials, EarlyView.
This study investigates laser metal deposition of aluminum alloys EN AW‐7075 and EN AW‐5083, using powder blending to compensate zinc and magnesium evaporation. In situ alloying and ex situ alloying with ZnAl12 and AZ91 preserve near‐standard compositions and improve mechanical properties.
Finn Bendixen, Anastasiya Toenjes, Annika Bohlen, Thomas Seefeld   +3 more
wiley   +1 more source

Transfer learning-based approach using new convolutional neural network classifier for steel surface defects classification

Scientific African
Automatic surface defect detection of industrial products using visual inspection has progressively replaced manual defect detection of steel strips and become a necessary part of industrial product surface defect detection of steel strips. Various steel
Alaa Aldein M.S. Ibrahim, Jules R. Tapamo   +1 more
doaj   +1 more source

Automatic detection of surface defects

, 2007
A commonly occurring problem when manufacturing panels in certain polymeric composites is the occurrence of pores in the surface. At SICOMP AB there is a project with the aim of developing a system that can detect these pores that are not necessarily visible to the human eye.
openaire   +1 more source

Manufacturing Continuous Fiber‐Reinforced Printing Filaments: Development of a Post‐Consolidation Unit

Advanced Engineering Materials, EarlyView.
A novel, temperature‐controlled post‐consolidation unit is developed to test its potential to improve the melt impregnation process used to manufacture continuous fiber‐reinforced filaments for additive manufacturing of high‐performance thermoplastics.
Daniel Beermann, Patrick Schiebel, David May   +2 more
wiley   +1 more source

A Lightweight Strip Steel Surface Defect Detection Network Based on Improved YOLOv8

Sensors
Strip steel surface defect detection has become a crucial step in ensuring the quality of strip steel production. To address the issues of low detection accuracy and long detection times in strip steel surface defect detection algorithms caused by ...
Yuqun Chu, Xiaoyan Yu, Xianwei Rong
doaj   +1 more source

Rheocasting versus Die Casting: An Insight into the Low‐Cycle Fatigue Behavior of AlSi7Mg0.6

Advanced Engineering Materials, EarlyView.
The study compares rheocast lightweight components with high‐pressure die cast materials regarding microstructure and fatigue behavior. Rheocast process offers higher efficiency due to lower casting temperatures. Despite some microstructural differences, both processes show similar strengths (yield strength 125 MPa, tensile strength 240 MPa).
Julia Richter, Thomas Wegener, Andreas Schilling, Martin Fehlbier, Thomas Niendorf   +4 more
wiley   +1 more source

DEW-YOLO: An Efficient Algorithm for Steel Surface Defect Detection

Applied Sciences
To address the current steel surface defect detection algorithms in practical applications involving low detection accuracy, an efficient and highly accurate strip steel surface defect detection algorithm, DEW-YOLO, is proposed in this paper. Firstly, by
Junjie Li, Mingxia Chen
doaj   +1 more source