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Automatic detection of surface defects
SCIENTIA SINICA Informationis, 2017In the automobile manufacturing industry, the detection of surface defects is a crucial process for quality control. This study simulates the process by which engineers find defects on an outer surface using a parallel light reflection map and the proposed integral reflection map (IRM)detection algorithm.
Quan LI, Jin HUANG, Hujun BAO, Zeyun SHI
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Few-Shot Steel Surface Defect Detection
IEEE Transactions on Instrumentation and Measurement, 2022Deep learning based algorithms have been widely employed to build reliable steel surface defect detection systems, which are important for manufacturing. The performance of deep learning models relies heavily on abundant annotated data. Nevertheless, the labeled image volume in industrial datasets is often limited.
Haohan Wang, Zhuoling Li, Haoqian Wang
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ULTRASONIC DETECTION OF SURFACE-BREAKING RAILHEAD DEFECTS
AIP Conference Proceedings, 2008We recently presented measurements of defects on the railhead, using a novel pitch‐catch ultrasonic system comprising of two electro‐magnetic acoustic transducers (EMATs) generating and detecting Rayleigh waves. Current systems used on the UK rail network for detecting surface breaking defects are limited in speed ( 5 mm).
Edwards, R. S. +7 more
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Surface Defect Detection Using Image Pyramid
IEEE Sensors Journal, 2020Surface defect detection has received increased attention in relation to the product quality and industry safety. This paper develops an image pyramid convolution neural network (IPCNN) model to detect surface defects in images. The IPCNN is an improvement of the Mask rcnn model.
Ling Xiao, Bo Wu, Youmin Hu
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Surface and internal defect detection
1998This chapter deals with the detection of surface and internal defects on components and structures. To be able to use the component or structure after examination, obviously, the inspection should not affect the item involved, and must therefore be non-destructive.
G. Hands, T. Armitt
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Surface defects detection of railway turnouts
2015 34th Chinese Control Conference (CCC), 2015As the turnout is a critical part of railway tracks, its surface defects are directly related to the operation safety. The defects detection of turnout is an effect way to ensure the safety and comfort of urban transit railway. In this paper, the feature extraction of the turnout defects is investigated based on the bogie acceleration measurements. The
Li Shen, Xiukun Wei, Limin Jia
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Nondestructive Defect Detection From Optical Surfaces
SPIE Proceedings, 1985Defects responsible for laser damage in visible-wavelength mirrors are observed at nondamaging intensities using a new video microscope system. Studies suggest that a defect scattering phenomenon combined with lag characteristics of video cameras makes this possible.
C. D. Marrs, J. O. Porteus, J. R. Palmer
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Defect detection on semiconductor wafer surfaces
Microelectronic Engineering, 2005A template-based vision system for the 100% inspection of wafer die surfaces has been developed. Design goals included a requirement for the detection of flaws as small as two thousandths of an inch on parts up to 8-in. wafer size. Each die is treated as one part of the whole wafer. One of the good dies is trained and kept as template die for the whole
N.G. Shankar, Z.W. Zhong
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Surface Defect Detection Using YOLO Network
2020Detecting defects on surfaces such as steel, can be a challenging task because defects have complex and unique features. These defects occur in many production lines and vary from one production line to another. In order to detect these defects, the You Only Look Once (YOLO) detector which uses a Convolutional Neural Network (CNN), is used and received
Muhieddine Hatab +2 more
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A DEFECT DETECTION SCHEME FOR WEB SURFACE INSPECTION
International Journal of Pattern Recognition and Artificial Intelligence, 2000The goal of this work was to develop an improved defect detection scheme for high-speed real-time web surface inspection. This goal was realized by splitting the task into two independent parts: feature extraction and segmentation. Both parts were implemented using efficient algorithms which were implemented in hardware that is suitable and fast ...
JUKKA IIVARINEN +4 more
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