A review on sensor based monitoring and control of friction stir welding process and a roadmap to Industry 4.0

D Mishra, RB Roy, S Dutta, SK Pal… - Journal of Manufacturing …, 2018 - Elsevier
This review is on the various techniques and methodologies applied to sensor based
monitoring of the quality and control of defects in an advanced joining process named …

Review on computer aided weld defect detection from radiography images

W Hou, D Zhang, Y Wei, J Guo, X Zhang - Applied Sciences, 2020 - mdpi.com
The weld defects inspection from radiography films is critical for assuring the serviceability
and safety of weld joints. The various limitations of human interpretation made the …

Detection and segmentation of manufacturing defects with convolutional neural networks and transfer learning

M Ferguson, R Ak, YTT Lee… - Smart and …, 2018 - asmedigitalcollection.asme.org
Quality control is a fundamental component of many manufacturing processes, especially
those involving casting or welding. However, manual quality control procedures are often …

Automated detection of welding defects in pipelines from radiographic images DWDI

N Boaretto, TM Centeno - Ndt & E International, 2017 - Elsevier
This paper presents a method for the automatic detection and classification of defects in
radiographic images of welded joints obtained by exposure technique of double wall double …

Transfer learning with CNN for classification of weld defect

S Kumaresan, KSJ Aultrin, SS Kumar, MD Anand - Ieee Access, 2021 - ieeexplore.ieee.org
Traditional Image Processing Techniques (IPT), used for automating the detection and
classification of weld defects from radiography images, have their own limitations, which can …

Ultrasonic testing in the field of engineering joining

Z Fan, K Bai, C Chen - The International Journal of Advanced …, 2024 - Springer
In recent years, with the development of materials science, the joining technology is also
constantly upgraded, ultrasonic testing technology can more accurately detect the defects or …

Automatic detection and classification of the ceramic tiles' surface defects

SH Hanzaei, A Afshar, F Barazandeh - Pattern recognition, 2017 - Elsevier
Defect detection and classification of ceramic tile surface defects occurred in firing units are
usually performed by human observations in most factories. In this paper, an automatic …

Automatic detection of welding defects using deep neural network

W Hou, Y Wei, J Guo, Y **, C Zhu - Journal of physics …, 2018 - iopscience.iop.org
In this paper, we propose an automatic detection schema including three stages for weld
defects in x-ray images. Firstly, the preprocessing procedure for the image is implemented to …

Deep features based on a DCNN model for classifying imbalanced weld flaw types

W Hou, Y Wei, Y **, C Zhu - Measurement, 2019 - Elsevier
Feature extraction and feature selection are vital steps to construct an intelligent diagnosis
system for classifying the weld flaws from an X-ray image. Deep learning has been …

Multiclass defect detection and classification in weld radiographic images using geometric and texture features

I Valavanis, D Kosmopoulos - Expert Systems with Applications, 2010 - Elsevier
In this paper, a method for the detection and classification of defects in weld radiographs is
presented. The method has been applied for detecting and discriminating discontinuities in …