Automatic inspection of gas pipeline welding defects using an expert vision system

Shafeek, Hani; Gadelmawla, E S; Abdel-Shafy, A A; Elewa, I M

doi:10.1016/j.ndteint.2003.10.004

Cited by 59 publications

(34 citation statements)

References 9 publications

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“…The classic expert system with weld defects classification rules drawn from sophisticated decision tree is described in [11]. The implemented knowledge base was gathered from specialists, textbooks and international standards.…”

Section: The Brief Overview Of Methods Used For Weld Defects Classifimentioning

confidence: 99%

The Application of Rough Sets Theory to Design of Weld Defect Classifiers

et al. 2017

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The innovative method for weld defect classification based on rough set theory is presented in this study. The classification rules have been generated by processing of data base composed of 640 radiographic images referring to certain welding process in aircraft industry. The obtained accuracy of defect identification (from 88% up to 100%, depending on class of defect and choice of classifier) can be evaluated as at least competitive or even better one comparing to results referring to other type of frequently "exploited" classifiers, those mentioned in attached overview section. The identification of weld defects is the final operation which is premised by complicated "chain" of consecutive operations transforming primary radiographs to the form enabling calculation of conditional attributes. That is why brief description of process of transformation of primary radiographs to the forms which are suitable for attributes calculation is included in the paper.

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Section: The Brief Overview Of Methods Used For Weld Defects Classifimentioning

confidence: 99%

The Application of Rough Sets Theory to Design of Weld Defect Classifiers

et al. 2017

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“…Thus, to fully achieve lightweight design in welded structures, manufacturing companies which utilize serial production will face challenges in quality assurance when introducing highstrength steel in their products. Other methods and tools which can be used for assessing the weld surface geometry are laser profile sensors or vision systems, in which the scanning device is used to acquire the surface and then an algorithm calculates certain surface features of the welded joint being measured [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Quality control and assurance in fabrication of welded structures subjected to fatigue loading

et al. 2017

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The current paper presents a comprehensive overview of weld quality control and assurance of welded structures where the major failure prevention is due to fatigue loading. It gives the drawbacks and limitation of quality control systems, international weld quality standards, and guidelines used in today's weld production. Furthermore, in recent development in quality control and assurance of welded structures, a new online method is presented. The main target is to enable a complete, online evaluation of large quantities of welds in an accurate and repeatable fashion. Information gathered will not only be used for determining the weld quality level with respect to the fatigue strength but also to be evaluated for use in improved process control, in welding power sources, and robot control systems. It is verified that the new online method, a new laser scanning technology, and algorithms can successfully be used as modern tools for automated unbiased geometrical weld quality assurance and implemented in weld production environment.

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“…This vision system, used to capture images for the radiographic films, can apply various image processing and computer vision algorithms to detect welding defects and calculate necessary information such as length, width, area, and perimeter of the defects. Shafeek et al [3] developed another vision system which makes use of various image processing and computer vision algorithms applied to capture images of the radiographic films to recognize the defects and to make acceptance decisions according to international standards. This system was capable of identifying and testing the main types of welding defects in gas pipelines welded by shielded metal arc welding.…”

Section: Introductionmentioning

confidence: 99%

Vision inspection system for the identification and classification of defects in MIG welding joints

Kumar

Natarajan

Ananthan

2011

Int J Adv Manuf Technol

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The variety of vision inspection systems for welding defects in the present manufacturing scenario is needed for overcoming certain limitations such as the problem of inaccuracy in the images, non-uniformed illumination, noise and deficient contrast, and confusion in defects if they occur in the same spot at the surface and subsurface. Hence, it is imperative to design a new vision inspection system which will enable to overcome the aforementioned problems in welding. A sophisticated new vision inspection system using machine vision has been developed for this study to identify and classify the surface defects of butt joint as per standard EN25817 in metal inert gas (MIG) welding. In this proposed vision system, images of welding surfaces are captured through a CCD camera. Four frames of sequence of images are obtained using four zones of LEDs using the front light illumination system in this method. From these images, the regions of interest are segmented and the average gray levels of the characteristic features of these images are calculated. The same process can be extended further to four zones (four quadrants) of four types of welded joints. Finally, welded joints can be classified into one of the four predefined ones based on the back-propagation neural network. The proposed system demonstrates an overall accuracy of 95% from the 80 real samples tested.

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Automatic inspection of gas pipeline welding defects using an expert vision system

Cited by 59 publications

References 9 publications

The Application of Rough Sets Theory to Design of Weld Defect Classifiers

The Application of Rough Sets Theory to Design of Weld Defect Classifiers

Quality control and assurance in fabrication of welded structures subjected to fatigue loading

Vision inspection system for the identification and classification of defects in MIG welding joints

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