Observation of a dynamic specular weld pool surface

Zhang, Y M; Song, Hui; Saeed, Gohar

doi:10.1088/0957-0233/17/6/l02

Cited by 46 publications

(25 citation statements)

References 5 publications

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“…Hence, an automatic search for the third highest peak for the 100th and 300th columns is applied. After the third peak is found, the threshold is determined based on the minimum of the peak values T = min(p31,p32)-1 (10) where p3\ is the third peak pixel value for the 100th column and /)32 is the third peak pixel value for the 300th column. Figure 16(i/) shows the segmented result.…”

Section: S{x) *D If (Xy±^)e a Or If (±í)mentioning

confidence: 99%

“…This principle which takes advantage of the difference in the propagation natures of the arc light and illumination laser has been proven to work in the back-lighting method u.sed to image droplets in gas metal arc welding (GMAW) [7][8][9] which shots a laser from one side of the torch but intercepts the laser that has been partially blocked by the droplet at the opposite side. Using this principle, the corresponding author's group has established an experimental set-up where a continuous low power laser is used to acquire clear images of laser lines reflected from the weld pool surface in gas tungsten arc welding (GTAW) [10] and the weld pool surface has been successfully measured [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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Machine Recognition of Laser Reflection From Gas Metal Arc Weld Pool Surfaces

Wang

Zhang

2011

Journal of Manufacturing Science and Engineering

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The reflection of projected laser lines may be used to determine the three-dimensional geometty of the reflecting weld pool surface. However, for gas metal arc welding (GMAWj, the transfer of the droplets into the weld pool makes the weld pool suiface highly dynamic and fluctuating. The position and geometry of the local reflecting suiface, which intercepts and reflects the projected laser changes rapidly. As a resuh, the reflection rays change their trajectories rapidly. The contrast of laser reflection with the background is much reduced and methods are needed to extract laser reflection from low contrast images. To this end, an image quality measurement method is proposed based on the number of the edge points to determine if an image may be further processed. The image lo be processed is then modeled as a superposition of the laser reflection and arc radiation background. Methods have been proposed to remove the uneven distribution of the arc radiation background from the image, such that a global threshold is possible to segment the laser reflection lines. The set of the laser line points are then clustered to form separate laser lines. These laser lines are then modeled and the parameters in the models are used to validate each modeled line. Processing results verified the effectiveness of the proposed methods/algorithms in providing laser lines from low contrast images that are formed by laser reflection from a high dynamic gas metal arc weld pool surface.

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Section: S{x) *D If (Xy±^)e a Or If (±í)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Machine Recognition of Laser Reflection From Gas Metal Arc Weld Pool Surfaces

Wang

Zhang

2011

Journal of Manufacturing Science and Engineering

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“…Destas duas abordagens apresentadas, diferentes observações da imagem especular da poça são reportadas [3,4] exemplo, o estudo da movimentação de escória e vórtices [12] e termometria [13], inclusive com sofisticações como uso de grade de laser [14,15] para caracterização tridimensional da poça.…”

Section: Cuidados Principaisunclassified

Cuidados ao se extrair dimensões de fotografia/filmagem em soldagem

2009

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Resumo As técnicas de fotografia e filmagem abriram caminhos para estudos em todas as áreas da IntroduçãoNão há dúvidas com relação ao potencial investigativo de uma imagem/filmagem. As técnicas de fotografia e filmagem abriram caminhos para estudos em todas as áreas da soldagem, seja metalurgia, processos, fabricação ou projeto. Microconstituintes, estruturas, transferência metálica, escoamento de gases, macrografias, deformações, medições geométricas de peças, dentre outras características têm sido estudadas com tais técnicas.Embora tenham uso fundamental na soldagem, tem-se notado constantes erros na utilização das técnicas de fotografia e filmagem, como erros de posicionamento, calibração, escolha do sensor, tipo e compactação de imagem. Desta forma, pretende-se abordar os principais detalhes para se extrair dimensões de uma imagem de forma prática para que o usuário possa aproveitar todo o potencial de sua fotografia/filmagem. Além disto, esperase que haja comentários sobre o texto no sentido de melhorar e trazer à tona esta importante discussão. Ressalta-se a finalidade do texto é apresentar um desafio, onde muitos usam a técnica, mas não a empregam de forma otimizada.Os tópicos seguintes procuram abordar os principais cuidados ao se medir imagens e filmes a partir da soldagem, onde são cobertos os temas de compensações geométricas para o posicionamento da câmera e a otimização de seu posicionamento, informações referentes à imagem e algumas características de câmera e sensores.

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“…They can detect weld pool geometry and weld pool surface depression and thus provide weld penetration information. [1][2][3][4][5] In keyhole plasma arc welding, the keyhole representing the weld quality can also be detected by a visual sensor. 6,7 In addition, visual sensors have also been used to track weld seam 8,9 through detecting root gap and weld groove.…”

Section: Introductionmentioning

confidence: 99%

Vision based measuring system for both weld pool and root gap in continuous current GTAW

Gao¹,

Wu²

2007

Science and Technology of Welding and Joining

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A low cost vision based measuring system is developed to detect both the weld pool geometry and root gap simultaneously. Efforts are made from both hardware and software aspects to decrease the strong interference from arc light during gas tungsten arc welding (GTAW) process with continuous current. A normal charge coupled device (CCD) camera is cooperated with specially made composite filter lens and the video signals before A/D conversion are adjusted according to the welding current. Clear images of both root gap and weld pool are captured under different welding parameters. The grey level distribution characteristics of root gap edges and weld pool edges in images are analysed and utilised for developing the algorithms for image processing. The continuum of weld pool edge and the linear features of root gap are also utilised in the algorithm. The results show that the algorithms can extract the weld pool edge and root gap edge effectively. A solid foundation for weld seam tracking and weld penetration control by a single sensor is thus established.

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Observation of a dynamic specular weld pool surface

Cited by 46 publications

References 5 publications

Machine Recognition of Laser Reflection From Gas Metal Arc Weld Pool Surfaces

Machine Recognition of Laser Reflection From Gas Metal Arc Weld Pool Surfaces

Cuidados ao se extrair dimensões de fotografia/filmagem em soldagem

Vision based measuring system for both weld pool and root gap in continuous current GTAW

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