DOI: https://doi.org/10.15587/1729-4061.2018.145713

Welded joints geometry testing by means of automated structured light scanning

German Filippov, Dmitry Sednev, Yana Salchak

Abstract


Nuclear industry in Russia plays an important role in total power generation. At the same time, it is considered to be dangerous in terms of high potential risk in a case of any failure occurrence. Therefore, constant monitoring and quality control is essential on every stage of energy production process, as well as maintenance of the technical quality of the exploited components. For that reason, specified regulatory documents are developed. They provide quality requirements for each component type and regulate inspection procedures. In this paper, welded joints were considered as the controlled object. It is represented that standard quality control methods based on the manual visual inspection are not accurate enough. Therefore, this paper suggests an advanced method of automated optical scanning for misalignment evaluation of welded parts based on structural light technique. Precision improvement was achieved by implementation of a robotic manipulator, which led to the development of the specific calibration technique. Considering that there are no established methodologies for such method the validation experiments were performed. The ability to detect the minimum displacement in accordance with nuclear industry regulatory documents was studied. The results demonstrated that misalignment of 0.47 mm can be measured, and it proves that proposed method can be further implemented for a practical application in nuclear industry

Keywords


3D-reconstruction; visual testing; structured light; industrial robot calibration; welding misalignment

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References


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GOST Style Citations


Mannan S. Lees' Process Safety Essentials. Elsevier, 2013. 570 p.

Parisher R. A., Rhea R. A. Pipe drafting and design. Elsevier, 2012. 418 p. doi: https://doi.org/10.1016/c2011-0-06090-8 

The Classification of Weld Seam Defects for Quantitative Analysis by means of Ultrasonic Testing / Salchak Y., Tverdokhlebova T., Sharavina S., Lider A. // IOP Conference Series: Materials Science and Engineering. 2016. Vol. 132. P. 012027. doi: https://doi.org/10.1088/1757-899x/132/1/012027 

Quantitative analysis of the SNF storage cask by means of ultrasonic testing / Salchak Y. A., Sednev D. A., Sharavina S. V., Tverdokhlebova T. S., Lider A. M. // International Congress on Advances in Nuclear Power Plants. 2016. P. 1362–1366.

Bredimas A., Nuttall W. J. An international comparison of regulatory organizations and licensing procedures for new nuclear power plants // Energy Policy. 2008. Vol. 36, Issue 4. P. 1344–1354. doi: https://doi.org/10.1016/j.enpol.2007.10.035 

PNAE G-7-010-89, Equipment and Piping of Nuclear Power Installations. Weld Joints and Weld. Overlays. Rules of inspection. Moscow: Gospromatomnadzor, 2000. 80 p.

Training Guidelines in Non-Destructive Testing Techniques: Manual for Visual Testing at Level 2. Vienna: IAEA, 2013. 226 p.

Improved visual inspection of advanced gas-cooled reactor fuel channels / West G., Murray P., Marshall S., McArthur S. // International Journal of Prognostics and Health Management. 2015. URL: http://ftp.phmsociety.org/sites/phmsociety.org/files/phm_submission/2015/ijphm_15_012.pdf

Development and Testing of Visual Inspection Applications for Tokamak Maintenance / Dutta P., Rastogi N., Joshi S., Patel A., Trivedi M., Gotewal K. K. // Evelopment and testing of visual inspection applications for tokamak maintenance. 2015. doi: http://doi.org/10.13140/RG.2.1.2979.0965

Remote controlled robot for visual inspection and sampling of the interior surface of CANDU pressure tubes / Ionescu S., Marinescu R., Mincu M., Petre M., Prisecaru I. // UPB Scientific Bulletin. Series C: Electrical Engineering. 2018. Vol. 80, Issue 1. P. 267–282.

A flexible 3D laser scanning system using a robotic arm / Fei Z., Zhou X., Gao X., Zhang G. // Optical Measurement Systems for Industrial Inspection X. 2017. doi: https://doi.org/10.1117/12.2278898 

Feature Extraction of Welding Seam Image Based on Laser Vision / Lu X., Gu D., Wang Y., Qu Y., Qin C., Huang F. // IEEE Sensors Journal. 2018. Vol. 18, Issue 11. P. 4715–4724. doi: https://doi.org/10.1109/jsen.2018.2824660 

A calibration algorithm of the structured light vision for the arc welding robot / Li W.-B., Cao G.-Z., Sun J.-D., Liang Y.-X., Huang S.-D. // 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). 2017. doi: https://doi.org/10.1109/urai.2017.7992782 

Feasibility Study of a Structured Light System Applied to Welding Inspection Based on Articulated Coordinate Measure Machine Data / Rodriguez-Martin M., Rodriguez-Gonzalvez P., Gonzalez-Aguilera D., Fernandez-Hernandez J. // IEEE Sensors Journal. 2017. Vol. 17, Issue 13. P. 4217–4224. doi: https://doi.org/10.1109/jsen.2017.2700954 

Zhang Z. Iterative point matching for registration of free-form curves and surfaces // International Journal of Computer Vision. 1994. Vol. 13, Issue 2. P. 119–152. doi: https://doi.org/10.1007/bf01427149 

The Trimmed Iterative Closest Point algorithm / Chetverikov D., Svirko D., Stepanov D., Krsek P. // Object recognition supported by user interaction for service robots. 2002. doi: https://doi.org/10.1109/icpr.2002.1047997 

Fukunaga K., Narendra P. M. A Branch and Bound Algorithm for Computing k-Nearest Neighbors // IEEE Transactions on Computers. 1975. Vol. C-24, Issue 7. P. 750–753. doi: https://doi.org/10.1109/t-c.1975.224297 







Copyright (c) 2018 German Filippov, Dmitry Sednev, Yana Salchak

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ISSN (print) 1729-3774, ISSN (on-line) 1729-4061