A Study on the Optimal Offset Distance Between Welding Torch and the Infrared Thermometers
Detection of weld defects using real-time monitoring and controlling algorithm is of the significant task in manufacturing industries due to the increased production and liability costs that result when weld defects are not identified early in the production cycle. Monitoring and controlling for rob...
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Veröffentlicht in: | Fluid dynamics & materials processing 2019-01, Vol.15 (1), p.1-14 |
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description | Detection of weld defects using real-time monitoring and controlling algorithm is of the significant task in manufacturing industries due to the increased production and liability costs that result when weld defects are not identified early in the production cycle. Monitoring and controlling for robotic arc welding process employed should be reliable, flexible and cost-effective in non-clean, high-volume production environments. Also, the robotic welding system has been utilized a complex jigging and mechanical devices to move the workpiece which related to the stationary welding head for getting higher efficiency and lower costs. To develop the fully robotic welding system, people make use of their senses of sound and/or sight to collect welding information, and take the necessary corrective measurements to ensure the weld quality after processing is satisfactory. Therefore, it is really required that the monitoring and controlling algorithm of sensors for increasing effectiveness in the robotic welding process has been developed. In this paper, bead-on-plate welding using an infrared thermography in the robotic GMA (Gas Metal Arc) welding process has been performed to study the effects of welding parameters on thermal profile characteristics and find the optimal offset distance which applied for monitoring and controlling of welding quality such as bead height. The analysis for correlation between temperature distributions at three offset distance and bead height which based on the regression analysis such as Standard Error of Estimate (SEE), the coefficient of correlation (R) and coefficient of determination (R2) and (Predictive Ability of Model) has been done. The infra-red sensor is useful for monitoring the isotherm radii that arise during the robotic welding process and identifying bead height as welding quality. |
doi_str_mv | 10.32604/fdmp.2019.04759 |
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Monitoring and controlling for robotic arc welding process employed should be reliable, flexible and cost-effective in non-clean, high-volume production environments. Also, the robotic welding system has been utilized a complex jigging and mechanical devices to move the workpiece which related to the stationary welding head for getting higher efficiency and lower costs. To develop the fully robotic welding system, people make use of their senses of sound and/or sight to collect welding information, and take the necessary corrective measurements to ensure the weld quality after processing is satisfactory. Therefore, it is really required that the monitoring and controlling algorithm of sensors for increasing effectiveness in the robotic welding process has been developed. In this paper, bead-on-plate welding using an infrared thermography in the robotic GMA (Gas Metal Arc) welding process has been performed to study the effects of welding parameters on thermal profile characteristics and find the optimal offset distance which applied for monitoring and controlling of welding quality such as bead height. The analysis for correlation between temperature distributions at three offset distance and bead height which based on the regression analysis such as Standard Error of Estimate (SEE), the coefficient of correlation (R) and coefficient of determination (R2) and (Predictive Ability of Model) has been done. The infra-red sensor is useful for monitoring the isotherm radii that arise during the robotic welding process and identifying bead height as welding quality.</description><identifier>ISSN: 1555-2578</identifier><identifier>ISSN: 1555-256X</identifier><identifier>EISSN: 1555-2578</identifier><identifier>DOI: 10.32604/fdmp.2019.04759</identifier><language>eng</language><publisher>Duluth: Tech Science Press</publisher><subject>Algorithms ; Arc welding ; Bead on plate welding ; Correlation analysis ; Error analysis ; Infrared imaging ; Jigging ; Liability ; Mechanical devices ; Monitoring ; Regression analysis ; Robotics ; Standard error ; Thermography ; Thermometers ; Weld defects ; Welding parameters ; Workpieces</subject><ispartof>Fluid dynamics & materials processing, 2019-01, Vol.15 (1), p.1-14</ispartof><rights>Copyright Tech Science Press 2019</rights><rights>2019. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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Monitoring and controlling for robotic arc welding process employed should be reliable, flexible and cost-effective in non-clean, high-volume production environments. Also, the robotic welding system has been utilized a complex jigging and mechanical devices to move the workpiece which related to the stationary welding head for getting higher efficiency and lower costs. To develop the fully robotic welding system, people make use of their senses of sound and/or sight to collect welding information, and take the necessary corrective measurements to ensure the weld quality after processing is satisfactory. Therefore, it is really required that the monitoring and controlling algorithm of sensors for increasing effectiveness in the robotic welding process has been developed. In this paper, bead-on-plate welding using an infrared thermography in the robotic GMA (Gas Metal Arc) welding process has been performed to study the effects of welding parameters on thermal profile characteristics and find the optimal offset distance which applied for monitoring and controlling of welding quality such as bead height. The analysis for correlation between temperature distributions at three offset distance and bead height which based on the regression analysis such as Standard Error of Estimate (SEE), the coefficient of correlation (R) and coefficient of determination (R2) and (Predictive Ability of Model) has been done. The infra-red sensor is useful for monitoring the isotherm radii that arise during the robotic welding process and identifying bead height as welding quality.</description><subject>Algorithms</subject><subject>Arc welding</subject><subject>Bead on plate welding</subject><subject>Correlation analysis</subject><subject>Error analysis</subject><subject>Infrared imaging</subject><subject>Jigging</subject><subject>Liability</subject><subject>Mechanical devices</subject><subject>Monitoring</subject><subject>Regression analysis</subject><subject>Robotics</subject><subject>Standard error</subject><subject>Thermography</subject><subject>Thermometers</subject><subject>Weld defects</subject><subject>Welding parameters</subject><subject>Workpieces</subject><issn>1555-2578</issn><issn>1555-256X</issn><issn>1555-2578</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kEtLAzEUhYMoWKt7lwHXU28yk0yyrPVVKHRhRXATMpkb29J5mKRI_71tdeHK1T2L75wLHyHXDEY5l1Dc-rrpRxyYHkFRCn1CBkwIkXFRqtM_-ZxcxLgGyEstigF5H9OXtK13tGtpWiKd92nV2A2dex8x0ftVTLZ1SO8wfSG29A039ar9oIsuuCW1bX1sTVsfbMCaLpYYmq7BhCFekjNvNxGvfu-QvD4-LCbP2Wz-NJ2MZ5nLC5Yy4VTJUHrQwoKXKG0BGp2oc6e0qKSVCgTKqq5AOgfKgZCyULaooFKignxIbn52-9B9bjEms-62od2_NDzXJZOcafEvxbmSJQAv9xT8UC50MQb0pg97H2FnGJijZ3PwbA6ezdFz_g3P2W_g</recordid><startdate>20190101</startdate><enddate>20190101</enddate><creator>Yun, Tae-Jong</creator><creator>Oh, Won-Bin</creator><creator>Lee, Bo-Ram</creator><creator>Son, Joon-Sik</creator><creator>Kim, Ill-soo</creator><general>Tech Science Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>JG9</scope><scope>KR7</scope><scope>L7M</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20190101</creationdate><title>A Study on the Optimal Offset Distance Between Welding Torch and the Infrared Thermometers</title><author>Yun, Tae-Jong ; Oh, Won-Bin ; Lee, Bo-Ram ; Son, Joon-Sik ; Kim, Ill-soo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c341t-5c871e6f095a0f6e6a409ec5d3c895b6a6805e6bdb06cc08c056648a4b0b85b03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Arc welding</topic><topic>Bead on plate welding</topic><topic>Correlation analysis</topic><topic>Error analysis</topic><topic>Infrared imaging</topic><topic>Jigging</topic><topic>Liability</topic><topic>Mechanical devices</topic><topic>Monitoring</topic><topic>Regression analysis</topic><topic>Robotics</topic><topic>Standard error</topic><topic>Thermography</topic><topic>Thermometers</topic><topic>Weld defects</topic><topic>Welding parameters</topic><topic>Workpieces</topic><toplevel>online_resources</toplevel><creatorcontrib>Yun, Tae-Jong</creatorcontrib><creatorcontrib>Oh, Won-Bin</creatorcontrib><creatorcontrib>Lee, Bo-Ram</creatorcontrib><creatorcontrib>Son, Joon-Sik</creatorcontrib><creatorcontrib>Kim, Ill-soo</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Materials Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Fluid dynamics & materials processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yun, Tae-Jong</au><au>Oh, Won-Bin</au><au>Lee, Bo-Ram</au><au>Son, Joon-Sik</au><au>Kim, Ill-soo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Study on the Optimal Offset Distance Between Welding Torch and the Infrared Thermometers</atitle><jtitle>Fluid dynamics & materials processing</jtitle><date>2019-01-01</date><risdate>2019</risdate><volume>15</volume><issue>1</issue><spage>1</spage><epage>14</epage><pages>1-14</pages><issn>1555-2578</issn><issn>1555-256X</issn><eissn>1555-2578</eissn><abstract>Detection of weld defects using real-time monitoring and controlling algorithm is of the significant task in manufacturing industries due to the increased production and liability costs that result when weld defects are not identified early in the production cycle. Monitoring and controlling for robotic arc welding process employed should be reliable, flexible and cost-effective in non-clean, high-volume production environments. Also, the robotic welding system has been utilized a complex jigging and mechanical devices to move the workpiece which related to the stationary welding head for getting higher efficiency and lower costs. To develop the fully robotic welding system, people make use of their senses of sound and/or sight to collect welding information, and take the necessary corrective measurements to ensure the weld quality after processing is satisfactory. Therefore, it is really required that the monitoring and controlling algorithm of sensors for increasing effectiveness in the robotic welding process has been developed. 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subjects | Algorithms Arc welding Bead on plate welding Correlation analysis Error analysis Infrared imaging Jigging Liability Mechanical devices Monitoring Regression analysis Robotics Standard error Thermography Thermometers Weld defects Welding parameters Workpieces |
title | A Study on the Optimal Offset Distance Between Welding Torch and the Infrared Thermometers |
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