A Novel Method of Using Vision System and Fuzzy Logic for Quality Estimation of Resistance Spot Welding
Finding a reliable quality inspection system of resistance spot welding (RSW) has become a very important issue in the automobile industry. In this study, improvement in the quality estimation of the weld nugget’s surface on the car underbody is introduced using image processing methods an...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-08-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/11/8/990 |
| _version_ | 1811300525586513920 |
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| author | Essa Alghannam Hong Lu Mingtian Ma Qian Cheng Andres A. Gonzalez Yue Zang Shuo Li |
| author_facet | Essa Alghannam Hong Lu Mingtian Ma Qian Cheng Andres A. Gonzalez Yue Zang Shuo Li |
| author_sort | Essa Alghannam |
| collection | DOAJ |
| description | Finding a reliable quality inspection system of resistance spot welding (RSW) has become a very important issue in the automobile industry. In this study, improvement in the quality estimation of the weld nugget’s surface on the car underbody is introduced using image processing methods and training a fuzzy inference system. Image segmentation, mathematical morphology (dilation and erosion), flood fill operation, least-squares fitting curve and some other new techniques such as location and value based selection of pixels are used to extract new geometrical characteristics from the weld nugget’s surface such as size and location, shape, and the numbers and areas of all side expulsions, peaks and troughs inside and outside the fusion zone. Topography of the weld nugget’s surface is created and shown as a 3D model based on the extracted geometrical characteristics from each spot. Extracted data is used to define input fuzzy functions for training a fuzzy logic inference system. Fuzzy logic rules are adopted based on knowledge database. The experiments are conducted on a 6 degree of freedom (DOF) robotic arm with a charge-coupled device (CCD) camera to collect pictures of various RSW locations on car underbodies. The results conclude that the estimation of the 3D model of the weld’s surface and weld’s quality can reach higher accuracy based on our proposed methods. |
| first_indexed | 2024-04-13T06:52:39Z |
| format | Article |
| id | doaj.art-d4ff28aa58ad4f64badf7d8754b64211 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-04-13T06:52:39Z |
| publishDate | 2019-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-d4ff28aa58ad4f64badf7d8754b642112022-12-22T02:57:21ZengMDPI AGSymmetry2073-89942019-08-0111899010.3390/sym11080990sym11080990A Novel Method of Using Vision System and Fuzzy Logic for Quality Estimation of Resistance Spot WeldingEssa Alghannam0Hong Lu1Mingtian Ma2Qian Cheng3Andres A. Gonzalez4Yue Zang5Shuo Li6School of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430000, ChinaSchool of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430000, ChinaSchool of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430000, ChinaSchool of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430000, ChinaSchool of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430000, ChinaSchool of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430000, ChinaSchool of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430000, ChinaFinding a reliable quality inspection system of resistance spot welding (RSW) has become a very important issue in the automobile industry. In this study, improvement in the quality estimation of the weld nugget’s surface on the car underbody is introduced using image processing methods and training a fuzzy inference system. Image segmentation, mathematical morphology (dilation and erosion), flood fill operation, least-squares fitting curve and some other new techniques such as location and value based selection of pixels are used to extract new geometrical characteristics from the weld nugget’s surface such as size and location, shape, and the numbers and areas of all side expulsions, peaks and troughs inside and outside the fusion zone. Topography of the weld nugget’s surface is created and shown as a 3D model based on the extracted geometrical characteristics from each spot. Extracted data is used to define input fuzzy functions for training a fuzzy logic inference system. Fuzzy logic rules are adopted based on knowledge database. The experiments are conducted on a 6 degree of freedom (DOF) robotic arm with a charge-coupled device (CCD) camera to collect pictures of various RSW locations on car underbodies. The results conclude that the estimation of the 3D model of the weld’s surface and weld’s quality can reach higher accuracy based on our proposed methods.https://www.mdpi.com/2073-8994/11/8/990resistance spot weldingvision systemimage processingfuzzy logic |
| spellingShingle | Essa Alghannam Hong Lu Mingtian Ma Qian Cheng Andres A. Gonzalez Yue Zang Shuo Li A Novel Method of Using Vision System and Fuzzy Logic for Quality Estimation of Resistance Spot Welding Symmetry resistance spot welding vision system image processing fuzzy logic |
| title | A Novel Method of Using Vision System and Fuzzy Logic for Quality Estimation of Resistance Spot Welding |
| title_full | A Novel Method of Using Vision System and Fuzzy Logic for Quality Estimation of Resistance Spot Welding |
| title_fullStr | A Novel Method of Using Vision System and Fuzzy Logic for Quality Estimation of Resistance Spot Welding |
| title_full_unstemmed | A Novel Method of Using Vision System and Fuzzy Logic for Quality Estimation of Resistance Spot Welding |
| title_short | A Novel Method of Using Vision System and Fuzzy Logic for Quality Estimation of Resistance Spot Welding |
| title_sort | novel method of using vision system and fuzzy logic for quality estimation of resistance spot welding |
| topic | resistance spot welding vision system image processing fuzzy logic |
| url | https://www.mdpi.com/2073-8994/11/8/990 |
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