A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVM
In the field of welding robotics, visual sensors, which are mainly composed of a camera and a laser, have proven to be promising devices because of their high precision, good stability, and high safety factor. In real welding environments, there are various kinds of weld joints due to the diversity...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/2/471 |
| _version_ | 1811278931491291136 |
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| author | Jiang Zeng Guang-Zhong Cao Ye-Ping Peng Su-Dan Huang |
| author_facet | Jiang Zeng Guang-Zhong Cao Ye-Ping Peng Su-Dan Huang |
| author_sort | Jiang Zeng |
| collection | DOAJ |
| description | In the field of welding robotics, visual sensors, which are mainly composed of a camera and a laser, have proven to be promising devices because of their high precision, good stability, and high safety factor. In real welding environments, there are various kinds of weld joints due to the diversity of the workpieces. The location algorithms for different weld joint types are different, and the welding parameters applied in welding are also different. It is very inefficient to manually change the image processing algorithm and welding parameters according to the weld joint type before each welding task. Therefore, it will greatly improve the efficiency and automation of the welding system if a visual sensor can automatically identify the weld joint before welding. However, there are few studies regarding these problems and the accuracy and applicability of existing methods are not strong. Therefore, a weld joint identification method for visual sensor based on image features and support vector machine (SVM) is proposed in this paper. The deformation of laser around a weld joint is taken as recognition information. Two kinds of features are extracted as feature vectors to enrich the identification information. Subsequently, based on the extracted feature vectors, the optimal SVM model for weld joint type identification is established. A comparative study of proposed and conventional strategies for weld joint identification is carried out via a contrast experiment and a robustness testing experiment. The experimental results show that the identification accuracy rate achieves 98.4%. The validity and robustness of the proposed method are verified. |
| first_indexed | 2024-04-13T00:45:40Z |
| format | Article |
| id | doaj.art-a127ad6926dd4bdc8f8a11fe70752ff7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T00:45:40Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a127ad6926dd4bdc8f8a11fe70752ff72022-12-22T03:10:01ZengMDPI AGSensors1424-82202020-01-0120247110.3390/s20020471s20020471A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVMJiang Zeng0Guang-Zhong Cao1Ye-Ping Peng2Su-Dan Huang3Shenzhen Key Laboratory of Electromagnetic Control, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, ChinaShenzhen Key Laboratory of Electromagnetic Control, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, ChinaShenzhen Key Laboratory of Electromagnetic Control, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, ChinaShenzhen Key Laboratory of Electromagnetic Control, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, ChinaIn the field of welding robotics, visual sensors, which are mainly composed of a camera and a laser, have proven to be promising devices because of their high precision, good stability, and high safety factor. In real welding environments, there are various kinds of weld joints due to the diversity of the workpieces. The location algorithms for different weld joint types are different, and the welding parameters applied in welding are also different. It is very inefficient to manually change the image processing algorithm and welding parameters according to the weld joint type before each welding task. Therefore, it will greatly improve the efficiency and automation of the welding system if a visual sensor can automatically identify the weld joint before welding. However, there are few studies regarding these problems and the accuracy and applicability of existing methods are not strong. Therefore, a weld joint identification method for visual sensor based on image features and support vector machine (SVM) is proposed in this paper. The deformation of laser around a weld joint is taken as recognition information. Two kinds of features are extracted as feature vectors to enrich the identification information. Subsequently, based on the extracted feature vectors, the optimal SVM model for weld joint type identification is established. A comparative study of proposed and conventional strategies for weld joint identification is carried out via a contrast experiment and a robustness testing experiment. The experimental results show that the identification accuracy rate achieves 98.4%. The validity and robustness of the proposed method are verified.https://www.mdpi.com/1424-8220/20/2/471weld joint type identificationimage feature extractionvisual sensorsupport vector machine (svm) |
| spellingShingle | Jiang Zeng Guang-Zhong Cao Ye-Ping Peng Su-Dan Huang A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVM Sensors weld joint type identification image feature extraction visual sensor support vector machine (svm) |
| title | A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVM |
| title_full | A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVM |
| title_fullStr | A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVM |
| title_full_unstemmed | A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVM |
| title_short | A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVM |
| title_sort | weld joint type identification method for visual sensor based on image features and svm |
| topic | weld joint type identification image feature extraction visual sensor support vector machine (svm) |
| url | https://www.mdpi.com/1424-8220/20/2/471 |
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