{"title":"对管道焊点进行可靠的视觉检测","authors":"Huijun An, Lingbao Kong","doi":"10.1108/ssmt-04-2023-0018","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>Solder joint inspection plays a critical role in various industries, with a focus on integrated chip (IC) solder joints and metal surface welds. However, the detection of tubular solder joints has received relatively less attention. This paper aims to address the challenges of detecting small targets and complex environments by proposing a robust visual detection method for pipeline solder joints. The method is characterized by its simplicity, cost-effectiveness and ease of implementation.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>A robust visual detection method based on the characteristics of pipeline solder joints is proposed. With the improved hue, saturation and value (HSV) color space, the method uses a multi-level template matching approach to first segment the pipeline from the background, and then match the endpoint of the pipeline to accurately locate the solder joint. The proposed method leverages the distinctive characteristics of pipeline solder joints and employs an enhanced HSV color space. A multi-level template matching approach is utilized to segment the pipeline from the background and accurately locate the solder joint by matching the pipeline endpoint.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The experimental results demonstrate the effectiveness of the proposed solder joint detection method in practical detection tasks. The average precision of pipeline weld joint localization exceeds 95%, while the average recall is greater than 90%. These findings highlight the applicability of the method to pipeline solder joint detection tasks, specifically in the context of production lines for refrigeration equipment.</p><!--/ Abstract__block -->\n<h3>Research limitations/implications</h3>\n<p>The precision of the method is influenced by the placement angle and lighting conditions of the test specimen, which may pose challenges and impact the algorithm's performance. Potential avenues for improvement include exploring deep learning methods, incorporating additional features and contextual information for localization, and utilizing advanced image enhancement techniques to improve image quality.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>The proposed pipeline solder joint detection method offers a novel and practical approach. The simplicity, cost-effectiveness and ease of implementation make it an attractive choice for detecting pipeline solder joints in different industrial applications.</p><!--/ Abstract__block -->","PeriodicalId":49499,"journal":{"name":"Soldering & Surface Mount Technology","volume":"38 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust vision detection of pipeline solder joints\",\"authors\":\"Huijun An, Lingbao Kong\",\"doi\":\"10.1108/ssmt-04-2023-0018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>Solder joint inspection plays a critical role in various industries, with a focus on integrated chip (IC) solder joints and metal surface welds. However, the detection of tubular solder joints has received relatively less attention. This paper aims to address the challenges of detecting small targets and complex environments by proposing a robust visual detection method for pipeline solder joints. The method is characterized by its simplicity, cost-effectiveness and ease of implementation.</p><!--/ Abstract__block -->\\n<h3>Design/methodology/approach</h3>\\n<p>A robust visual detection method based on the characteristics of pipeline solder joints is proposed. With the improved hue, saturation and value (HSV) color space, the method uses a multi-level template matching approach to first segment the pipeline from the background, and then match the endpoint of the pipeline to accurately locate the solder joint. The proposed method leverages the distinctive characteristics of pipeline solder joints and employs an enhanced HSV color space. A multi-level template matching approach is utilized to segment the pipeline from the background and accurately locate the solder joint by matching the pipeline endpoint.</p><!--/ Abstract__block -->\\n<h3>Findings</h3>\\n<p>The experimental results demonstrate the effectiveness of the proposed solder joint detection method in practical detection tasks. The average precision of pipeline weld joint localization exceeds 95%, while the average recall is greater than 90%. These findings highlight the applicability of the method to pipeline solder joint detection tasks, specifically in the context of production lines for refrigeration equipment.</p><!--/ Abstract__block -->\\n<h3>Research limitations/implications</h3>\\n<p>The precision of the method is influenced by the placement angle and lighting conditions of the test specimen, which may pose challenges and impact the algorithm's performance. Potential avenues for improvement include exploring deep learning methods, incorporating additional features and contextual information for localization, and utilizing advanced image enhancement techniques to improve image quality.</p><!--/ Abstract__block -->\\n<h3>Originality/value</h3>\\n<p>The proposed pipeline solder joint detection method offers a novel and practical approach. The simplicity, cost-effectiveness and ease of implementation make it an attractive choice for detecting pipeline solder joints in different industrial applications.</p><!--/ Abstract__block -->\",\"PeriodicalId\":49499,\"journal\":{\"name\":\"Soldering & Surface Mount Technology\",\"volume\":\"38 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Soldering & Surface Mount Technology\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1108/ssmt-04-2023-0018\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soldering & Surface Mount Technology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1108/ssmt-04-2023-0018","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Solder joint inspection plays a critical role in various industries, with a focus on integrated chip (IC) solder joints and metal surface welds. However, the detection of tubular solder joints has received relatively less attention. This paper aims to address the challenges of detecting small targets and complex environments by proposing a robust visual detection method for pipeline solder joints. The method is characterized by its simplicity, cost-effectiveness and ease of implementation.
Design/methodology/approach
A robust visual detection method based on the characteristics of pipeline solder joints is proposed. With the improved hue, saturation and value (HSV) color space, the method uses a multi-level template matching approach to first segment the pipeline from the background, and then match the endpoint of the pipeline to accurately locate the solder joint. The proposed method leverages the distinctive characteristics of pipeline solder joints and employs an enhanced HSV color space. A multi-level template matching approach is utilized to segment the pipeline from the background and accurately locate the solder joint by matching the pipeline endpoint.
Findings
The experimental results demonstrate the effectiveness of the proposed solder joint detection method in practical detection tasks. The average precision of pipeline weld joint localization exceeds 95%, while the average recall is greater than 90%. These findings highlight the applicability of the method to pipeline solder joint detection tasks, specifically in the context of production lines for refrigeration equipment.
Research limitations/implications
The precision of the method is influenced by the placement angle and lighting conditions of the test specimen, which may pose challenges and impact the algorithm's performance. Potential avenues for improvement include exploring deep learning methods, incorporating additional features and contextual information for localization, and utilizing advanced image enhancement techniques to improve image quality.
Originality/value
The proposed pipeline solder joint detection method offers a novel and practical approach. The simplicity, cost-effectiveness and ease of implementation make it an attractive choice for detecting pipeline solder joints in different industrial applications.
期刊介绍：
Soldering & Surface Mount Technology seeks to make an important contribution to the advancement of research and application within the technical body of knowledge and expertise in this vital area. Soldering & Surface Mount Technology compliments its sister publications; Circuit World and Microelectronics International.
The journal covers all aspects of SMT from alloys, pastes and fluxes, to reliability and environmental effects, and is currently providing an important dissemination route for new knowledge on lead-free solders and processes. The journal comprises a multidisciplinary study of the key materials and technologies used to assemble state of the art functional electronic devices. The key focus is on assembling devices and interconnecting components via soldering, whilst also embracing a broad range of related approaches.
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