{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T07:55:49Z","timestamp":1770278149265,"version":"3.49.0"},"reference-count":32,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2024,6,23]],"date-time":"2024-06-23T00:00:00Z","timestamp":1719100800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Korean Planning &amp; Evaluation Institute of Industrial Technology","award":["1761002860"],"award-info":[{"award-number":["1761002860"]}]},{"name":"the Korean Planning &amp; Evaluation Institute of Industrial Technology","award":["IITP-2024-RS-2023-00254177"],"award-info":[{"award-number":["IITP-2024-RS-2023-00254177"]}]},{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP)","award":["1761002860"],"award-info":[{"award-number":["1761002860"]}]},{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP)","award":["IITP-2024-RS-2023-00254177"],"award-info":[{"award-number":["IITP-2024-RS-2023-00254177"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In the shipbuilding industry, welding automation using welding robots often relies on arc-sensing techniques due to spatial limitations. However, the reliability of the feedback current value, core sensing data, is reduced when welding target workpieces have significant curvature or gaps between curved workpieces due to the control of short-circuit transition, leading to seam tracking failure and subsequent damage to the workpieces. To address these problems, this study proposes a new algorithm, MBSC (median-based spatial clustering), based on the DBSCAN (density-based spatial clustering of applications with noise) clustering algorithm. By performing clustering based on the median value of data in each weaving area and considering the characteristics of the feedback current data, the proposed technique utilizes detected outliers to enhance seam tracking accuracy and responsiveness in unstructured and challenging welding environments. The effectiveness of the proposed technique was verified through actual welding experiments in a yard environment.<\/jats:p>","DOI":"10.3390\/s24134075","type":"journal-article","created":{"date-parts":[[2024,6,24]],"date-time":"2024-06-24T06:59:58Z","timestamp":1719212398000},"page":"4075","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Data Clustering Utilization Technologies Using Medians of Current Values for Improving Arc Sensing in Unstructured Environments"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-0462-8765","authenticated-orcid":false,"given":"Hee-Jun","family":"Kim","sequence":"first","affiliation":[{"name":"Samsung Heavy Industries Co., Ltd., Geoje-si 53261, Republic of Korea"},{"name":"Department of Computer Engineering, Pusan National University, Busan 43241, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2064-9364","authenticated-orcid":false,"given":"Jeong-Ho","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Pusan National University, Busan 43241, Republic of Korea"},{"name":"Center for Artificial Intelligence Research, Pusan National University, Busan 43241, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1362-8441","authenticated-orcid":false,"given":"Shin-Nyeong","family":"Heo","sequence":"additional","affiliation":[{"name":"Samsung Heavy Industries Co., Ltd., Geoje-si 53261, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Do-Hyung","family":"Jeon","sequence":"additional","affiliation":[{"name":"Samsung Heavy Industries Co., Ltd., Geoje-si 53261, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1341-7978","authenticated-orcid":false,"given":"Won-Suk","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Pusan National University, Busan 43241, Republic of Korea"},{"name":"Center for Artificial Intelligence Research, Pusan National University, Busan 43241, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Boekholt, R. (1996). Welding Mechanisation and Automation in Shipbuilding Worldwide: Production Methods and Trends Based on Yard Capacity, Elsevier.","DOI":"10.1533\/9780857093196"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1108\/01439910510600218","article-title":"Sensors in robotic arc welding to support small series production","volume":"32","author":"Olsson","year":"2005","journal-title":"Ind. Robot Int. J."},{"key":"ref_3","unstructured":"Bostelman, R., Jacoff, A., and Bunch, R. (1999, January 1\u20134). Delivery of an Advanced Double-Hull Ship Welding System using RoboCrane. Proceedings of the Intelligent Industrial Automation (IIA\u201999) & Soft Computing (SOCO\u201999), Genova, Italy."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1007\/s00773-010-0099-5","article-title":"Development of a mobile welding robot for double-hull structures in shipbuilding","volume":"15","author":"Ku","year":"2010","journal-title":"J. Mar. Sci. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.rcim.2018.08.003","article-title":"Advances in weld seam tracking techniques for robotic welding: A review","volume":"56","author":"Rout","year":"2019","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_6","first-page":"322S","article-title":"Arc sensing for defects in constant-voltage gas metal arc welding","volume":"78","author":"Madigan","year":"1999","journal-title":"Weld J."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1186\/s40712-015-0042-y","article-title":"Robotic arc welding sensors and programming in industrial applications","volume":"10","author":"Kah","year":"2015","journal-title":"Int. J. Mech. Mater. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1109\/TIE.1983.356736","article-title":"Robotic arc welding: Research in sensory feedback control","volume":"3","author":"Cook","year":"1983","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1179\/174329306X153196","article-title":"Mathematical modelling of rotational arc sensor in GMAW and its applications to seam tracking and endpoint detection","volume":"11","author":"Shi","year":"2006","journal-title":"Sci. Technol. Weld. Join."},{"key":"ref_10","first-page":"102","article-title":"Development of Digital controlled SCR type CO2 Welding System for Implementation Pulse Output","volume":"32","author":"Eun","year":"2014","journal-title":"J. Weld. Join."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1109\/PESC.1999.789058","article-title":"A new instantaneous output current control method for inverter arc welding machine","volume":"Volume 1","author":"Chae","year":"1999","journal-title":"Proceedings of the 30th Annual IEEE Power Electronics Specialists Conference. Record. (Cat. No. 99CH36321)"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4","DOI":"10.5781\/KWJS.2007.25.6.004","article-title":"A review of welding current waveform control and mechanical control technique for reduction of spatter in short circuit transfer","volume":"25","author":"Kim","year":"2007","journal-title":"J. Weld. Join."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"854","DOI":"10.1016\/j.jmapro.2022.05.029","article-title":"Application of sensing technology in intelligent robotic arc welding: A review","volume":"79","author":"Xu","year":"2022","journal-title":"J. Manuf. Process."},{"key":"ref_14","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"Volume 96","author":"Ester","year":"1996","journal-title":"KDD-96 Proceedings"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Roiger, R.J. (2017). Data Mining: A Tutorial-Based Primer, Chapman and Hall\/CRC.","DOI":"10.1201\/9781315382586"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1007\/s00170-007-0939-6","article-title":"A visual seam tracking system for robotic arc welding","volume":"37","author":"Xu","year":"2008","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_17","first-page":"79","article-title":"Development of a multiline laser vision sensor for joint tracking in welding","volume":"88","author":"Sung","year":"2009","journal-title":"Weld J."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Changyong, T., Xuhao, S., Tie, Y., and Yi, Z. (2022, January 6\u201311). Laser Weld Seam Tracking Sensing Technology Based on Swing Mirror. Proceedings of the 2022 IEEE 7th Optoelectronics Global Conference (OGC), Shenzhen, China.","DOI":"10.1109\/OGC55558.2022.10050920"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"42345","DOI":"10.1109\/ACCESS.2021.3065956","article-title":"Intelligent guidance programming of welding robot for 3D curved welding seam","volume":"9","author":"Zhou","year":"2021","journal-title":"IEEE Access"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7261","DOI":"10.1109\/TIE.2017.2694399","article-title":"Automatic welding seam tracking and identification","volume":"64","author":"Li","year":"2017","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.optlastec.2018.01.010","article-title":"Real-time seam tracking control system based on line laser visions","volume":"103","author":"Zou","year":"2018","journal-title":"Opt. Laser Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3481","DOI":"10.1007\/s00170-023-12667-5","article-title":"Robust weld seam tracking method based on detection and tracking of laser stripe","volume":"130","author":"Wang","year":"2024","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_23","first-page":"1","article-title":"Intelligent seam tracking of an ultranarrow gap during K-TIG welding: A hybrid CNN and adaptive ROI operation algorithm","volume":"72","author":"Lin","year":"2022","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1023\/A:1022652706683","article-title":"Robotic welding systems with vision-sensing and self-learning neuron control of arc welding dynamic process","volume":"36","author":"Chen","year":"2003","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_25","first-page":"173","article-title":"A study on the Selection of Arc Sensing Signal for Seam Tracking in Pulsed GMAW","volume":"38","author":"Seo","year":"2020","journal-title":"J. Weld. Join"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"5227","DOI":"10.1007\/s00170-023-11442-w","article-title":"Weld seam tracking method of root pass welding with variable gap based on magnetically controlled arc sensor","volume":"126","author":"Lin","year":"2023","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_27","first-page":"157","article-title":"Sensors in arc welding","volume":"20","author":"Ushio","year":"1991","journal-title":"Trans. JWRI"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Lu, J., Yang, A., Chen, X., Xu, X., Lv, R., and Zhao, Z. (2022). A seam tracking method based on an image segmentation deep convolutional neural network. Metals, 12.","DOI":"10.3390\/met12081365"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2813","DOI":"10.1007\/s00170-017-0633-2","article-title":"Rectangular fillet weld tracking by robots based on rotating arc sensors in gas metal arc welding","volume":"93","author":"Le","year":"2017","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2705","DOI":"10.1007\/s00170-016-8990-9","article-title":"Circular fillet weld tracking in GMAW by robots based on rotating arc sensors","volume":"88","author":"Le","year":"2017","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"16339","DOI":"10.1109\/JSEN.2022.3189681","article-title":"Infrared visual sensing detection approach of swing arc narrow gap weld deviation based on outlier data filtering","volume":"22","author":"Su","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_32","unstructured":"Jang, J., and Jiang, H. (2019, January 9\u201315). DBSCAN++: Towards fast and scalable density clustering. Proceedings of the International Conference on Machine Learning, Long Beach, CA, USA."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/13\/4075\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:03:08Z","timestamp":1760108588000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/13\/4075"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,23]]},"references-count":32,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["s24134075"],"URL":"https:\/\/doi.org\/10.3390\/s24134075","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6,23]]}}}