{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T12:23:27Z","timestamp":1781007807755,"version":"3.54.1"},"reference-count":30,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2017,5,10]],"date-time":"2017-05-10T00:00:00Z","timestamp":1494374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This work proposes a new methodology for the detection of discontinuities in the weld bead applied in Shielded Metal Arc Welding (SMAW) processes. The detection system is based on two sensors\u2014a microphone and piezoelectric\u2014that acquire acoustic emissions generated during the welding. The feature vectors extracted from the sensor dataset are used to construct classifier models. The approaches based on Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers are able to identify with a high accuracy the three proposed weld bead classes: desirable weld bead, shrinkage cavity and burn through discontinuities. Experimental results illustrate the system\u2019s high accuracy, greater than 90% for each class. A novel Hierarchical Support Vector Machine (HSVM) structure is proposed to make feasible the use of this system in industrial environments. This approach presented 96.6% overall accuracy. Given the simplicity of the equipment involved, this system can be applied in the metal transformation industries.<\/jats:p>","DOI":"10.3390\/s17051082","type":"journal-article","created":{"date-parts":[[2017,5,10]],"date-time":"2017-05-10T12:04:20Z","timestamp":1494417860000},"page":"1082","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Discontinuity Detection in the Shield Metal Arc Welding Process"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0059-725X","authenticated-orcid":false,"given":"Jos\u00e9","family":"Cocota","sequence":"first","affiliation":[{"name":"School of Mines, Federal University of Ouro Preto (UFOP), Morro do Cruzeiro, 35400-000 Ouro Preto, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabriel","family":"Garcia","sequence":"additional","affiliation":[{"name":"Instituto Tecnol\u00f3gico Vale (ITV)\u2014Avenida Juscelino Kubitschek, 31, Bauxita, 35400-000 Ouro Preto, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3123-0701","authenticated-orcid":false,"given":"Adilson","family":"Da Costa","sequence":"additional","affiliation":[{"name":"School of Mines, Federal University of Ouro Preto (UFOP), Morro do Cruzeiro, 35400-000 Ouro Preto, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Milton","family":"De Lima","sequence":"additional","affiliation":[{"name":"Institute for Advanced Studies (IEAv-CTA), 12228-970 S\u00e3o Jos\u00e9 dos Campos, SP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Filipe","family":"Rocha","sequence":"additional","affiliation":[{"name":"Instituto Tecnol\u00f3gico Vale (ITV)\u2014Avenida Juscelino Kubitschek, 31, Bauxita, 35400-000 Ouro Preto, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gustavo","family":"Freitas","sequence":"additional","affiliation":[{"name":"Instituto Tecnol\u00f3gico Vale (ITV)\u2014Avenida Juscelino Kubitschek, 31, Bauxita, 35400-000 Ouro Preto, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,5,10]]},"reference":[{"key":"ref_1","unstructured":"O\u2019Brien, A. (2004). AWS Welding Handbook, American Welding Society. [9th ed.]."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3717","DOI":"10.1109\/TIE.2016.2522945","article-title":"Robust Product Design Using SOSM for Control of Shielded Metal Arc-Welding (SMAW) Process","volume":"63","author":"Paul","year":"2016","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_3","first-page":"166","article-title":"Robotic Shielded Metal Arc Welding","volume":"89","author":"Lima","year":"2010","journal-title":"Weld. J."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Paul, A.K. (2013, January 21\u201323). Sliding Surface in 1-Sliding Boosts Multi-objective Optimization Program of Shielded Metal Arc Welding Process. Proceedings of the International Conference on Advanced Electronic Systems, Pilani, India.","DOI":"10.1109\/ICAES.2013.6659357"},{"key":"ref_5","first-page":"176","article-title":"Laser-Vision-Based Measurement and Analysis of Weld Pool Oscillation Frequency in GTAW-P","volume":"94","author":"Shi","year":"2015","journal-title":"Weld. J."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.measurement.2015.04.001","article-title":"Influence of Argon Pollution on the Weld Surface Morphology","volume":"70","author":"Krolczyk","year":"2015","journal-title":"Measurement"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.1109\/TII.2014.2309482","article-title":"Multisensor Fusion System for Monitoring High-Power Disk Laser Welding Using Support Vector Machine","volume":"10","author":"You","year":"2014","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_8","unstructured":"Ao, S., Luo, Z., Zhao, N., and Wang, R. (2010, January 18\u201320). Blind Source Separation based on Principal Component Analysis\u2014Independent Component Analysis for Acoustic Signal during Laser Welding Process. Proceedings of the International Conference on Digital Manufacturing and Automation, ChangSha, China."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"6953","DOI":"10.3390\/s120606953","article-title":"Sensoring Fusion Data from the Optic and Acoustic Emissions of Electric Arcs in the GMAW-S Process for Welding Quality Assessment","volume":"12","author":"Alfaro","year":"2012","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Apasov, A.M., and Apasov, A.A. (2012, January 18\u201321). Acoustic Emission Diagnostics of Fault Fusion in Welding. Proceedings of the International Forum on Strategic Technology, Tomsk, Russia.","DOI":"10.1109\/IFOST.2012.6357718"},{"key":"ref_11","first-page":"5525","article-title":"Ultrasonic Time of Flight Diffraction Technique for Weld Defects: A Review","volume":"24","author":"Manjula","year":"2012","journal-title":"Res. J. Appl. Sci. Eng. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1109\/28.60056","article-title":"Artificial Neural Networks Applied to Arc Welding Process Modeling and Control","volume":"26","author":"Andersen","year":"1990","journal-title":"IEEE Trans. Ind. Appl."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1484","DOI":"10.1109\/28.475745","article-title":"Weld Modeling and Control Using Artificial Neural Networks","volume":"31","author":"Cook","year":"1995","journal-title":"IEEE Trans. Ind. Appl."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/S0924-0136(02)00101-2","article-title":"Prediction of Weld Bead Geometry and Penetration in Shielded Metal-Arc Welding Using Artificial Neural Networks","volume":"123","author":"Nagesh","year":"2002","journal-title":"J. Mater. Proc. Tech."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1016\/j.jmatprotec.2006.12.012","article-title":"Artificial Neural Networks for Predicting Diffusible Hydrogen Content and Cracking Susceptibility in Rutile Flux-cored Arc Welds","volume":"184","author":"Sterjovski","year":"2007","journal-title":"J. Mater. Proc. Tech."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.ndteint.2006.12.001","article-title":"Real-time Arc-welding Defect Detection and Classification with Principal Component Analysis and Artificial Neural Networks","volume":"40","author":"Mirapeix","year":"2007","journal-title":"NDT E Int."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6496","DOI":"10.3390\/s8106496","article-title":"Arc-Welding Spectroscopic Monitoring based on Feature Selection and Neural Networks","volume":"8","author":"Mirapeix","year":"2008","journal-title":"Sensors"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.measurement.2015.11.031","article-title":"Analysis of Arc Welding Process Using Digital Storage Oscilloscope","volume":"81","author":"Kumar","year":"2016","journal-title":"Measurement"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1117\/12.463427","article-title":"Optical Sensor for Real Time Weld Defects Detection","volume":"4669","author":"Ancona","year":"2002","journal-title":"Proc. SPIE"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5263","DOI":"10.3390\/s90705263","article-title":"Use of the Plasma Spectrum RMS Signal for Arc-Welding Diagnostics","volume":"9","author":"Mirapeix","year":"2009","journal-title":"Sensors"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.jmatprotec.2016.07.015","article-title":"EMD-based pulsed TIG welding process porosity defect detection and defect diagnosis using GA-SVM","volume":"239","author":"Huang","year":"2017","journal-title":"J. Mater. Proc. Tech."},{"key":"ref_22","unstructured":"Rocha, F.A.S., Serrantola, W.G., Lopez, G.N., Torga, D.S., de Carvalho, M.A., de Souza, G.P., Cocota, J.A.N., and R\u00eago Segundo, A.K. (2015, January 25\u201328). Retrofitting of a XY Table. Proceedings of the XII Brazilian Symposium on Intelligent Automation, Natal, Brazil."},{"key":"ref_23","first-page":"85","article-title":"Quality Level Assessment for Imperfections in GMAW","volume":"93","author":"Kumar","year":"2014","journal-title":"Weld. J."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Giannakopoulos, T., and Pikrakis, A. (2014). Introduction to Audio Analysi, Academic Press. [1st ed.].","DOI":"10.1016\/B978-0-08-099388-1.00001-7"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wersborg, I.S.G., Bautze, T., Born, F., and Diepold, K. (2009, January 15\u201318). A cognitive approach for a robotic welding system that can learn how to weld from acoustic data. Proceedings of the International Conference on Computational Intelligence in Robotics and Automation, Daejeon, Korea.","DOI":"10.1109\/CIRA.2009.5423224"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3549","DOI":"10.3390\/s100403549","article-title":"Plasma Plume Oscillations Monitoring during Laser Welding of Stainless Steel by Discrete Wavelet Transform Application","volume":"10","author":"Sibillano","year":"2010","journal-title":"Sensors"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"628","DOI":"10.1109\/TIE.2014.2319216","article-title":"PD-PCA-Based Laser Welding Process Monitoring and Defects Diagnosis by Using FNN and SVM","volume":"62","author":"You","year":"2015","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_28","first-page":"190","article-title":"Monitoring and Control of Penetration in GTAW and Pipe Welding","volume":"92","author":"Li","year":"2013","journal-title":"Weld. J."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Kannatey-Asibu, E. (2009). Principles of Laser Materials Processing, John Wiley & Sons. [1st ed.].","DOI":"10.1002\/9780470459300"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.micpro.2008.11.001","article-title":"FPGA implementation of time-frequency analysis algorithms for laser welding monitoring","volume":"33","author":"Molino","year":"2009","journal-title":"J. Microprocess. Microsyst."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/5\/1082\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:35:21Z","timestamp":1760207721000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/5\/1082"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,10]]},"references-count":30,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2017,5]]}},"alternative-id":["s17051082"],"URL":"https:\/\/doi.org\/10.3390\/s17051082","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,10]]}}}