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Transactions on Intelligent Welding Manufacturing Volume III No. 4 2019 Transactions on Intelligent Welding Manufacturing Editors-in-Chief ShanbenChen YumingZhang ZhiliFeng ShanghaiJiaoTongUniversity DepartmentofElectrical OakRidgeNationalLaboratory Shanghai,China andComputerEngineering OakRidge,TN,USA UniversityofKentucky Lexington,KY,USA HonoraryEditors G.Cook,USA S.J.Na,KOR T.Lienert,USA K.L.Moore,USA LinWu,PRC T.J.Tarn,USA Ji-LuanPan,PRC Y.Hirata,JAP S.A.David,USA J.Norrish,AUS GuestEditors H.P.Chen,USA X.Q.Chen,NZL D.Du,PRC D.Fan,PRC J.C.Feng,PRC D.Hong,USA X.D.Jiao,PRC I.Lopez-Juarez,MEX H.J.Li,AUS W.Zhou,SGP RegionalEditors Asia:L.X.Zhang,PRC Australia:Z.X.Pan,AUS America:Y.K.Liu,USA Europe:S.Konovalov,RUS AssociateEditors Q.X.Cao,PRC Y.Huang,USA PedroNeto,PRT S.Wang,PRC B.H.Chang,PRC S.Konovalov,RUS G.Panoutsos,UK X.W.Wang,PRC J.Chen,USA W.H.Li,PRC Z.X.Pan,AUS Z.Z.Wang,PRC H.B.Chen,PRC X.R.Li,USA X.D.Peng,NL G.J.Zhang,PRC S.J.Chen,PRC Y.K.Liu,USA Y.Shi,PRC H.Zhang,B,PRC X.Z.Chen,PRC L.M.Liu,PRC J.Wu,USA H.Zhang,N,PRC A.-K.Christiansson,SWE H.Lu,PRC J.X.Xue,PRC L.X.Zhang,PRC Z.G.Li,PRC Z.Luo,PRC L.J.Yang,PRC W.J.Zhang,USA X.M.Hua,PRC G.H.Ma,PRC M.Wang,PRC AcademicAssistantEditors J.Cao,PRC S.B.Lin,PRC S.L.Wang,PRC H.W.Yu,PRC B.Chen,PRC Y.Shao,USA J.Xiao,PRC K.Zhang,PRC Y.Luo,PRC Y.Tao,PRC J.J.Xu,PRC W.Z.Zhang,PRC N.Lv,PRC J.J.Wang,PRC Y.L.Xu,PRC Z.F.Zhang,PRC F.Li,PRC H.Y.Wang,PRC C.Yu,PRC EditorialStaff ExecutiveEditor(ManuscriptandPublication): Dr.YanZhang,PRC ResponsibleEditors(AcademicandTechnical): Dr.NaLv,PRC Dr.JingWu,USA More information about this series at http://www.springer.com/series/15698 Shanben Chen Yuming Zhang Zhili Feng (cid:129) (cid:129) Editors Transactions on Intelligent Welding Manufacturing Volume III No. 4 2019 123 Editors Shanben Chen YumingZhang ShanghaiJiao Tong University Department ofElectrical andComputer Shanghai, China Engineering University of Kentucky Zhili Feng Lexington, KY,USA Oak RidgeNational Laboratory Oak Ridge,TN, USA ISSN 2520-8519 ISSN 2520-8527 (electronic) Transactions onIntelligent Welding Manufacturing ISBN978-981-33-6501-8 ISBN978-981-33-6502-5 (eBook) https://doi.org/10.1007/978-981-33-6502-5 ©SpringerNatureSingaporePteLtd.2021 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfrom therelevantprotectivelawsandregulationsandthereforefreeforgeneraluse. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained hereinorforanyerrorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregard tojurisdictionalclaimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSingaporePteLtd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Editorials This issue of the Transactions on Intelligent Welding Manufacturing (TIWM) is also a collection in part selected from the high-quality contributions recommended by “The 2019 International Workshop on Intelligentized Welding Manufacturing (IWIWM’2019).” It includes two feature articles, eight research papers and two short papers. The first featured article in this issue, “Multi-layer Multi-pass Welding of Medium Thickness Plate: Technologies, Advances and Future Prospects”, is con- tributedbyFengjingXu,ShanbenChenandYanlingXufromShanghaiJiaoTong University. This paper discusses the research status of multi-layer multi-pass (MLMP) welding of medium thickness plates and welding simulation process in detail. Novel feature extraction methods based on different sensing techniques are also summarized in this paper. The second featured article in this issue, “A Review: Application Research of Intelligent 3D Detection Technology Based on Linear-Structured Light”, is con- tributedbyShaojieChen,WeiTao,HuiZhaoandNaLv,fromShanghaiJiaoTong University.Thispaperanalyzesthelatestapplicationandresearchofline-structured light sensingtechnology intheindustrialapplicationofworkpieceobjectdetection and positioning, geometric profile measurement, three-dimensional reconstruction. The first research article, “Acoustic Emission-Based Weld Crack In-situ Detection and Location Using WT-TDOA”, is contributed by Zhifen Zhang, Rui QinandGuangruiWenallfromXi’anJiaoTongUniversity.Thispaperproposesa time difference of arrival (TDOA) method based on wavelet transform (WT) to enabletheaccurate locationofweldcracks atthebeginningofitsappearance.The results of the study show that TDOA based on wavelet transform (WT-TDOA) outperformed the conventional TDOA significantly in terms of location accuracy. The second research paper is entitled “The Research of Real-Time Welding QualityDetectionviaVisualSensorforMIGWeldingProcess”.Itisacontribution from a research team at Beibu Gulf University. A real-time monitoring system basedonvisualsensingtechnologyisproposed,aimingattheonlinemonitoringof weld quality in welding process. Based on the ROI visual attention mechanism, images of the front and back of the pool were extracted. A random forest special v vi Editorials fusion model based on weld parameters and image features is constructed, which realizes the recognition of weld penetration status classification and the regression prediction of weld back penetration width. The third research paper titled “A Weld Bead Profile Extraction Method Based onScanningMonocularStereoVisionforMulti-layerMulti-passWeldingonMid- thickPlate”iscontributedbyaresearchteamfromShanghaiJiaoTongUniversity. This paper studies multi-layer multi-pass welding (MLMPW). In this paper, scanning monocular stereo vision for MLMPW is used to reconstruct the weld bead. Through the slicing and filtering of the point cloud data, the profile of the weld bead surface is obtained, which provides a solid foundation for MLMPP and its online correction. The fourth research paper, “The Intelligent Methodology for Monitoring the Dynamic Welding Quality Using Visual and Audio Sensor”, is co-authored by Zhiqiang Feng, Ziquan Jiao and Junfeng Han affiliated with the Beibu Gulf University, China. In this paper, a real-time welding quality prediction scheme basedonmulti-informationfusionisproposed.Theresultsshowthatthearcsound andvisualinformationcouldcomplementeachotherandbeeffectivelycombinedto achieve adequate online welding quality monitoring. The fifth research paper, “Convolutional Neural Network Prediction of Aluminum Alloy GTAW Penetration Process Based on Arc Sound Sensing”, is contributed by a research team from Shanghai Jiao Tong University. This paper uses industrial Internet of things (IoT) to design a set of technical solutions, uploading various data collected during the welding process to the cloud for stor- age, and to remotely monitor the welding process in real time through a browser. A weld penetration state classification model based on convolutional neural net- works is also established. The sixth research paper, “Identification and Penetration Prediction of Aluminum Alloy GTAW Pool Based on Network Vision Monitoring”, is a con- tributionfromShanghaiJiaoTongUniversity.Weldpenetrationdetectionbasedon weld pool image intungsteninert gas(TIG)welding has been a hotresearch topic inindustryandacademia.Inthispaper,apredictionmodelofthemeltwidthonthe back of the aluminum alloy TIG weld pool and a classification model of the alu- minum alloy TIG welding state are constructed and XGBoost-based models are used for real-time prediction of backside bead width. Theseventhresearch paper inthecollectionis“Research onWeldingTransient Deformation Monitoring Technology Based on Non-contact Sensor Technology” contributed from researchers at Beibu Gulf University. This paper tries to analyze theresearchondetectionofweldingdeformationindifferentsensorytechnologies. The results show that they could get good result in a different application envi- ronment for different sensing technologies. The non-contact detection could get more intelligent and more accurate, and the contact detection is more reliable and widely used in industry. The last research paper, “Binocular Stereo Vision and Modified DBSCAN on Point Clouds for Single Leaf Segmentation”, is a contribution from Shanghai Jiao Tong University. In this paper, a modified density-based spatial clustering of Editorials vii applications with noise (DBSCAN) algorithm based on the above new-defined distance metric is used to cluster the refined point clouds. In the category of short papers, “Teaching-Free Intelligent Robotic Welding of HeterocyclicMediumandThickPlatesBasedonVision”isfromZhejiangNormal University. It provides technical support for the “intelligent manufacturing” upgrade of China’s high-end marine engineering equipment and has important valueinengineeringpromotion.“In-ProcessVisualMonitoringofPenetrationState in Nuclear Steel Pipe Welding” from Shanghai Jiao Tong University develops a pipe inner inspection robot equipped with CMOS sensor and laser scanner. The result shows that this monitoring system has an important impact on the quality control of the all-position pipe welding process. This issue of TIWM shows the new perspectives and developments in the field of intelligent welding research, as well as the topics related to the IWIWM’2019 Conference. The publication of this issue will certainly give readers new inspira- tion, as we always hope so. Prof. Yuming Zhang TIWM Editor-in-Chief University of Kentucky Lexington, KY, USA [email protected] Contents Feature Articles Multi-layer Multi-pass Welding of Medium Thickness Plate: Technologies, Advances and Future Prospects . . . . . . . . . . . . . . . . . . . . 3 Fengjing Xu, Runquan Xiao, Zhen Hou, Yanling Xu, Huajun Zhang, and Shanben Chen A Review: Application Research of Intelligent 3D Detection Technology Based on Linear-Structured Light. . . . . . . . . . . . . . . . . . . . 35 Shaojie Chen, Wei Tao, Hui Zhao, and Na Lv Research Papers Acoustic Emission-Based Weld Crack In-situ Detection and Location Using WT-TDOA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Zhifen Zhang, Rui Qin, Yujiao Yuan, Wenjing Ren, Zhe Yang, and Guangrui Wen The Research of Real-Time Welding Quality Detection via Visual Sensor for MIG Welding Process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Junfeng Han, Zhiqiang Feng, Ziquan Jiao, and Xiangxi Han A Weld Bead Profile Extraction Method Based on Scanning Monocular Stereo Vision for Multi-layer Multi-pass Welding on Mid-thick Plate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Zhen Hou, Yanling Xu, Runquan Xiao, and Shanben Chen The Intelligent Methodology for Monitoring the Dynamic Welding Quality Using Visual and Audio Sensor . . . . . . . . . . . . . . . . . . . . . . . . . 99 Zhiqiang Feng, Ziquan Jiao, Junfeng Han, and Weiming Huang ConvolutionalNeuralNetworkPredictionofAluminumAlloyGTAW Penetration Process Based on Arc Sound Sensing . . . . . . . . . . . . . . . . . 115 Zisheng Jiang, Chao Chen, Shanben Chen, and Na Lv ix x Contents Identification and Penetration Prediction of Aluminum Alloy GTAW Pool Based on Network Vision Monitoring . . . . . . . . . . . . . . . . . . . . . . 131 YiLei Luo, Chao Chen, ZiSheng Jiang, and Shanben Chen Research on Welding Transient Deformation Monitoring Technology Based on Non-contact Sensor Technology . . . . . . . . . . . . . . . . . . . . . . . 149 Ziquan Jiao, Zhiqiang Feng, Junfeng Han, and Weiming Huang Binocular Stereo Vision and Modified DBSCAN on Point Clouds for Single Leaf Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Chengyu Tao, Na Lv, and Shanben Chen Short Papers and Technical Notes Teaching-Free Intelligent Robotic Welding of Heterocyclic Medium and Thick Plates Based on Vision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Hu Lan, Huajun Zhang, Jun Fu, Libin Gao, and Liang Wei In-Process Visual Monitoring of Penetration State in Nuclear Steel Pipe Welding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Liangrui Wang, Shu’ang Wang, Weihua Liu, Yuefeng Chen, and Huabin Chen Information for Authors. .... ..... .... .... .... .... .... ..... .... 201 Author Index.. .... .... .... ..... .... .... .... .... .... ..... .... 203

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