{"id":"https://openalex.org/W2527639036","doi":"https://doi.org/10.1109/aim.2016.7576823","title":"Automated identification and characterization of clustered weld defects","display_name":"Automated identification and characterization of clustered weld defects","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2527639036","doi":"https://doi.org/10.1109/aim.2016.7576823","mag":"2527639036"},"language":"en","primary_location":{"id":"doi:10.1109/aim.2016.7576823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aim.2016.7576823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101528762","display_name":"Hongyu Luo","orcid":"https://orcid.org/0000-0003-0977-0880"},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"H. Luo","raw_affiliation_strings":["Singapore Institute of Manufacturing Technology, Innovis, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Manufacturing Technology, Innovis, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015043863","display_name":"Q. H. Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Q. H. Chen","raw_affiliation_strings":["Singapore Institute of Manufacturing Technology, Innovis, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Manufacturing Technology, Innovis, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025635687","display_name":"Ngoc Chi Nam Doan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"N. C. N. Doan","raw_affiliation_strings":["Singapore Institute of Manufacturing Technology, Innovis, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Manufacturing Technology, Innovis, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100636013","display_name":"Wei Lin","orcid":"https://orcid.org/0000-0002-3869-6651"},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"W. Lin","raw_affiliation_strings":["Singapore Institute of Manufacturing Technology, Innovis, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Manufacturing Technology, Innovis, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101528762"],"corresponding_institution_ids":["https://openalex.org/I4210091207"],"apc_list":null,"apc_paid":null,"fwci":0.2862,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.59998001,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"536","last_page":"541"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5774394869804382},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5169965028762817},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5150694251060486},{"id":"https://openalex.org/keywords/characterization","display_name":"Characterization (materials science)","score":0.5106163620948792},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4993724822998047},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49623948335647583},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4761333763599396},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.45792871713638306},{"id":"https://openalex.org/keywords/planar","display_name":"Planar","score":0.4509267210960388},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.44912081956863403},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42631834745407104},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33359798789024353},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.20906206965446472},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.14609724283218384},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13633403182029724},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1030007004737854},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.10010945796966553}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5774394869804382},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5169965028762817},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5150694251060486},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.5106163620948792},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4993724822998047},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49623948335647583},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4761333763599396},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.45792871713638306},{"id":"https://openalex.org/C134786449","wikidata":"https://www.wikidata.org/wiki/Q3391255","display_name":"Planar","level":2,"score":0.4509267210960388},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.44912081956863403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42631834745407104},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33359798789024353},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.20906206965446472},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.14609724283218384},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13633403182029724},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1030007004737854},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.10010945796966553},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aim.2016.7576823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aim.2016.7576823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2037911143","https://openalex.org/W2060350027","https://openalex.org/W2062377817","https://openalex.org/W2076098952","https://openalex.org/W2084532715","https://openalex.org/W2094229830","https://openalex.org/W2099820337","https://openalex.org/W2123410556","https://openalex.org/W2127260386","https://openalex.org/W2138451308","https://openalex.org/W2145179397","https://openalex.org/W2160642098","https://openalex.org/W2165275822","https://openalex.org/W2322337930","https://openalex.org/W2474868255","https://openalex.org/W2894977557","https://openalex.org/W4247105055","https://openalex.org/W4285719527","https://openalex.org/W6720678532"],"related_works":["https://openalex.org/W4255837520","https://openalex.org/W4206327962","https://openalex.org/W2387011115","https://openalex.org/W2010009304","https://openalex.org/W4234808182","https://openalex.org/W2804364458","https://openalex.org/W4255628145","https://openalex.org/W2382043075","https://openalex.org/W1996851061","https://openalex.org/W2809151339"],"abstract_inverted_index":{"Automated":[0],"identification":[1],"and":[2,25,47,64,78,101,107],"characterization":[3],"of":[4,12,121],"clustered":[5,40,114],"weld":[6,41,98],"defects,":[7,17],"which":[8],"comprise":[9],"a":[10,95],"plural":[11],"closely":[13],"distributed":[14],"individual":[15,55,71,111,123],"member":[16,56,72,124],"is":[18,67,86,102],"challenging.":[19],"In":[20],"this":[21],"paper,":[22],"time,":[23],"Cartesian":[24],"Polar":[26],"domain":[27,52],"features":[28,120],"in":[29],"phased":[30],"array":[31],"ultrasonic":[32],"sectorial":[33],"scanning":[34,93],"data":[35,90],"are":[36,59,127],"studied":[37],"to":[38,74,79,88,104],"segment":[39],"defect":[42,57,73],"echoes":[43,58],"by":[44],"density":[45],"based":[46],"K-means":[48],"clustering.":[49],"Through":[50],"multiple":[51],"segmentation,":[53],"all":[54,109],"successfully":[60],"identified.":[61],"Then":[62],"size":[63],"depth":[65],"estimation":[66],"performed":[68],"on":[69,94,117],"each":[70,122],"describe":[75],"its":[76,81],"patterns":[77],"locate":[80],"depth.":[82],"The":[83],"developed":[84],"technique":[85],"applied":[87],"experimental":[89],"collected":[91],"from":[92],"tubular":[96],"T":[97],"test":[99],"sample":[100],"shown":[103],"discriminate,":[105],"locate,":[106],"measure":[108],"the":[110,118],"defects":[112],"inside":[113],"defects.":[115,135],"Based":[116],"geometrical":[119],"defect,":[125],"they":[126],"classified":[128],"as":[129],"either":[130],"point,":[131],"linear":[132],"or":[133],"planar":[134]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}