{"id":"https://openalex.org/W4226096052","doi":"https://doi.org/10.1177/1063293x211073714","title":"RETRACTED: Phased array ultrasonic test signal enhancement and classification using Empirical Wavelet Transform and Deep Convolution Neural Network","display_name":"RETRACTED: Phased array ultrasonic test signal enhancement and classification using Empirical Wavelet Transform and Deep Convolution Neural Network","publication_year":2022,"publication_date":"2022-02-22","ids":{"openalex":"https://openalex.org/W4226096052","doi":"https://doi.org/10.1177/1063293x211073714"},"language":"en","primary_location":{"id":"doi:10.1177/1063293x211073714","is_oa":false,"landing_page_url":"https://doi.org/10.1177/1063293x211073714","pdf_url":null,"source":{"id":"https://openalex.org/S25105827","display_name":"Concurrent Engineering","issn_l":"1063-293X","issn":["1063-293X","1531-2003"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Concurrent Engineering","raw_type":"journal-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/A5045283840","display_name":"F. V. Jayasudha","orcid":"https://orcid.org/0000-0003-2103-0893"},"institutions":[{"id":"https://openalex.org/I43814544","display_name":"Sathyabama Institute of Science and Technology","ror":"https://ror.org/01defpn95","country_code":"IN","type":"education","lineage":["https://openalex.org/I43814544"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Jayasudha JC","raw_affiliation_strings":["Faculty of Electronics, Sathyabama Institute of Science and Technology, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0003-2103-0893","affiliations":[{"raw_affiliation_string":"Faculty of Electronics, Sathyabama Institute of Science and Technology, Chennai, India","institution_ids":["https://openalex.org/I43814544"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037018835","display_name":"S. Lalithakumari","orcid":null},"institutions":[{"id":"https://openalex.org/I43814544","display_name":"Sathyabama Institute of Science and Technology","ror":"https://ror.org/01defpn95","country_code":"IN","type":"education","lineage":["https://openalex.org/I43814544"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Lalithakumari S","raw_affiliation_strings":["Department of EIE, Sathyabama Institute of Science and Technology, Chennai, India","Faculty of Electronics, Sathyabama Institute of Science and Technology, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of EIE, Sathyabama Institute of Science and Technology, Chennai, India","institution_ids":["https://openalex.org/I43814544"]},{"raw_affiliation_string":"Faculty of Electronics, Sathyabama Institute of Science and Technology, Chennai, India","institution_ids":["https://openalex.org/I43814544"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045283840"],"corresponding_institution_ids":["https://openalex.org/I43814544"],"apc_list":null,"apc_paid":null,"fwci":1.4455,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.77328127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"30","issue":"3","first_page":"229","last_page":"236"},"is_retracted":true,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":1.0,"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":1.0,"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":0.9990000128746033,"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/filter","display_name":"Filter (signal processing)","score":0.537559449672699},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5237343311309814},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.4920448958873749},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49052590131759644},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.47824493050575256},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4756338596343994},{"id":"https://openalex.org/keywords/nondestructive-testing","display_name":"Nondestructive testing","score":0.4704044461250305},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.46441003680229187},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4549838602542877},{"id":"https://openalex.org/keywords/ultrasonic-testing","display_name":"Ultrasonic testing","score":0.42842280864715576},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.4117048382759094},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37016692757606506},{"id":"https://openalex.org/keywords/ultrasonic-sensor","display_name":"Ultrasonic sensor","score":0.3320755362510681},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.27252456545829773},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.20578038692474365}],"concepts":[{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.537559449672699},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5237343311309814},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.4920448958873749},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49052590131759644},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.47824493050575256},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4756338596343994},{"id":"https://openalex.org/C56529433","wikidata":"https://www.wikidata.org/wiki/Q626700","display_name":"Nondestructive testing","level":2,"score":0.4704044461250305},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.46441003680229187},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4549838602542877},{"id":"https://openalex.org/C139730468","wikidata":"https://www.wikidata.org/wiki/Q1779355","display_name":"Ultrasonic testing","level":3,"score":0.42842280864715576},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4117048382759094},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37016692757606506},{"id":"https://openalex.org/C81288441","wikidata":"https://www.wikidata.org/wiki/Q20736125","display_name":"Ultrasonic sensor","level":2,"score":0.3320755362510681},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.27252456545829773},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.20578038692474365},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/1063293x211073714","is_oa":false,"landing_page_url":"https://doi.org/10.1177/1063293x211073714","pdf_url":null,"source":{"id":"https://openalex.org/S25105827","display_name":"Concurrent Engineering","issn_l":"1063-293X","issn":["1063-293X","1531-2003"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Concurrent Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2002960468","https://openalex.org/W2109701261","https://openalex.org/W2418691539","https://openalex.org/W2434005075","https://openalex.org/W2792741217","https://openalex.org/W2794380976","https://openalex.org/W2796202593","https://openalex.org/W2998927846","https://openalex.org/W3036250038","https://openalex.org/W3176488901","https://openalex.org/W3179502743"],"related_works":["https://openalex.org/W2348223506","https://openalex.org/W2767051368","https://openalex.org/W890166521","https://openalex.org/W2101807102","https://openalex.org/W2082653230","https://openalex.org/W2465306490","https://openalex.org/W2955340206","https://openalex.org/W2352912787","https://openalex.org/W2392374476","https://openalex.org/W4235889335"],"abstract_inverted_index":{"In":[0,69,93,187],"the":[1,9,21,38,89,94,97,111,120,150,181,188,216,223,227,242,260,278],"recent":[2],"past,":[3],"Non-Destructive":[4],"Testing":[5],"(NDT)":[6],"has":[7],"become":[8],"most":[10],"popular":[11],"technique":[12],"due":[13],"to":[14,87,135,139,175,202,246],"its":[15,25],"efficiency":[16],"and":[17,23,28,33,56,67,108,143,161,194,272,292,300],"accuracy":[18],"without":[19],"destroying":[20],"object":[22],"maintaining":[24],"original":[26],"structure":[27],"gathering":[29],"while":[30],"examining":[31],"external":[32],"internal":[34],"welding":[35,100,243,285],"defects.":[36],"Generally,":[37],"NDT":[39,62,86],"environment":[40],"is":[41,44,75,102,133,149,169,213,233,249,257,288],"harmful":[42],"which":[43,116],"distinguished":[45],"by":[46,179,297],"huge":[47],"volatile":[48],"fields":[49],"of":[50,152,218,262,264,266],"electromagnetic,":[51],"elevated":[52,57],"radiation":[53],"emission":[54],"instability,":[55],"heat.":[58],"Therefore,":[59],"a":[60,72,79,172],"suitable":[61],"approach":[63],"could":[64],"be":[65],"recognized":[66],"practiced.":[68],"this":[70],"paper,":[71],"novel":[73],"algorithm":[74],"proposed":[76,95,134,214,279],"based":[77],"on":[78,222],"Phased":[80],"array":[81],"ultrasonic":[82],"test":[83,91],"(PAUT)":[84],"for":[85,206,215,235,259,281,284],"attain":[88],"proper":[90],"attributes.":[92],"methodology,":[96],"carbon":[98],"steel":[99],"section":[101],"synthetically":[103],"produced":[104],"with":[105],"various":[106,204],"defects":[107],"tested":[109],"using":[110],"PAUT":[112,121,137,167,219,224,282],"method.":[113],"The":[114,126,146,165,209,238,253,274],"signals":[115],"are":[117,123,200],"acquired":[118],"from":[119],"device":[122],"having":[124],"noise.":[125,145],"Adaptive":[127],"Least":[128],"Mean":[129],"Square":[130],"(ALMS)":[131],"filter":[132,136,148,155,159,163],"signal":[138,168,174,225,244],"eliminate":[140],"random":[141],"noise":[142],"Gaussian":[144],"ALMS":[147],"combination":[151],"low":[153],"pass":[154,158],"(LPF),":[156],"high":[157],"(HPF),":[160],"bandpass":[162],"(BPF).":[164],"time-domain":[166],"converted":[170],"into":[171],"frequency-domain":[173],"extract":[176,203],"more":[177,290],"features":[178,197,205],"applying":[180],"Empirical":[182],"Wavelet":[183],"Transform":[184],"(EWT)":[185],"algorithm.":[186],"frequency":[189],"domain":[190],"signal,":[191],"first":[192],"order":[193,196],"second":[195],"extraction":[198],"techniques":[199],"applied":[201,234],"further":[207,236],"classification.":[208,237],"Deep":[210,228],"Learning":[211],"methodology":[212,280],"classification":[217,267,287],"signals.":[220],"Based":[221],"features,":[226],"Convolution":[229],"Neural":[230],"Network":[231],"(DCNN)":[232],"DCNN":[239],"will":[240],"classify":[241],"as":[245,268],"whether":[247],"it":[248],"defective":[250],"or":[251],"non-defective.":[252],"Confusion":[254],"Matrix":[255],"(CM)":[256],"used":[258],"estimation":[261],"measurement":[263],"performance":[265],"calculating":[269],"accuracy,":[270],"sensitivity,":[271],"specificity.":[273],"experiments":[275],"prove":[276],"that":[277],"testing":[283],"defect":[286],"obtained":[289],"accurately":[291],"efficiently":[293],"across":[294],"existing":[295],"methodologies":[296],"providing":[298],"numerical":[299],"graphical":[301],"results.":[302]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-05-05T00:00:00"}