{"id":"https://openalex.org/W2781587800","doi":"https://doi.org/10.1109/tim.2017.2777619","title":"Convolutional Sparse Learning for Blind Deconvolution and Application on Impulsive Feature Detection","display_name":"Convolutional Sparse Learning for Blind Deconvolution and Application on Impulsive Feature Detection","publication_year":2018,"publication_date":"2018-01-04","ids":{"openalex":"https://openalex.org/W2781587800","doi":"https://doi.org/10.1109/tim.2017.2777619","mag":"2781587800"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2017.2777619","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2017.2777619","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","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/A5000845394","display_name":"Zhaohui Du","orcid":"https://orcid.org/0000-0002-6736-4373"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhaohui Du","raw_affiliation_strings":["State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0002-6736-4373","affiliations":[{"raw_affiliation_string":"State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114139896","display_name":"Xuefeng Chen","orcid":"https://orcid.org/0009-0009-2373-8757"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Chen","raw_affiliation_strings":["State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0001-9963-7092","affiliations":[{"raw_affiliation_string":"State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100399366","display_name":"Han Zhang","orcid":"https://orcid.org/0000-0003-2253-8605"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Zhang","raw_affiliation_strings":["State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000845394"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":3.1468,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.92610196,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"67","issue":"2","first_page":"338","last_page":"349"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/deconvolution","display_name":"Deconvolution","score":0.678013265132904},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6088804602622986},{"id":"https://openalex.org/keywords/blind-deconvolution","display_name":"Blind deconvolution","score":0.5660749673843384},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.4920806288719177},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4850015342235565},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4831475615501404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4007207453250885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3265320658683777}],"concepts":[{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.678013265132904},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6088804602622986},{"id":"https://openalex.org/C30044814","wikidata":"https://www.wikidata.org/wiki/Q11334452","display_name":"Blind deconvolution","level":3,"score":0.5660749673843384},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.4920806288719177},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4850015342235565},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4831475615501404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4007207453250885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3265320658683777},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2017.2777619","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2017.2777619","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G2320743339","display_name":null,"funder_award_id":"51421004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5421506396","display_name":null,"funder_award_id":"51605365","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W427289305","https://openalex.org/W1562101002","https://openalex.org/W1591714781","https://openalex.org/W1946620893","https://openalex.org/W1971521993","https://openalex.org/W1981766787","https://openalex.org/W2019024593","https://openalex.org/W2033777252","https://openalex.org/W2056700360","https://openalex.org/W2066458068","https://openalex.org/W2106290330","https://openalex.org/W2164278908","https://openalex.org/W2174317074","https://openalex.org/W2190662802","https://openalex.org/W2216139520","https://openalex.org/W2325453973","https://openalex.org/W2354630311","https://openalex.org/W2437984376","https://openalex.org/W2507952184","https://openalex.org/W2518759730","https://openalex.org/W2521893785","https://openalex.org/W2530780582","https://openalex.org/W2555910166","https://openalex.org/W2558698691","https://openalex.org/W2585519949","https://openalex.org/W2595459642","https://openalex.org/W2599672124","https://openalex.org/W2962853966","https://openalex.org/W3080864541","https://openalex.org/W4292363360","https://openalex.org/W6688447623","https://openalex.org/W6781683108"],"related_works":["https://openalex.org/W2023738877","https://openalex.org/W1914708705","https://openalex.org/W2059639161","https://openalex.org/W2058895457","https://openalex.org/W1538056422","https://openalex.org/W2586325539","https://openalex.org/W2147401053","https://openalex.org/W2589098082","https://openalex.org/W2029084792","https://openalex.org/W2139898842"],"abstract_inverted_index":{"The":[0,58],"mechanical":[1],"structure":[2,99],"or":[3],"transmission":[4,36,67],"path":[5,37,68],"between":[6],"fault":[7],"source":[8],"and":[9,32,69,146,171],"sensor":[10],"location":[11],"always":[12],"distorts":[13],"the":[14,28,33,40,62,66,74,88,92,97,101,107,111,115,144,149,157,175,178,183,188,198,202],"impulsive":[15,30,55,102,199],"signatures":[16],"of":[17,35,65,91,100,110,138,148,177,201],"machine":[18],"faults.":[19],"It":[20],"is":[21,51,70,104,128,191],"thus":[22],"an":[23],"important":[24],"task":[25],"to":[26,53,86,141],"estimate":[27],"desired":[29],"feature":[31,56,103],"influence":[34],"simultaneously":[38],"from":[39,73,114],"noisy":[41],"observation":[42],"signals.":[43],"Therefore,":[44],"a":[45,120,132,163],"convolutional":[46],"sparse":[47,98],"learning":[48],"model":[49],"(ConvSLM)":[50],"proposed":[52],"perform":[54],"detection.":[57],"ConvSLM":[59],"directly":[60],"models":[61],"modulation":[63],"process":[64],"completely":[71],"different":[72],"indirect":[75],"inverse":[76],"filter":[77],"design":[78],"scheme":[79],"as":[80],"popular":[81,93],"deconvolution":[82,186],"techniques":[83],"adopted.":[84],"Meanwhile,":[85],"overcome":[87],"inherent":[89],"drawbacks":[90],"Kurtosis":[94],"maximization":[95],"strategy,":[96],"integrated":[105],"into":[106],"objective":[108,151],"function":[109],"ConvSLM.":[112],"Different":[113],"recently":[116],"developed":[117,130],"two-stage":[118],"solver,":[119],"new":[121],"iterative":[122],"algorithm":[123],"with":[124,143,182],"only":[125,155],"one":[126],"stage":[127],"also":[129,161],"under":[131],"multiple-block":[133],"nonconvex":[134],"alternating":[135],"direction":[136],"method":[137],"multiplier":[139],"framework":[140],"cope":[142],"nonconvexity":[145],"nonsmoothness":[147],"sparsity-regularized":[150],"function,":[152],"which":[153],"not":[154],"reduces":[156],"algorithmic":[158],"complexity":[159],"but":[160],"has":[162],"convergence":[164],"guarantee.":[165],"Numerical":[166],"experiments":[167],"on":[168,197],"synthetic":[169],"data":[170],"test":[172],"results":[173],"corroborate":[174],"efficacy":[176],"advocated":[179],"approach.":[180],"Compared":[181],"state-of-the-art":[184],"blind":[185],"techniques,":[187],"ConvSLM's":[189],"superiority":[190],"sufficiently":[192],"verified":[193],"through":[194],"its":[195],"application":[196],"detection":[200],"wind":[203],"turbine":[204],"gearbox":[205],"gear.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}