{"id":"https://openalex.org/W2589171657","doi":"https://doi.org/10.3390/s17020414","title":"An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox","display_name":"An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox","publication_year":2017,"publication_date":"2017-02-21","ids":{"openalex":"https://openalex.org/W2589171657","doi":"https://doi.org/10.3390/s17020414","mag":"2589171657","pmid":"https://pubmed.ncbi.nlm.nih.gov/28230767"},"language":"en","primary_location":{"id":"doi:10.3390/s17020414","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s17020414","pdf_url":"https://www.mdpi.com/1424-8220/17/2/414/pdf?version=1487659541","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/17/2/414/pdf?version=1487659541","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028967243","display_name":"Lu Jing","orcid":"https://orcid.org/0000-0002-4316-4879"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luyang Jing","raw_affiliation_strings":["School of Mechanical Engineering, Tianjin University, Tianjin 300354, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tianjin University, Tianjin 300354, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Taiyong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Taiyong Wang","raw_affiliation_strings":["School of Mechanical Engineering, Tianjin University, Tianjin 300354, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tianjin University, Tianjin 300354, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078956553","display_name":"Ming Zhao","orcid":"https://orcid.org/0000-0001-5989-5580"},"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":"Ming Zhao","raw_affiliation_strings":["School of Mechanical Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China","School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China"],"raw_orcid":"https://orcid.org/0000-0001-5989-5580","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100395912","display_name":"Peng Wang","orcid":"https://orcid.org/0000-0001-6467-1581"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Wang","raw_affiliation_strings":["School of Mechanical Engineering, Tianjin University, Tianjin 300354, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tianjin University, Tianjin 300354, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":25.0239,"has_fulltext":false,"cited_by_count":377,"citation_normalized_percentile":{"value":0.99861189,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"17","issue":"2","first_page":"414","last_page":"414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9923999905586243,"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"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.974399983882904,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6795507669448853},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6270542144775391},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6194382309913635},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6040221452713013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.581417977809906},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5401254296302795},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5246149301528931},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5171108245849609},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4770314395427704},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4570889174938202},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4370175898075104},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.42202699184417725},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34605708718299866},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34116053581237793},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2586979866027832}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6795507669448853},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6270542144775391},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6194382309913635},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6040221452713013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.581417977809906},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5401254296302795},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5246149301528931},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5171108245849609},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4770314395427704},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4570889174938202},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4370175898075104},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.42202699184417725},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34605708718299866},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34116053581237793},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2586979866027832},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s17020414","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s17020414","pdf_url":"https://www.mdpi.com/1424-8220/17/2/414/pdf?version=1487659541","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:28230767","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28230767","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:f6ddbe4197564c1fa07e086e32bee771","is_oa":true,"landing_page_url":"https://doaj.org/article/f6ddbe4197564c1fa07e086e32bee771","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 17, Iss 2, p 414 (2017)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/17/2/414/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s17020414","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 17; Issue 2; Pages: 414","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:5335931","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5335931","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s17020414","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s17020414","pdf_url":"https://www.mdpi.com/1424-8220/17/2/414/pdf?version=1487659541","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6200000047683716}],"awards":[{"id":"https://openalex.org/G251610480","display_name":null,"funder_award_id":"51475324","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":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2589171657.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1951577346","https://openalex.org/W1976062869","https://openalex.org/W1983364832","https://openalex.org/W2012193335","https://openalex.org/W2028549589","https://openalex.org/W2030644162","https://openalex.org/W2038420319","https://openalex.org/W2048076701","https://openalex.org/W2049550263","https://openalex.org/W2065431367","https://openalex.org/W2070461430","https://openalex.org/W2072137555","https://openalex.org/W2076063813","https://openalex.org/W2084919742","https://openalex.org/W2100187942","https://openalex.org/W2102605133","https://openalex.org/W2126584714","https://openalex.org/W2132241724","https://openalex.org/W2145339207","https://openalex.org/W2158449659","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2167251835","https://openalex.org/W2167324070","https://openalex.org/W2169805405","https://openalex.org/W2183341477","https://openalex.org/W2188183693","https://openalex.org/W2219903032","https://openalex.org/W2286961399","https://openalex.org/W2287029277","https://openalex.org/W2317595875","https://openalex.org/W2324044936","https://openalex.org/W2329322811","https://openalex.org/W2404692435","https://openalex.org/W2440930599","https://openalex.org/W2461729787","https://openalex.org/W2480364715","https://openalex.org/W2482991831","https://openalex.org/W2485614840","https://openalex.org/W2556345765","https://openalex.org/W2580840020","https://openalex.org/W2919115771","https://openalex.org/W4231109964","https://openalex.org/W6676179485","https://openalex.org/W6679144490","https://openalex.org/W6684191040","https://openalex.org/W6702031711"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W2530420969","https://openalex.org/W2051187167","https://openalex.org/W1980100242"],"abstract_inverted_index":{"A":[0],"fault":[1,66,104,130],"diagnosis":[2,67,131,195],"approach":[3,25],"based":[4,96],"on":[5,97],"multi-sensor":[6,92],"data":[7,41,93,114],"fusion":[8,49,61,94,121,147],"is":[9,52,136,181],"a":[10,47,64,117,139,162],"promising":[11],"tool":[12],"to":[13,55,124,183],"deal":[14],"with":[15,192],"complicated":[16],"damage":[17],"detection":[18],"problems":[19],"of":[20,39,46,119,128,187],"mechanical":[21],"systems.":[22],"Nevertheless,":[23],"this":[24],"suffers":[26],"from":[27,36,112],"two":[28,86,153],"challenges,":[29,87],"which":[30],"are":[31,76,167],"(1)":[32],"the":[33,44,126,172,178,185,188,193,202],"feature":[34,59],"extraction":[35],"various":[37],"types":[38],"sensory":[40,150],"and":[42,69,73,115,152,161],"(2)":[43],"selection":[45],"suitable":[48],"level.":[50],"It":[51],"usually":[53],"difficult":[54],"choose":[56],"an":[57,90],"optimal":[58],"or":[60],"level":[62],"for":[63,103],"specific":[65],"task,":[68],"extensive":[70],"domain":[71],"expertise":[72],"human":[74],"labor":[75],"also":[77],"highly":[78],"required":[79],"during":[80],"these":[81,85],"selections.":[82],"To":[83],"address":[84],"we":[88],"propose":[89],"adaptive":[91],"method":[95,108,135,180],"deep":[98],"convolutional":[99],"neural":[100,158],"networks":[101,159],"(DCNN)":[102],"diagnosis.":[105],"The":[106,133,174],"proposed":[107,134,179],"can":[109],"learn":[110],"features":[111],"raw":[113],"optimize":[116],"combination":[118],"different":[120],"levels":[122],"adaptively":[123],"satisfy":[125],"requirements":[127],"any":[129],"task.":[132],"tested":[137],"through":[138],"planetary":[140,189],"gearbox":[141,190],"test":[142],"rig.":[143],"Handcraft":[144],"features,":[145],"manual-selected":[146],"levels,":[148],"single":[149],"data,":[151],"traditional":[154],"intelligent":[155],"models,":[156],"back-propagation":[157],"(BPNN)":[160],"support":[163],"vector":[164],"machine":[165],"(SVM),":[166],"used":[168],"as":[169],"comparisons":[170],"in":[171,201],"experiment.":[173,203],"results":[175],"demonstrate":[176],"that":[177],"able":[182],"detect":[184],"conditions":[186],"effectively":[191],"best":[194],"accuracy":[196],"among":[197],"all":[198],"comparative":[199],"methods":[200]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":36},{"year":2023,"cited_by_count":42},{"year":2022,"cited_by_count":53},{"year":2021,"cited_by_count":48},{"year":2020,"cited_by_count":60},{"year":2019,"cited_by_count":69},{"year":2018,"cited_by_count":27},{"year":2017,"cited_by_count":4},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}
