{"id":"https://openalex.org/W2976320596","doi":"https://doi.org/10.1109/access.2019.2943381","title":"AESGRU: An Attention-Based Temporal Correlation Approach for End-to-End Machine Health Perception","display_name":"AESGRU: An Attention-Based Temporal Correlation Approach for End-to-End Machine Health Perception","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2976320596","doi":"https://doi.org/10.1109/access.2019.2943381","mag":"2976320596"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2943381","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2019.2943381","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101707934","display_name":"Weiting Zhang","orcid":"https://orcid.org/0000-0002-7473-2234"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"funder","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiting Zhang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071654735","display_name":"Dong Yang","orcid":"https://orcid.org/0000-0003-3402-3668"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"funder","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Yang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648099","display_name":"Hongchao Wang","orcid":"https://orcid.org/0000-0001-7905-2513"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"funder","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongchao Wang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020220195","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0003-3232-5195"},"institutions":[],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["Beijing Sheenline Technology Company Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Sheenline Technology Company Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004012289","display_name":"Mikael Gidlund","orcid":"https://orcid.org/0000-0003-0873-7827"},"institutions":[{"id":"https://openalex.org/I56475706","display_name":"Mid Sweden University","ror":"https://ror.org/019k1pd13","country_code":"SE","type":"funder","lineage":["https://openalex.org/I56475706"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Mikael Gidlund","raw_affiliation_strings":["Information and Communication Systems, Mid Sweden University, Sundsvall, Sweden"],"affiliations":[{"raw_affiliation_string":"Information and Communication Systems, Mid Sweden University, Sundsvall, Sweden","institution_ids":["https://openalex.org/I56475706"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.541,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":5,"citation_normalized_percentile":{"value":0.684495,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":79,"max":80},"biblio":{"volume":"7","issue":null,"first_page":"141487","last_page":"141497"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9956,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9956,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9711,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9486,"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/end-to-end-principle","display_name":"End-to-end principle","score":0.78718114},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5195923},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5140234},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature Engineering","score":0.45429626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8038312},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.78718114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6646351},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.555516},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5515369},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5195923},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.51608485},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5140234},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.49458858},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4626217},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.45429626},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44446564},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.44260475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43039352},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.42100286},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.41254425},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37714544},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25978476},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2943381","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-37398","pdf_url":"https://miun.diva-portal.org/smash/get/diva2:1355188/FULLTEXT01","source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2943381","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61771040"},{"funder":"https://openalex.org/F4320321392","funder_display_name":"Northwestern Polytechnical University","award_id":"2018YJS013"},{"funder":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China","award_id":"2018YFB1702001"}],"datasets":[],"versions":[],"referenced_works_count":32,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1598796236","https://openalex.org/W1967352108","https://openalex.org/W1999393241","https://openalex.org/W2033800551","https://openalex.org/W2064675550","https://openalex.org/W2076063813","https://openalex.org/W2131774270","https://openalex.org/W2133564696","https://openalex.org/W2157331557","https://openalex.org/W2219903032","https://openalex.org/W2317595875","https://openalex.org/W2341973567","https://openalex.org/W2470673105","https://openalex.org/W2513477101","https://openalex.org/W2545804724","https://openalex.org/W2558869916","https://openalex.org/W2564947831","https://openalex.org/W2580840020","https://openalex.org/W2587696068","https://openalex.org/W2591591405","https://openalex.org/W2628062541","https://openalex.org/W2736470268","https://openalex.org/W2740570963","https://openalex.org/W2749487223","https://openalex.org/W2761862788","https://openalex.org/W2793273050","https://openalex.org/W2801420905","https://openalex.org/W2925209208","https://openalex.org/W2944364052","https://openalex.org/W3105875582","https://openalex.org/W4298168912"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4211085505","https://openalex.org/W3179968364","https://openalex.org/W3034267371","https://openalex.org/W2968295315","https://openalex.org/W2938107654","https://openalex.org/W2154771632","https://openalex.org/W2151749779","https://openalex.org/W2067317451","https://openalex.org/W1999612375"],"abstract_inverted_index":{"Accurate":[0],"and":[1,71,86,137],"real-time":[2],"perception":[3],"of":[4,8,16,20,43,79,134,161],"the":[5,40,94,105,111,131,153,162],"operating":[6],"status":[7],"rolling":[9],"bearings,":[10],"which":[11,123],"constitute":[12],"a":[13,55,118],"key":[14],"component":[15],"rotating":[17],"machinery,":[18],"is":[19,124],"vital":[21],"significance.":[22],"However,":[23],"most":[24],"existing":[25],"solutions":[26],"not":[27],"only":[28],"require":[29],"substantial":[30],"expertise":[31],"to":[32,48,67,129],"conduct":[33],"feature":[34],"engineering,":[35],"but":[36],"also":[37],"seldom":[38],"consider":[39],"temporal":[41,101],"correlation":[42],"sensor":[44,135],"sequences,":[45],"ultimately":[46],"leading":[47],"complex":[49],"modeling":[50],"processes.":[51],"Therefore,":[52],"we":[53,116],"present":[54],"novel":[56],"model,":[57],"named":[58],"Attention-based":[59],"Equitable":[60],"Segmentation":[61],"Gated":[62],"Recurrent":[63],"Unit":[64],"Networks":[65],"(AESGRU),":[66],"improve":[68],"diagnostic":[69],"accuracy":[70],"model-building":[72],"efficiency.":[73],"Specifically,":[74],"our":[75,148],"proposed":[76,154],"AESGRU":[77],"consists":[78],"two":[80],"modules,":[81],"an":[82,87],"equitable":[83],"segmentation":[84],"approach":[85,155],"improved":[88],"deep":[89],"model.":[90],"We":[91],"first":[92],"transform":[93],"original":[95],"dataset":[96],"into":[97],"time-series":[98],"segments":[99,136],"with":[100],"correlation,":[102],"so":[103],"that":[104,152],"model":[106],"enables":[107],"end-to-end":[108],"learning":[109],"from":[110],"strongly":[112],"correlated":[113],"data.":[114],"Then,":[115],"deploy":[117],"single-layer":[119],"bidirectional":[120],"GRU":[121],"network,":[122],"enhanced":[125],"by":[126],"attention":[127,140],"mechanism,":[128],"capture":[130],"long-term":[132],"dependency":[133],"focus":[138],"limited":[139],"resources":[141],"on":[142],"those":[143],"informative":[144],"sampling":[145],"points.":[146],"Finally,":[147],"experimental":[149],"results":[150],"show":[151],"outperforms":[156],"previous":[157],"approaches":[158],"in":[159],"terms":[160],"accuracy.":[163]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2976320596","counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-04-15T20:21:24.341027","created_date":"2019-10-03"}