{"id":"https://openalex.org/W2591591405","doi":"https://doi.org/10.3390/s17030549","title":"Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence","display_name":"Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence","publication_year":2017,"publication_date":"2017-03-09","ids":{"openalex":"https://openalex.org/W2591591405","doi":"https://doi.org/10.3390/s17030549","mag":"2591591405","pmid":"https://pubmed.ncbi.nlm.nih.gov/28282936"},"language":"en","primary_location":{"id":"doi:10.3390/s17030549","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s17030549","pdf_url":"https://www.mdpi.com/1424-8220/17/3/549/pdf?version=1489146617","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/1424-8220/17/3/549/pdf?version=1489146617","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100439301","display_name":"Ran Zhang","orcid":"https://orcid.org/0000-0002-9514-7253"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Zhang","raw_affiliation_strings":["Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","Beijing Engineering Research Center of High Reliable Embedded System, Capital Normal University, Beijing 100048, China","College of Information Engineering, Capital Normal University, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Beijing Engineering Research Center of High Reliable Embedded System, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"College of Information Engineering, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105024332","display_name":"Zhen Peng","orcid":"https://orcid.org/0000-0001-5639-5839"},"institutions":[{"id":"https://openalex.org/I130541836","display_name":"Beijing Institute of Petrochemical Technology","ror":"https://ror.org/025s55q11","country_code":"CN","type":"education","lineage":["https://openalex.org/I130541836"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Peng","raw_affiliation_strings":["Information Management Department, Beijing Institute of Petrochemical Technology, Beijing 102617, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Management Department, Beijing Institute of Petrochemical Technology, Beijing 102617, China","institution_ids":["https://openalex.org/I130541836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101892410","display_name":"Lifeng Wu","orcid":"https://orcid.org/0000-0002-5238-8823"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lifeng Wu","raw_affiliation_strings":["Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","Beijing Engineering Research Center of High Reliable Embedded System, Capital Normal University, Beijing 100048, China","College of Information Engineering, Capital Normal University, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Beijing Engineering Research Center of High Reliable Embedded System, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"College of Information Engineering, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034070359","display_name":"Beibei Yao","orcid":"https://orcid.org/0000-0001-8382-3042"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Beibei Yao","raw_affiliation_strings":["Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","Beijing Engineering Research Center of High Reliable Embedded System, Capital Normal University, Beijing 100048, China","College of Information Engineering, Capital Normal University, Beijing 100048, China"],"raw_orcid":"https://orcid.org/0000-0001-8382-3042","affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Beijing Engineering Research Center of High Reliable Embedded System, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"College of Information Engineering, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087366755","display_name":"Yong Guan","orcid":"https://orcid.org/0000-0002-2373-2779"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Guan","raw_affiliation_strings":["Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","Beijing Engineering Research Center of High Reliable Embedded System, Capital Normal University, Beijing 100048, China","College of Information Engineering, Capital Normal University, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Beijing Engineering Research Center of High Reliable Embedded System, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"College of Information Engineering, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101892410"],"corresponding_institution_ids":["https://openalex.org/I96852419"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":12.8546,"has_fulltext":false,"cited_by_count":133,"citation_normalized_percentile":{"value":0.99043087,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"17","issue":"3","first_page":"549","last_page":"549"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9987000226974487,"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":0.9987000226974487,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9957000017166138,"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":0.972100019454956,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6222385168075562},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.6037048101425171},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5853551030158997},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5567097663879395},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.5530086159706116},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5254946351051331},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5137754082679749},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5062636137008667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4751065671443939},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4288368821144104},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40284720063209534},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3082006275653839},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.11351287364959717}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6222385168075562},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.6037048101425171},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5853551030158997},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5567097663879395},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.5530086159706116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5254946351051331},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5137754082679749},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5062636137008667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4751065671443939},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4288368821144104},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40284720063209534},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3082006275653839},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.11351287364959717},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","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/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s17030549","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s17030549","pdf_url":"https://www.mdpi.com/1424-8220/17/3/549/pdf?version=1489146617","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:28282936","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28282936","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:f7044adcdfc6477b880059c679d3771f","is_oa":true,"landing_page_url":"https://doaj.org/article/f7044adcdfc6477b880059c679d3771f","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 3, p 549 (2017)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/17/3/549/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s17030549","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 3; Pages: 549","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:5375835","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5375835","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/s17030549","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s17030549","pdf_url":"https://www.mdpi.com/1424-8220/17/3/549/pdf?version=1489146617","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":[],"awards":[{"id":"https://openalex.org/G697953858","display_name":null,"funder_award_id":"No. 61202027","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/W2591591405.pdf"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1675477313","https://openalex.org/W1889820893","https://openalex.org/W1909255270","https://openalex.org/W2003205626","https://openalex.org/W2040070030","https://openalex.org/W2060099436","https://openalex.org/W2072378835","https://openalex.org/W2076462394","https://openalex.org/W2090055229","https://openalex.org/W2100495367","https://openalex.org/W2107434184","https://openalex.org/W2136922672","https://openalex.org/W2140833774","https://openalex.org/W2141188346","https://openalex.org/W2187740413","https://openalex.org/W2191588813","https://openalex.org/W2219903032","https://openalex.org/W2272183427","https://openalex.org/W2285970544","https://openalex.org/W2440930599","https://openalex.org/W2586090183","https://openalex.org/W6680887930","https://openalex.org/W6688510240"],"related_works":["https://openalex.org/W4252510819","https://openalex.org/W3012838233","https://openalex.org/W2363876787","https://openalex.org/W2605106030","https://openalex.org/W1982640233","https://openalex.org/W4388053854","https://openalex.org/W3034410548","https://openalex.org/W2980555063","https://openalex.org/W3036953692","https://openalex.org/W2366527604"],"abstract_inverted_index":{"Intelligent":[0],"condition":[1],"monitoring":[2],"and":[3,20,29,65,103],"fault":[4,18,55,81,161,188],"diagnosis":[5,19,56,82,162,189],"by":[6,124],"analyzing":[7],"the":[8,13,60,70,111,115,130,133,139,149,153,177,195],"sensor":[9,42,98],"data":[10,99,122,144,170],"can":[11,92,183],"assure":[12],"safety":[14],"of":[15,62,73,110,114,136,152,180,197],"machinery.":[16],"Conventional":[17],"classification":[21,150,178],"methods":[22],"usually":[23],"implement":[24],"pretreatments":[25],"to":[26,49,128,147],"decrease":[27],"noise":[28],"extract":[30],"some":[31,45],"time":[32,40,74,96,119,157,168],"domain":[33,36],"or":[34],"frequency":[35],"features":[37],"from":[38,59],"raw":[39,95,118],"series":[41,75,97,120,158,169],"data.":[43,76,116,159],"Then,":[44],"classifiers":[46],"are":[47,126,145],"utilized":[48],"make":[50],"diagnosis.":[51],"However,":[52],"these":[53],"conventional":[54],"approaches":[57],"suffer":[58],"expertise":[61],"feature":[63,101],"selection":[64,102],"they":[66],"do":[67],"not":[68],"consider":[69],"temporal":[71,112,164],"coherence":[72,113,165],"This":[77],"paper":[78],"proposes":[79],"a":[80],"model":[83,91],"based":[84],"on":[85,155],"Deep":[86],"Neural":[87],"Networks":[88],"(DNN).":[89],"The":[90,186],"directly":[93],"recognize":[94],"without":[100],"signal":[104],"processing.":[105],"It":[106],"also":[107],"takes":[108],"advantage":[109],"Firstly,":[117],"training":[121],"collected":[123],"sensors":[125],"used":[127,146],"train":[129],"DNN":[131,137,154],"until":[132],"cost":[134],"function":[135],"gets":[138],"minimal":[140],"value;":[141],"Secondly,":[142],"test":[143,148],"accuracy":[151,179],"local":[156],"Finally,":[160],"considering":[163],"with":[166],"former":[167],"is":[171,191],"implemented.":[172],"Experimental":[173],"results":[174],"show":[175],"that":[176],"bearing":[181,198],"faults":[182],"get":[184],"100%.":[185],"proposed":[187],"approach":[190],"effective":[192],"in":[193],"recognizing":[194],"type":[196],"faults.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":25},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":4}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}
