{"id":"https://openalex.org/W2775117058","doi":"https://doi.org/10.1109/iecon.2017.8217235","title":"A dirty data recognition method for machinery condition monitoring in big data era","display_name":"A dirty data recognition method for machinery condition monitoring in big data era","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2775117058","doi":"https://doi.org/10.1109/iecon.2017.8217235","mag":"2775117058"},"language":"en","primary_location":{"id":"doi:10.1109/iecon.2017.8217235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon.2017.8217235","pdf_url":null,"source":{"id":"https://openalex.org/S4363608531","display_name":"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"},"type":"conference-paper","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/A5008554873","display_name":"Yaguo Lei","orcid":"https://orcid.org/0000-0002-5167-1459"},"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":"Yaguo Lei","raw_affiliation_strings":["Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","Key Laboratory of Education, Ministry for Modern Design and Rotor-Bearing System, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Key Laboratory of Education, Ministry for Modern Design and Rotor-Bearing System, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076859183","display_name":"Xin Zhou","orcid":"https://orcid.org/0000-0003-2814-3399"},"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":"Xin Zhou","raw_affiliation_strings":["Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","Key Laboratory of Education, Ministry for Modern Design and Rotor-Bearing System, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Key Laboratory of Education, Ministry for Modern Design and Rotor-Bearing System, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005909676","display_name":"Xuefang Xu","orcid":"https://orcid.org/0000-0002-3861-8733"},"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":"Xuefang Xu","raw_affiliation_strings":["Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","Key Laboratory of Education, Ministry for Modern Design and Rotor-Bearing System, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Key Laboratory of Education, Ministry for Modern Design and Rotor-Bearing System, 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/A5081893651","display_name":"Feng Jia","orcid":"https://orcid.org/0000-0001-8467-4413"},"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":"Feng Jia","raw_affiliation_strings":["Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","Key Laboratory of Education, Ministry for Modern Design and Rotor-Bearing System, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Key Laboratory of Education, Ministry for Modern Design and Rotor-Bearing System, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7061","last_page":"7066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.992900013923645,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.992900013923645,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9804999828338623,"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":0.9764000177383423,"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/outlier","display_name":"Outlier","score":0.7166980504989624},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6190939545631409},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6163057088851929},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5574378371238708},{"id":"https://openalex.org/keywords/autoregressive-conditional-heteroskedasticity","display_name":"Autoregressive conditional heteroskedasticity","score":0.5474668741226196},{"id":"https://openalex.org/keywords/heteroscedasticity","display_name":"Heteroscedasticity","score":0.5288206934928894},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.49779677391052246},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4853042960166931},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47355902194976807},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46521973609924316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4499899744987488},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43225765228271484},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.4249744713306427},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.234975665807724},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.20533838868141174},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17516198754310608}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7166980504989624},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6190939545631409},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6163057088851929},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5574378371238708},{"id":"https://openalex.org/C23922673","wikidata":"https://www.wikidata.org/wiki/Q180752","display_name":"Autoregressive conditional heteroskedasticity","level":3,"score":0.5474668741226196},{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.5288206934928894},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.49779677391052246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4853042960166931},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47355902194976807},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46521973609924316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4499899744987488},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43225765228271484},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.4249744713306427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.234975665807724},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.20533838868141174},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17516198754310608},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon.2017.8217235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon.2017.8217235","pdf_url":null,"source":{"id":"https://openalex.org/S4363608531","display_name":"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1979575715","https://openalex.org/W1999996900","https://openalex.org/W2026493302","https://openalex.org/W2101549186","https://openalex.org/W2122646361","https://openalex.org/W2134490011","https://openalex.org/W2140585983","https://openalex.org/W2140971281","https://openalex.org/W2219903032","https://openalex.org/W2317595875","https://openalex.org/W2395916081","https://openalex.org/W2406935090","https://openalex.org/W2591055632","https://openalex.org/W2738563279","https://openalex.org/W6842158552"],"related_works":["https://openalex.org/W1676609285","https://openalex.org/W3148934225","https://openalex.org/W1608601224","https://openalex.org/W2051923604","https://openalex.org/W2017138702","https://openalex.org/W1978494725","https://openalex.org/W2776656900","https://openalex.org/W2031589205","https://openalex.org/W3125539950","https://openalex.org/W3029813487"],"abstract_inverted_index":{"Condition":[0],"monitoring":[1,33],"of":[2,13,19,131,148],"machinery":[3,32],"has":[4],"entered":[5],"the":[6,11,17,20,27,55,61,65,68,72,79,83,98,103,111,116,123,129,146,149],"big":[7],"data":[8,15,29,57],"era,":[9],"while":[10],"existence":[12],"dirty":[14,28,56,124],"reduces":[16],"quality":[18],"whole":[21],"data.":[22,125],"In":[23],"order":[24],"to":[25,53,77,96,121],"recognize":[26,122],"included":[30],"in":[31,40],"data,":[34],"a":[35,44,138],"new":[36],"method":[37,134],"is":[38,51,94,119],"proposed":[39,133,150],"this":[41,132],"paper.":[42],"First,":[43],"feature":[45,80,84,99],"named":[46],"sampled":[47],"power":[48],"index":[49],"(SPI)":[50],"designed":[52],"transform":[54,74],"recognition":[58],"issue":[59],"into":[60],"outlier":[62],"recognition.":[63],"Then":[64],"windowing":[66],"technique,":[67],"difference":[69],"operation":[70],"and":[71,82,101,107,115,128,140],"logarithm":[73],"are":[75,113,135],"introduced":[76],"reduce":[78],"tendency":[81],"volatility.":[85],"Next,":[86],"auto":[87],"regression-generalized":[88],"autoregressive":[89],"conditional":[90],"heteroskedasticity":[91],"(AR-GARCH)":[92],"model":[93],"applied":[95,120],"regress":[97],"series":[100],"produce":[102],"crippled":[104],"local":[105,108],"means":[106],"volatilities.":[109],"Finally,":[110],"features":[112],"normalized":[114],"3\u03c3":[117],"criterion":[118],"The":[126,143],"performance":[127],"feasibility":[130],"evaluated":[136],"by":[137],"simulation":[139],"an":[141],"experiment.":[142],"results":[144],"validate":[145],"effectiveness":[147],"method.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
