{"id":"https://openalex.org/W2010934470","doi":"https://doi.org/10.1109/fskd.2013.6816305","title":"Feature extraction of gearbox vibration signals based on EEMD and sample entropy","display_name":"Feature extraction of gearbox vibration signals based on EEMD and sample entropy","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2010934470","doi":"https://doi.org/10.1109/fskd.2013.6816305","mag":"2010934470"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2013.6816305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2013.6816305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","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/A5084710341","display_name":"Xiaoping Chen","orcid":"https://orcid.org/0000-0001-8992-9286"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoping Chen","raw_affiliation_strings":["School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China","School of Electrical & Information Engineering, Jiangsu University,Zhenjiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]},{"raw_affiliation_string":"School of Electrical & Information Engineering, Jiangsu University,Zhenjiang,China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101050077","display_name":"Chunfang Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunfang Yin","raw_affiliation_strings":["School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China","School of Electrical & Information Engineering, Jiangsu University,Zhenjiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]},{"raw_affiliation_string":"School of Electrical & Information Engineering, Jiangsu University,Zhenjiang,China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102210213","display_name":"HE Wei-xing","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixing He","raw_affiliation_strings":["School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China","School of Electrical & Information Engineering, Jiangsu University,Zhenjiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]},{"raw_affiliation_string":"School of Electrical & Information Engineering, Jiangsu University,Zhenjiang,China","institution_ids":["https://openalex.org/I115592961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I115592961"],"apc_list":null,"apc_paid":null,"fwci":0.936,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.67307578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"811","last_page":"815"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9976999759674072,"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":0.9976999759674072,"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":0.9585999846458435,"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/T14225","display_name":"Advanced Sensor and Control Systems","score":0.9552000164985657,"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/sample-entropy","display_name":"Sample entropy","score":0.8272307515144348},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6742079854011536},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.6585476398468018},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.6360377073287964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6119874715805054},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5522685050964355},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5427983999252319},{"id":"https://openalex.org/keywords/approximate-entropy","display_name":"Approximate entropy","score":0.5302764177322388},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47979456186294556},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.19687625765800476},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.12648749351501465}],"concepts":[{"id":"https://openalex.org/C66696666","wikidata":"https://www.wikidata.org/wiki/Q17105612","display_name":"Sample entropy","level":3,"score":0.8272307515144348},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6742079854011536},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.6585476398468018},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.6360377073287964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6119874715805054},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5522685050964355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5427983999252319},{"id":"https://openalex.org/C86859247","wikidata":"https://www.wikidata.org/wiki/Q4781760","display_name":"Approximate entropy","level":3,"score":0.5302764177322388},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47979456186294556},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.19687625765800476},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.12648749351501465},{"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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2013.6816305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2013.6816305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8999999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W163612977","https://openalex.org/W1862394037","https://openalex.org/W2007221293","https://openalex.org/W2120390927","https://openalex.org/W6606628390","https://openalex.org/W6677952202"],"related_works":["https://openalex.org/W2093589470","https://openalex.org/W2415751681","https://openalex.org/W1862394037","https://openalex.org/W2889925888","https://openalex.org/W3121271574","https://openalex.org/W2084594947","https://openalex.org/W4205160129","https://openalex.org/W2076258781","https://openalex.org/W2099197004","https://openalex.org/W2890995276"],"abstract_inverted_index":{"Gearbox":[0],"vibration":[1,52,133],"signals":[2,21,53,134],"are":[3],"non-stationary":[4],"and":[5,41,66,83,110,122,151],"nonlinear.":[6],"In":[7],"order":[8],"to":[9,44],"identify":[10],"different":[11,59],"working":[12],"conditions":[13],"of":[14,19,34,49,54,80,87,98,102,119,131,139,159],"the":[15,17,29,47,78,85,91,96,112,123,128,137,163],"gearbox,":[16],"eigenvalues":[18,48],"corresponding":[20,50],"should":[22],"be":[23],"extracted.":[24],"The":[25,71,117,142],"paper":[26],"proposed":[27],"for":[28,162],"first":[30],"time":[31],"a":[32,155],"method":[33,118,146],"combining":[35,120],"ensemble":[36],"empirical":[37],"mode":[38],"decomposition":[39],"(EEMD)":[40],"sample":[42,92,107,124],"entropy":[43,93,104,125],"extract":[45],"effectively":[46],"gearbox":[51,132],"wind":[55],"turbine":[56],"in":[57,105],"three":[58],"states,":[60],"namely":[61],"normal":[62],"gear,":[63],"worn":[64],"gear":[65,67],"with":[68],"broken":[69],"teeth.":[70],"results":[72],"showed":[73],"that":[74],"EEMD":[75,121],"could":[76,94,126],"overcome":[77],"problem":[79,97],"frequency":[81],"aliasing":[82],"had":[84],"advantage":[86],"strong":[88],"adaptability,":[89],"while":[90],"solve":[95],"lower":[99],"relative":[100],"consistency":[101],"approximate":[103],"small":[106],"data":[108],"processing,":[109],"improve":[111],"computing":[113],"speed":[114],"as":[115],"well.":[116],"show":[127],"status":[129],"characteristics":[130],"well":[135],"during":[136],"process":[138],"feature":[140,144],"extraction.":[141],"new":[143],"extraction":[145],"is":[147],"fast,":[148],"effective,":[149],"reliable,":[150],"it":[152],"can":[153],"provide":[154],"reliable":[156],"input":[157],"vector":[158],"characteristic":[160],"value":[161],"following":[164],"fault":[165],"classification.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
