{"id":"https://openalex.org/W4403060754","doi":"https://doi.org/10.1109/iotaai62601.2024.10692468","title":"Prediction and Degradation Analysis Revolutionizing Electric Vehicle Reducer Prognostics: An Advanced Deep Learning Framework for Accurate RUL Prediction and Degradation Analysis","display_name":"Prediction and Degradation Analysis Revolutionizing Electric Vehicle Reducer Prognostics: An Advanced Deep Learning Framework for Accurate RUL Prediction and Degradation Analysis","publication_year":2024,"publication_date":"2024-07-26","ids":{"openalex":"https://openalex.org/W4403060754","doi":"https://doi.org/10.1109/iotaai62601.2024.10692468"},"language":"en","primary_location":{"id":"doi:10.1109/iotaai62601.2024.10692468","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iotaai62601.2024.10692468","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 6th International Conference on Internet of Things, Automation and Artificial Intelligence (IoTAAI)","raw_type":"proceedings-article"},"type":"article","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/A5100690568","display_name":"Weilin Li","orcid":"https://orcid.org/0000-0002-9864-3594"},"institutions":[{"id":"https://openalex.org/I4210132615","display_name":"Zhejiang Energy Group (China)","ror":"https://ror.org/03a2tkf74","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132615"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weilin Li","raw_affiliation_strings":["LTD,Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation, Zhejiang Fangyuan Test Group Co.,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"LTD,Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation, Zhejiang Fangyuan Test Group Co.,Hangzhou,China","institution_ids":["https://openalex.org/I4210132615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079324557","display_name":"Zhongjie Zhang","orcid":"https://orcid.org/0000-0002-9615-0518"},"institutions":[{"id":"https://openalex.org/I4210132615","display_name":"Zhejiang Energy Group (China)","ror":"https://ror.org/03a2tkf74","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongjie Zhang","raw_affiliation_strings":["LTD,Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation, Zhejiang Fangyuan Test Group Co.,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"LTD,Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation, Zhejiang Fangyuan Test Group Co.,Hangzhou,China","institution_ids":["https://openalex.org/I4210132615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003734692","display_name":"Yangming Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132615","display_name":"Zhejiang Energy Group (China)","ror":"https://ror.org/03a2tkf74","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangming Jiang","raw_affiliation_strings":["LTD,Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation, Zhejiang Fangyuan Test Group Co.,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"LTD,Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation, Zhejiang Fangyuan Test Group Co.,Hangzhou,China","institution_ids":["https://openalex.org/I4210132615"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002265025","display_name":"Keyu Wang","orcid":"https://orcid.org/0009-0007-6296-6934"},"institutions":[{"id":"https://openalex.org/I4210132615","display_name":"Zhejiang Energy Group (China)","ror":"https://ror.org/03a2tkf74","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keyu Wang","raw_affiliation_strings":["LTD,Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation, Zhejiang Fangyuan Test Group Co.,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"LTD,Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation, Zhejiang Fangyuan Test Group Co.,Hangzhou,China","institution_ids":["https://openalex.org/I4210132615"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100690568"],"corresponding_institution_ids":["https://openalex.org/I4210132615"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19420106,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"58","last_page":"64"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9610999822616577,"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":0.9610999822616577,"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/T13213","display_name":"Mechanical Failure Analysis and Simulation","score":0.9537000060081482,"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"}},{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":0.945900022983551,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/prognostics","display_name":"Prognostics","score":0.9214924573898315},{"id":"https://openalex.org/keywords/reducer","display_name":"Reducer","score":0.8861616849899292},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.8372812271118164},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5529704689979553},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.41461968421936035},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.40385037660598755},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.35106444358825684},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.12331083416938782},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07896000146865845}],"concepts":[{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.9214924573898315},{"id":"https://openalex.org/C2776985865","wikidata":"https://www.wikidata.org/wiki/Q26820931","display_name":"Reducer","level":2,"score":0.8861616849899292},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.8372812271118164},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5529704689979553},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.41461968421936035},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.40385037660598755},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.35106444358825684},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.12331083416938782},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07896000146865845}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iotaai62601.2024.10692468","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iotaai62601.2024.10692468","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 6th International Conference on Internet of Things, Automation and Artificial Intelligence (IoTAAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2889850233","https://openalex.org/W3040694753","https://openalex.org/W3119081482","https://openalex.org/W3128962944","https://openalex.org/W3210944650","https://openalex.org/W4225116077","https://openalex.org/W4291366336","https://openalex.org/W4377097572","https://openalex.org/W4385830646","https://openalex.org/W4393097606","https://openalex.org/W4399035779"],"related_works":["https://openalex.org/W2943236215","https://openalex.org/W2394411596","https://openalex.org/W2737431648","https://openalex.org/W2349055795","https://openalex.org/W2310476526","https://openalex.org/W2557573737","https://openalex.org/W2383842997","https://openalex.org/W2143585755","https://openalex.org/W1815542355","https://openalex.org/W2152540334"],"abstract_inverted_index":{"This":[0,66,129,195,245],"paper":[1,196],"presents":[2],"an":[3],"advanced":[4],"framework":[5],"for":[6,28,83,258],"predicting":[7],"and":[8,78,139,241],"analyzing":[9],"the":[10,36,57,71,79,93,96,103,117,136,149,155,167,172,179,202,226,248],"Remaining":[11],"Useful":[12],"Life":[13],"(RUL)":[14],"of":[15,23,38,60,95,151,178,189,205,219,250],"electric":[16,61],"vehicle":[17,62],"reducers":[18,63],"using":[19],"a":[20,175,198],"novel":[21],"combination":[22],"deep":[24,251],"learning":[25,252],"techniques":[26],"tailored":[27],"mechanical":[29,206],"health":[30],"monitoring.":[31],"The":[32,216],"proposed":[33],"methodology":[34],"leverages":[35],"strengths":[37],"Convolutional":[39,97],"Long":[40],"Short-Term":[41],"Memory":[42],"(Conv-LSTM)":[43],"networks,":[44],"which":[45],"uniquely":[46],"merge":[47],"spatial":[48,72],"understanding":[49],"with":[50,223],"temporal":[51],"dependency":[52],"modeling":[53],"to":[54,110,120,145,184,237],"accurately":[55],"forecast":[56],"degradation":[58],"process":[59],"over":[64],"time.":[65],"integration":[67],"ensures":[68],"that":[69,235],"both":[70],"patterns":[73,124,187],"captured":[74],"from":[75,125],"sensor":[76,213],"data":[77,214],"sequential":[80],"information":[81],"essential":[82],"time-series":[84],"analysis":[85],"are":[86],"comprehensively":[87],"addressed.":[88],"A":[89],"key":[90],"innovation":[91],"is":[92],"incorporation":[94],"Block":[98],"Attention":[99],"Module":[100],"(CBAM)":[101],"into":[102,225],"model":[104],"architecture.":[105],"CBAM":[106],"facilitates":[107],"selective":[108],"attention":[109],"significant":[111,199],"features":[112],"at":[113],"multiple":[114],"levels,":[115],"enhancing":[116],"network's":[118],"ability":[119],"discern":[121],"critical":[122,259],"wear":[123],"less":[126],"pertinent":[127],"data.":[128],"multi-level":[130],"feature":[131,157],"extraction":[132],"capability":[133],"significantly":[134],"boosts":[135],"model's":[137,156],"interpretability":[138],"predictive":[140,203],"power":[141],"in":[142,201,209,254,264],"identifying":[143],"precursors":[144],"reducer":[146,229],"failure.":[147],"Furthermore,":[148],"implementation":[150],"dilated":[152],"convolutions":[153],"enriches":[154],"receptive":[158],"field":[159],"without":[160,192],"escalating":[161],"computational":[162],"demands.":[163],"By":[164],"strategically":[165],"increasing":[166],"spacing":[168],"between":[169],"kernel":[170],"elements,":[171],"network":[173],"gains":[174],"broader":[176],"perspective":[177],"input":[180],"data,":[181],"allowing":[182],"it":[183],"detect":[185],"global":[186],"indicative":[188],"impending":[190],"failure":[191],"sacrificing":[193],"resolution.":[194],"represent":[197],"advancement":[200],"maintenance":[204,233,243,256],"systems,":[207],"particularly":[208],"handling":[210],"complex,":[211],"high-dimensional":[212],"streams.":[215],"enhanced":[217],"accuracy":[218],"RUL":[220],"estimations,":[221],"coupled":[222],"insights":[224],"mechanisms":[227],"driving":[228],"degradation,":[230],"supports":[231],"proactive":[232],"strategies":[234],"aim":[236],"minimize":[238],"operational":[239],"downtime":[240],"reduce":[242],"costs.":[244],"research":[246],"underscores":[247],"potential":[249],"architectures":[253],"revolutionizing":[255],"practices":[257],"machinery,":[260],"demonstrating":[261],"their":[262],"efficacy":[263],"real-world":[265],"applications.":[266]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}