{"id":"https://openalex.org/W4366668772","doi":"https://doi.org/10.1109/tits.2023.3265401","title":"Multi-Sensor Graph Transfer Network for Health Assessment of High-Speed Rail Suspension Systems","display_name":"Multi-Sensor Graph Transfer Network for Health Assessment of High-Speed Rail Suspension Systems","publication_year":2023,"publication_date":"2023-04-21","ids":{"openalex":"https://openalex.org/W4366668772","doi":"https://doi.org/10.1109/tits.2023.3265401"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2023.3265401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3265401","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-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/A5071436911","display_name":"Dingcheng Zhang","orcid":"https://orcid.org/0000-0001-5843-9428"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dingcheng Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-5843-9428","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070592593","display_name":"Min Xie","orcid":"https://orcid.org/0000-0002-8500-8364"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Min Xie","raw_affiliation_strings":["Department of Systems Engineering and Engineering Management, City University of Hong Kong, Jurong West, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-8500-8364","affiliations":[{"raw_affiliation_string":"Department of Systems Engineering and Engineering Management, City University of Hong Kong, Jurong West, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101553001","display_name":"Jingyuan Yang","orcid":"https://orcid.org/0000-0002-7206-800X"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jingyuan Yang","raw_affiliation_strings":["School of Engineering, University of Birmingham, Birmingham, U.K"],"raw_orcid":"https://orcid.org/0000-0002-7206-800X","affiliations":[{"raw_affiliation_string":"School of Engineering, University of Birmingham, Birmingham, U.K","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101749804","display_name":"Tao Wen","orcid":"https://orcid.org/0000-0002-8253-9338"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wen","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8253-9338","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5071436911"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":3.0018,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.91234097,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"24","issue":"9","first_page":"9425","last_page":"9434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9926999807357788,"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":0.9926999807357788,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9768999814987183,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/train","display_name":"Train","score":0.7213715314865112},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5777852535247803},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5566838979721069},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48931095004081726},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.487779438495636},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.48324641585350037},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.45369863510131836},{"id":"https://openalex.org/keywords/suspension","display_name":"Suspension (topology)","score":0.41305840015411377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3495336174964905},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3489302396774292},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10558772087097168},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.08160239458084106}],"concepts":[{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.7213715314865112},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5777852535247803},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5566838979721069},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48931095004081726},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.487779438495636},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.48324641585350037},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.45369863510131836},{"id":"https://openalex.org/C105341887","wikidata":"https://www.wikidata.org/wiki/Q1307987","display_name":"Suspension (topology)","level":3,"score":0.41305840015411377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3495336174964905},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3489302396774292},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10558772087097168},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.08160239458084106},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C5961521","wikidata":"https://www.wikidata.org/wiki/Q746083","display_name":"Homotopy","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2023.3265401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3265401","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2696031726","display_name":null,"funder_award_id":"2023NSFSC0862","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3729859358","display_name":null,"funder_award_id":"T32-101/15-R","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"id":"https://openalex.org/G3756673222","display_name":null,"funder_award_id":"2023YFSY0003","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6852337077","display_name":null,"funder_award_id":"2021YFB3300801","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1998536814","https://openalex.org/W2030366021","https://openalex.org/W2046721486","https://openalex.org/W2056054794","https://openalex.org/W2074997793","https://openalex.org/W2079715933","https://openalex.org/W2082536113","https://openalex.org/W2084050536","https://openalex.org/W2151017405","https://openalex.org/W2461729787","https://openalex.org/W2553056948","https://openalex.org/W2601590138","https://openalex.org/W2747276445","https://openalex.org/W2765640728","https://openalex.org/W2773549135","https://openalex.org/W2897585580","https://openalex.org/W2951543691","https://openalex.org/W2964321699","https://openalex.org/W2995279030","https://openalex.org/W2996739774","https://openalex.org/W3080532600","https://openalex.org/W3094594436","https://openalex.org/W3094978828","https://openalex.org/W3115300804","https://openalex.org/W3194131586","https://openalex.org/W3199139896","https://openalex.org/W3205719659","https://openalex.org/W4240592325","https://openalex.org/W4288032970","https://openalex.org/W4293195785","https://openalex.org/W6720006811","https://openalex.org/W6801291849","https://openalex.org/W6802599841"],"related_works":["https://openalex.org/W618248309","https://openalex.org/W2377336366","https://openalex.org/W1601203902","https://openalex.org/W4390419160","https://openalex.org/W2102464536","https://openalex.org/W2361332776","https://openalex.org/W4225671779","https://openalex.org/W1568097102","https://openalex.org/W2897407000","https://openalex.org/W2248934910"],"abstract_inverted_index":{"Suspension":[0],"systems":[1],"are":[2,182],"significant":[3],"for":[4,51,209],"safe":[5],"and":[6,25,43,84,145,204],"comfort":[7],"operation":[8,29,230],"of":[9,22,30,45,54,80,133,158,180,184,222],"high-speed":[10,31,159],"trains.":[11],"Health":[12],"assessment":[13,53,211],"is":[14,76,99,122,163,199],"a":[15,64,92,153],"useful":[16],"tool":[17],"to":[18,102,124,165,170,201],"schedule":[19],"maintenance":[20],"plans":[21],"suspension":[23,56,135,161],"systems,":[24],"furthermore":[26],"ensure":[27],"safety":[28],"railway":[32],"transportation.":[33],"In":[34,61,88,149,173],"real":[35],"operating":[36],"condition,":[37],"two":[38,141],"problems,":[39],"i.e.":[40],"data":[41,194],"imbalance":[42],"shortage":[44],"labelled":[46,167,193],"data,":[47],"result":[48],"in":[49,78,113,120,143,188,195],"difficult":[50],"health":[52,210],"the":[55,89,134,150,174,177,185,189,196,206,217,223],"system":[57,162],"using":[58,228],"deep":[59,81],"learning.":[60],"this":[62],"work,":[63],"multi-sensor":[65,71,94,126],"information":[66,127],"fusion":[67,118],"method,":[68,91],"called":[69],"as":[70],"graph":[72,85,95],"transfer":[73,82],"network":[74,97],"(MSGTN),":[75],"proposed":[77,90,101,123,224],"basis":[79],"learning":[83],"neural":[86,96],"network.":[87],"domain-share":[93],"(MSGNN)":[98],"firstly":[100],"extract":[103],"features":[104],"from":[105,109],"vibration":[106],"signals":[107],"collected":[108],"three":[110],"different":[111],"positions":[112],"train":[114],"vehicles.":[115],"A":[116],"graph-based":[117],"layer":[119],"MSGNN":[121,181,203],"fuse":[125],"by":[128,215],"combining":[129],"frequency":[130],"response":[131],"curves":[132],"system.":[136],"The":[137,192,220],"MSGTN":[138],"mainly":[139],"includes":[140],"parts":[142],"source":[144,151,190],"target":[146,175,197],"domains":[147],"respectively.":[148],"domain,":[152,176],"simple":[154],"physical":[155],"dynamic":[156],"model":[157,187,208],"rail":[160],"built":[164],"generate":[166],"simulation":[168],"datasets":[169],"pre-train":[171,186],"MSGNN.":[172],"initial":[178],"hyper-parameters":[179],"that":[183],"domain.":[191],"domain":[198],"fed":[200],"fine-tune":[202],"then":[205],"final":[207],"can":[212],"be":[213],"obtained":[214],"minimizing":[216],"loss":[218],"function.":[219],"effectiveness":[221],"method":[225],"was":[226],"verified":[227],"real-work":[229],"data.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3}],"updated_date":"2026-05-12T08:28:47.272897","created_date":"2025-10-10T00:00:00"}
