{"id":"https://openalex.org/W7225425284","doi":"https://doi.org/10.1108/rs-09-2026-0071","title":"Multi-channel data fusion and lightweight 1D-CNN for compound axle bearing fault diagnosis in bogie systems","display_name":"Multi-channel data fusion and lightweight 1D-CNN for compound axle bearing fault diagnosis in bogie systems","publication_year":2026,"publication_date":"2026-11-06","ids":{"openalex":"https://openalex.org/W7225425284","doi":"https://doi.org/10.1108/rs-09-2026-0071"},"language":"en","primary_location":{"id":"doi:10.1108/rs-09-2026-0071","doi":"https://doi.org/10.1108/rs-09-2026-0071","is_oa":true,"landing_page_url":"https://doi.org/10.1108/rs-09-2026-0071","pdf_url":null,"source":{"id":"https://openalex.org/S4387280010","display_name":"Railway Sciences","issn_l":"2755-0907","issn":["2755-0907","2755-0915"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj"],"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Railway Sciences","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1108/rs-09-2026-0071","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116605483","display_name":"Meryem Abtane","orcid":"https://orcid.org/0009-0003-8466-1921","observed_orcids":["https://orcid.org/0009-0003-8466-1921"]},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I144889574","display_name":"Universit\u00e9 de Pau et des Pays de l'Adour","ror":"https://ror.org/01frn9647","country_code":"FR","type":"education","lineage":["https://openalex.org/I144889574"]},{"id":"https://openalex.org/I4210092492","display_name":"Institut des Sciences Analytiques et de Physico-Chimie pour l'Environnement et les Mat\u00e9riaux","ror":"https://ror.org/00222yk13","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I144889574","https://openalex.org/I205703379","https://openalex.org/I4210092492","https://openalex.org/I4210127738","https://openalex.org/I4210128300"]},{"id":"https://openalex.org/I4387153621","display_name":"Ecole Centrale Casablanca","ror":"https://ror.org/04g1c5a53","country_code":"MA","type":"education","lineage":["https://openalex.org/I4387153621"]}],"countries":["FR","MA"],"is_corresponding":false,"raw_author_name":"Meryem Abtane","raw_affiliation_strings":["E2S UPPA, CNRS UMR 5254, IPREM, Universit\u00e9 de Pau et des Pays de l'Adour , ,","Ecole Centrale Casablanca Complex Systems and Interactions, , ,"],"raw_orcid":"https://orcid.org/0009-0003-8466-1921","affiliations":[{"raw_affiliation_string":"E2S UPPA, CNRS UMR 5254, IPREM, Universit\u00e9 de Pau et des Pays de l'Adour , ,","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I144889574","https://openalex.org/I4210092492"]},{"raw_affiliation_string":"Ecole Centrale Casablanca Complex Systems and Interactions, , ,","institution_ids":["https://openalex.org/I4387153621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059789660","display_name":"Khalid Dahi","orcid":"https://orcid.org/0000-0002-1651-0668","observed_orcids":["https://orcid.org/0000-0002-1651-0668"]},"institutions":[{"id":"https://openalex.org/I4387153621","display_name":"Ecole Centrale Casablanca","ror":"https://ror.org/04g1c5a53","country_code":"MA","type":"education","lineage":["https://openalex.org/I4387153621"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Khalid Dahi","raw_affiliation_strings":["Ecole Centrale Casablanca Complex Systems and Interactions, , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ecole Centrale Casablanca Complex Systems and Interactions, , ,","institution_ids":["https://openalex.org/I4387153621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012154645","display_name":"Herv\u00e9 Martinez","orcid":"https://orcid.org/0000-0002-6621-199X","observed_orcids":["https://orcid.org/0000-0002-6621-199X"]},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I144889574","display_name":"Universit\u00e9 de Pau et des Pays de l'Adour","ror":"https://ror.org/01frn9647","country_code":"FR","type":"education","lineage":["https://openalex.org/I144889574"]},{"id":"https://openalex.org/I4210092492","display_name":"Institut des Sciences Analytiques et de Physico-Chimie pour l'Environnement et les Mat\u00e9riaux","ror":"https://ror.org/00222yk13","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I144889574","https://openalex.org/I205703379","https://openalex.org/I4210092492","https://openalex.org/I4210127738","https://openalex.org/I4210128300"]},{"id":"https://openalex.org/I4387153621","display_name":"Ecole Centrale Casablanca","ror":"https://ror.org/04g1c5a53","country_code":"MA","type":"education","lineage":["https://openalex.org/I4387153621"]}],"countries":["FR","MA"],"is_corresponding":false,"raw_author_name":"Herv\u00e9 Martinez","raw_affiliation_strings":["E2S UPPA, CNRS UMR 5254, IPREM, Universit\u00e9 de Pau et des Pays de l'Adour , ,","Ecole Centrale Casablanca Complex Systems and Interactions, , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"E2S UPPA, CNRS UMR 5254, IPREM, Universit\u00e9 de Pau et des Pays de l'Adour , ,","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I144889574","https://openalex.org/I4210092492"]},{"raw_affiliation_string":"Ecole Centrale Casablanca Complex Systems and Interactions, , ,","institution_ids":["https://openalex.org/I4387153621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094000819","display_name":"Iman Makrouf","orcid":"https://orcid.org/0000-0002-9803-1977","observed_orcids":["https://orcid.org/0000-0002-9803-1977"]},"institutions":[{"id":"https://openalex.org/I4387153621","display_name":"Ecole Centrale Casablanca","ror":"https://ror.org/04g1c5a53","country_code":"MA","type":"education","lineage":["https://openalex.org/I4387153621"]},{"id":"https://openalex.org/I99297268","display_name":"University of Hassan II Casablanca","ror":"https://ror.org/001q4kn48","country_code":"MA","type":"education","lineage":["https://openalex.org/I99297268"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Iman Makrouf","raw_affiliation_strings":["ENSAM, Universit\u00e9 Hassan II Casablanca Laboratory of Digital Engineering for Leading Technologies and Automation, , ,","Ecole Centrale Casablanca Complex Systems and Interactions, , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ENSAM, Universit\u00e9 Hassan II Casablanca Laboratory of Digital Engineering for Leading Technologies and Automation, , ,","institution_ids":["https://openalex.org/I99297268"]},{"raw_affiliation_string":"Ecole Centrale Casablanca Complex Systems and Interactions, , ,","institution_ids":["https://openalex.org/I4387153621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079334767","display_name":"Sedki Mohamed","orcid":"https://orcid.org/0009-0006-0853-3372","observed_orcids":["https://orcid.org/0009-0006-0853-3372"]},"institutions":[{"id":"https://openalex.org/I4210096509","display_name":"Moroccan National Railways Office","ror":"https://ror.org/00p9yb286","country_code":"MA","type":"government","lineage":["https://openalex.org/I4210096509"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Mohamed Sedki","raw_affiliation_strings":["ONCF, Office National des Chemins de Fer , ,","SIANA, Soci\u00e9t\u00e9 Marocaine de Maintenance des Rames \u00e0 Grande Vitesse , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ONCF, Office National des Chemins de Fer , ,","institution_ids":["https://openalex.org/I4210096509"]},{"raw_affiliation_string":"SIANA, Soci\u00e9t\u00e9 Marocaine de Maintenance des Rames \u00e0 Grande Vitesse , ,","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161071339","display_name":"Hicham El Kimi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hicham El Kimi","raw_affiliation_strings":["SIANA, Soci\u00e9t\u00e9 Marocaine de Maintenance des Rames \u00e0 Grande Vitesse , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIANA, Soci\u00e9t\u00e9 Marocaine de Maintenance des Rames \u00e0 Grande Vitesse , ,","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5116605488","display_name":"Luciano Fernandes Borges","orcid":"https://orcid.org/0009-0001-2659-3276","observed_orcids":["https://orcid.org/0009-0001-2659-3276"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luciano Fernandes Borges","raw_affiliation_strings":["SIANA, Soci\u00e9t\u00e9 Marocaine de Maintenance des Rames \u00e0 Grande Vitesse , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIANA, Soci\u00e9t\u00e9 Marocaine de Maintenance des Rames \u00e0 Grande Vitesse , ,","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":1.0,"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":1.0,"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.0,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.0,"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/bearing-fault-diagnosis","display_name":"bearing fault diagnosis","score":0.7680000066757202},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"sensor fusion","score":0.8420000076293945},{"id":"https://openalex.org/keywords/vibration-signals","display_name":"vibration signals","score":0.9300000071525574},{"id":"https://openalex.org/keywords/acoustic-emission","display_name":"acoustic emission","score":0.878000020980835},{"id":"https://openalex.org/keywords/1d-convolutional-neural-network","display_name":"1D convolutional neural network","score":0.8640000224113464},{"id":"https://openalex.org/keywords/lightweight-deep-learning-models","display_name":"lightweight deep learning","score":0.8709999918937683},{"id":"https://openalex.org/keywords/predictive-maintenance","display_name":"predictive maintenance","score":0.8029999732971191},{"id":"https://openalex.org/keywords/subway-trains","display_name":"subway trains","score":0.4790000021457672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.676800012588501},{"id":"https://openalex.org/C123045823","wikidata":"https://www.wikidata.org/wiki/Q217421","display_name":"Bogie","level":2,"score":0.6273999810218811},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5422000288963318},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.5414000153541565},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5249999761581421},{"id":"https://openalex.org/C129727815","wikidata":"https://www.wikidata.org/wiki/Q188209","display_name":"Axle","level":2,"score":0.49399998784065247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4708000123500824},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46369999647140503},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4433000087738037},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.40130001306533813},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.39910000562667847},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3817000091075897},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3398999869823456},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.328900009393692},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3111000061035156},{"id":"https://openalex.org/C2776247918","wikidata":"https://www.wikidata.org/wiki/Q1423713","display_name":"Structural health monitoring","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28610000014305115},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2648000121116638}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/rs-09-2026-0071","doi":"https://doi.org/10.1108/rs-09-2026-0071","is_oa":true,"landing_page_url":"https://doi.org/10.1108/rs-09-2026-0071","pdf_url":null,"source":{"id":"https://openalex.org/S4387280010","display_name":"Railway Sciences","issn_l":"2755-0907","issn":["2755-0907","2755-0915"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj"],"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Railway Sciences","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1108/rs-09-2026-0071","doi":"https://doi.org/10.1108/rs-09-2026-0071","is_oa":true,"landing_page_url":"https://doi.org/10.1108/rs-09-2026-0071","pdf_url":null,"source":{"id":"https://openalex.org/S4387280010","display_name":"Railway Sciences","issn_l":"2755-0907","issn":["2755-0907","2755-0915"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj"],"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Railway Sciences","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":1.0,"id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1529114373","https://openalex.org/W2004263461","https://openalex.org/W2560859102","https://openalex.org/W2759995600","https://openalex.org/W2890952527","https://openalex.org/W2921234326","https://openalex.org/W3081032406","https://openalex.org/W3113180030","https://openalex.org/W4205608352","https://openalex.org/W4311901446","https://openalex.org/W4319990462","https://openalex.org/W4365142140","https://openalex.org/W4387138565","https://openalex.org/W4391328318","https://openalex.org/W4396572044","https://openalex.org/W4401699858","https://openalex.org/W4408609531","https://openalex.org/W4413017947","https://openalex.org/W4413909946","https://openalex.org/W4414223587","https://openalex.org/W6941255086","https://openalex.org/W7118463285","https://openalex.org/W7155175915","https://openalex.org/W7160405338","https://openalex.org/W7161151285","https://openalex.org/W7165687444"],"related_works":["https://openalex.org/W4413033413","https://openalex.org/W4416307541","https://openalex.org/W6925099316","https://openalex.org/W4408229147","https://openalex.org/W4381185947","https://openalex.org/W4386066062","https://openalex.org/W3090238656","https://openalex.org/W4407694458","https://openalex.org/W7163675442","https://openalex.org/W7170196943"],"abstract_inverted_index":{"Purpose":[0],"Traditional":[1],"diagnostic":[2,183],"methods":[3],"are,":[4],"in":[5,178],"most":[6],"cases,":[7],"based":[8],"on":[9,111],"single-sensor":[10],"data;":[11],"however,":[12],"this":[13],"configuration":[14],"may":[15],"fail":[16],"to":[17,60,134,167],"capture":[18],"the":[19,36,73,80,112,127,144,161],"complex":[20],"dynamic":[21],"signatures":[22],"associated":[23],"with":[24,185],"multi-component":[25],"degradation.":[26],"This":[27],"paper":[28],"presents":[29,130],"a":[30,52,87,92,169,186],"lightweight":[31],"deep":[32],"learning":[33],"architecture":[34,138],"for":[35,99,143,175],"fusion":[37,165],"of":[38,163],"multi-modal":[39],"sensor":[40],"data,":[41],"typically":[42],"vibration":[43,65],"and":[44,67,91,104,154,172,189],"acoustic":[45,69],"signals.":[46],"Design/methodology/approach":[47],"The":[48,137],"proposed":[49],"model":[50],"represents":[51],"dual-branch":[53],"one-dimensional":[54],"convolutional":[55],"neural":[56],"network":[57],"(1D-CNN)":[58],"designed":[59],"simultaneously":[61],"process":[62],"six":[63],"axis":[64],"signals":[66],"dual-channel":[68],"emissions.":[70],"To":[71],"ensure":[72],"model's":[74],"generalizability":[75],"under":[76],"multiple":[77],"operating":[78],"conditions,":[79,148],"study":[81],"evaluates":[82],"two":[83],"distinct":[84,146],"data-splitting":[85],"strategies:":[86],"standard":[88],"random":[89],"split":[90,96],"more":[93],"rigorous":[94],"sample-based":[95],"that":[97,126],"accounts":[98],"specific":[100],"data":[101,164],"acquisition":[102],"conditions":[103],"trial-to-trial":[105],"variability.":[106],"Findings":[107],"Experimental":[108],"results,":[109],"validated":[110],"open-source":[113],"Beijing":[114],"Jiaotong":[115],"University":[116],"-":[117],"Rail":[118],"Autonomous":[119],"Operations":[120],"(BJTU-RAO)":[121],"subway":[122],"bogie":[123],"dataset,":[124],"demonstrate":[125],"fusion-based":[128],"approach":[129],"significant":[131],"results":[132,159],"compared":[133],"single-modality":[135],"baselines.":[136],"achieves":[139],"high":[140,182],"classification":[141],"accuracy":[142],"12":[145],"health":[147],"which":[149],"precisely":[150],"identify":[151],"both":[152],"single":[153],"multiple-component":[155],"defects.":[156],"Originality/value":[157],"These":[158],"highlight":[160],"potential":[162],"integration":[166],"provide":[168],"stable,":[170],"scalable":[171],"frugal":[173],"framework":[174],"predictive":[176],"maintenance":[177],"railway":[179],"systems,":[180],"combining":[181],"performance":[184],"minimal":[187],"computational":[188],"memory":[190],"footprint.":[191]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-11-07T00:00:00"}
