{"id":"https://openalex.org/W4292672370","doi":"https://doi.org/10.1109/tim.2022.3197801","title":"Analytics of Waveform Distortion Variations in Railway Pantograph Measurements by Deep Learning","display_name":"Analytics of Waveform Distortion Variations in Railway Pantograph Measurements by Deep Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4292672370","doi":"https://doi.org/10.1109/tim.2022.3197801"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3197801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3197801","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5088883540","display_name":"Rafael S. Salles","orcid":"https://orcid.org/0000-0002-3625-8578"},"institutions":[{"id":"https://openalex.org/I190632392","display_name":"Lule\u00e5 University of Technology","ror":"https://ror.org/016st3p78","country_code":"SE","type":"education","lineage":["https://openalex.org/I190632392"]},{"id":"https://openalex.org/I4210100733","display_name":"Skellefte\u00e5 Hospital","ror":"https://ror.org/0133j5m54","country_code":"SE","type":"healthcare","lineage":["https://openalex.org/I4210100733"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Rafael S. Salles","raw_affiliation_strings":["Electric Power Engineering, Luleå University of Technology, Skellefteå, Sweden","University of Technology, Skellefte&#x00E5",", Sweden"],"raw_orcid":"https://orcid.org/0000-0002-3625-8578","affiliations":[{"raw_affiliation_string":"Electric Power Engineering, Luleå University of Technology, Skellefteå, Sweden","institution_ids":["https://openalex.org/I190632392"]},{"raw_affiliation_string":"University of Technology, Skellefte&#x00E5","institution_ids":["https://openalex.org/I4210100733"]},{"raw_affiliation_string":", Sweden","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063838872","display_name":"Roger Alves de Oliveira","orcid":"https://orcid.org/0000-0001-5845-5620"},"institutions":[{"id":"https://openalex.org/I190632392","display_name":"Lule\u00e5 University of Technology","ror":"https://ror.org/016st3p78","country_code":"SE","type":"education","lineage":["https://openalex.org/I190632392"]},{"id":"https://openalex.org/I4210100733","display_name":"Skellefte\u00e5 Hospital","ror":"https://ror.org/0133j5m54","country_code":"SE","type":"healthcare","lineage":["https://openalex.org/I4210100733"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Roger Alves de Oliveira","raw_affiliation_strings":["Electric Power Engineering, Luleå University of Technology, Skellefteå, Sweden","University of Technology, Skellefte&#x00E5",", Sweden"],"raw_orcid":"https://orcid.org/0000-0001-5845-5620","affiliations":[{"raw_affiliation_string":"Electric Power Engineering, Luleå University of Technology, Skellefteå, Sweden","institution_ids":["https://openalex.org/I190632392"]},{"raw_affiliation_string":"University of Technology, Skellefte&#x00E5","institution_ids":["https://openalex.org/I4210100733"]},{"raw_affiliation_string":", Sweden","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043027712","display_name":"Sarah R\u00f6nnberg","orcid":"https://orcid.org/0000-0002-4004-0352"},"institutions":[{"id":"https://openalex.org/I190632392","display_name":"Lule\u00e5 University of Technology","ror":"https://ror.org/016st3p78","country_code":"SE","type":"education","lineage":["https://openalex.org/I190632392"]},{"id":"https://openalex.org/I4210100733","display_name":"Skellefte\u00e5 Hospital","ror":"https://ror.org/0133j5m54","country_code":"SE","type":"healthcare","lineage":["https://openalex.org/I4210100733"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sarah K. Ronnberg","raw_affiliation_strings":["Electric Power Engineering, Luleå University of Technology, Skellefteå, Sweden",", Sweden","University of Technology, Skellefte&#x00E5"],"raw_orcid":"https://orcid.org/0000-0002-4004-0352","affiliations":[{"raw_affiliation_string":"Electric Power Engineering, Luleå University of Technology, Skellefteå, Sweden","institution_ids":["https://openalex.org/I190632392"]},{"raw_affiliation_string":", Sweden","institution_ids":[]},{"raw_affiliation_string":"University of Technology, Skellefte&#x00E5","institution_ids":["https://openalex.org/I4210100733"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069618209","display_name":"Andrea Mariscotti","orcid":"https://orcid.org/0000-0002-0096-7305"},"institutions":[{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Mariscotti","raw_affiliation_strings":["Department of Electrical, Electronics and Telecommunication Engineering and Naval Architecture (DITEN), University of Genoa, Genoa, Italy"],"raw_orcid":"https://orcid.org/0000-0002-0096-7305","affiliations":[{"raw_affiliation_string":"Department of Electrical, Electronics and Telecommunication Engineering and Naval Architecture (DITEN), University of Genoa, Genoa, Italy","institution_ids":["https://openalex.org/I83816512"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5088883540"],"corresponding_institution_ids":["https://openalex.org/I190632392","https://openalex.org/I4210100733"],"apc_list":null,"apc_paid":null,"fwci":2.089,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.86095582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12371","display_name":"Electrical Contact Performance and Analysis","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T12371","display_name":"Electrical Contact Performance and Analysis","score":0.9995999932289124,"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.9994999766349792,"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/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/waveform","display_name":"Waveform","score":0.6618391871452332},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6021968126296997},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5647708773612976},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5496219396591187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5325960516929626},{"id":"https://openalex.org/keywords/pantograph","display_name":"Pantograph","score":0.5305106043815613},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5038289427757263},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4865402281284332},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4787932336330414},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4492626190185547},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3908610939979553},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34949737787246704},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3280007839202881},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.293454110622406},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11486005783081055},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.10203209519386292}],"concepts":[{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.6618391871452332},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6021968126296997},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5647708773612976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5496219396591187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5325960516929626},{"id":"https://openalex.org/C20756127","wikidata":"https://www.wikidata.org/wiki/Q722757","display_name":"Pantograph","level":2,"score":0.5305106043815613},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5038289427757263},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4865402281284332},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4787932336330414},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4492626190185547},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3908610939979553},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34949737787246704},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3280007839202881},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.293454110622406},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11486005783081055},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.10203209519386292},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tim.2022.3197801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3197801","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:iris.unige.it:11567/1102677","is_oa":false,"landing_page_url":"https://hdl.handle.net/11567/1102677","pdf_url":null,"source":{"id":"https://openalex.org/S4377196291","display_name":"CINECA IRIS Institutial Research Information System (University of Genoa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I83816512","host_organization_name":"University of Genoa","host_organization_lineage":["https://openalex.org/I83816512"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322711","display_name":"Energimyndigheten","ror":"https://ror.org/0359z7n90"},{"id":"https://openalex.org/F4320327853","display_name":"Trafikverket","ror":"https://ror.org/000nes056"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1947894988","https://openalex.org/W2016624209","https://openalex.org/W2083766071","https://openalex.org/W2085487226","https://openalex.org/W2089468765","https://openalex.org/W2090023330","https://openalex.org/W2097494045","https://openalex.org/W2100495367","https://openalex.org/W2120122198","https://openalex.org/W2169729720","https://openalex.org/W2505742470","https://openalex.org/W2523336504","https://openalex.org/W2528038959","https://openalex.org/W2792776798","https://openalex.org/W2920947047","https://openalex.org/W2936246465","https://openalex.org/W2958959725","https://openalex.org/W2983460574","https://openalex.org/W2998229718","https://openalex.org/W2999320175","https://openalex.org/W3000488516","https://openalex.org/W3014014312","https://openalex.org/W3020135825","https://openalex.org/W3026686908","https://openalex.org/W3038293692","https://openalex.org/W3042157780","https://openalex.org/W3049613208","https://openalex.org/W3082024442","https://openalex.org/W3089155409","https://openalex.org/W3110766518","https://openalex.org/W3126638903","https://openalex.org/W3137902428","https://openalex.org/W3196404998","https://openalex.org/W3206060653","https://openalex.org/W3210949705","https://openalex.org/W4220891740","https://openalex.org/W4254146266","https://openalex.org/W4281647000","https://openalex.org/W6631190155","https://openalex.org/W6748102297","https://openalex.org/W6755218872"],"related_works":["https://openalex.org/W2573375108","https://openalex.org/W4401544776","https://openalex.org/W4252833549","https://openalex.org/W4387011711","https://openalex.org/W4310873165","https://openalex.org/W2806873178","https://openalex.org/W2965146396","https://openalex.org/W2770818364","https://openalex.org/W4404095322","https://openalex.org/W4312416532"],"abstract_inverted_index":{"Waveform":[0],"distortion":[1,82,134],"in":[2,8,45,180],"general":[3],"represent":[4],"a":[5,60,90,128,191],"widespread":[6],"problem":[7],"electrified":[9],"transports":[10],"due":[11],"to":[12,73,79,126,147,166,190],"interference,":[13],"service":[14],"disruption,":[15],"increased":[16],"losses":[17],"and":[18,28,42,107,143,184],"ageing":[19],"of":[20,25,70,75,86,131,141,159,171,182,186],"components.":[21],"Given":[22],"the":[23,29,51,116,157,160,167,172],"multitude":[24],"moving":[26],"sources":[27],"extremely":[30],"variable":[31],"operating":[32,169],"conditions,":[33],"short":[34],"time":[35],"records":[36],"must":[37],"be":[38],"considered":[39],"for":[40,53,203],"analysis,":[41],"this":[43],"increases":[44],"turn":[46],"its":[47],"complexity,":[48],"from":[49,89],"which":[50],"need":[52],"effective":[54],"automated":[55],"processing,":[56],"as":[57,201],"offered":[58],"by":[59,121,155,163],"deep":[61,117],"learning":[62],"(DL)":[63],"approach.":[64],"This":[65],"paper":[66],"proposes":[67],"an":[68],"application":[69],"unsupervised":[71],"DL":[72,99,112],"measurements":[74],"railway":[76,96],"pantograph":[77,87],"quantities":[78],"identify":[80],"waveform":[81],"patterns.":[83],"Data":[84],"consists":[85],"current":[88],"Swiss":[91],"15":[92],"kV":[93],"16.7":[94],"Hz":[95],"system.":[97],"Three":[98],"input":[100],"types":[101],"are":[102,151,178],"considered:":[103],"waveforms,":[104],"harmonic":[105,142],"spectra,":[106],"supraharmonic":[108,144],"spectra.":[109],"The":[110],"applied":[111,114],"method":[113],"is":[115,135],"autoencoder":[118],"(DAE)":[119],"followed":[120],"feature":[122],"clustering,":[123],"using":[124],"techniques":[125],"define":[127],"suitable":[129],"number":[130],"clusters.":[132],"Short-term":[133],"evaluated":[136],"over":[137],"sub-10":[138],"min":[139],"intervals":[140],"spectra":[145],"down":[146],"sub-second":[148],"intervals.":[149],"Results":[150],"explained":[152],"among":[153],"others":[154],"connecting":[156],"distribution":[158],"clusters":[161],"(determined":[162],"self-supervised":[164],"method)":[165],"dynamic":[168],"conditions":[170],"rolling":[173],"stock.":[174],"Resulting":[175],"DAE":[176],"performance":[177],"superior":[179],"terms":[181],"accuracy":[183],"comprehensiveness":[185],"spectral":[187],"components":[188],"compared":[189],"more":[192],"traditional":[193],"principal":[194],"component":[195],"analysis":[196],"(PCA)":[197],"that":[198],"was":[199],"chosen":[200],"reference":[202],"comparison.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}