{"id":"https://openalex.org/W2903310602","doi":"https://doi.org/10.23919/eusipco.2018.8553525","title":"Embedding Intelligent Features for Vibration-Based Machine Condition Monitoring","display_name":"Embedding Intelligent Features for Vibration-Based Machine Condition Monitoring","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2903310602","doi":"https://doi.org/10.23919/eusipco.2018.8553525","mag":"2903310602"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2018.8553525","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","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/A5020287667","display_name":"Christian Reich","orcid":"https://orcid.org/0000-0001-6844-0449"},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Reich","raw_affiliation_strings":["Robert Bosch GmbH, Corporate Research, Renningen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robert Bosch GmbH, Corporate Research, Renningen, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057967722","display_name":"Ahmad Mansour","orcid":"https://orcid.org/0009-0005-8325-7809"},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ahmad Mansour","raw_affiliation_strings":["Robert Bosch GmbH, Corporate Research, Renningen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robert Bosch GmbH, Corporate Research, Renningen, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027114416","display_name":"Kristof Van Laerhoven","orcid":"https://orcid.org/0000-0001-5296-5347"},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kristof van Laerhoven","raw_affiliation_strings":["Ubiquitous Computing, University of Siegen, Siegen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ubiquitous Computing, University of Siegen, Siegen, Germany","institution_ids":["https://openalex.org/I206895457"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5128,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.66400364,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"371","last_page":"375"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10188","display_name":"Advanced machining processes and optimization","score":0.9998999834060669,"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/T10188","display_name":"Advanced machining processes and optimization","score":0.9998999834060669,"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/T13113","display_name":"Engineering Technology and Methodologies","score":0.9962999820709229,"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"}},{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9944999814033508,"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/embedding","display_name":"Embedding","score":0.7041569352149963},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6659296751022339},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.5939993858337402},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.5669010281562805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31667232513427734},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18727576732635498},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.18687719106674194},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.15096241235733032},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07486549019813538}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7041569352149963},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6659296751022339},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.5939993858337402},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.5669010281562805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31667232513427734},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18727576732635498},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.18687719106674194},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.15096241235733032},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07486549019813538}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2018.8553525","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W78747592","https://openalex.org/W1503398984","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1972437757","https://openalex.org/W1981688790","https://openalex.org/W2000304567","https://openalex.org/W2037560739","https://openalex.org/W2070171541","https://openalex.org/W2088638930","https://openalex.org/W2142635246","https://openalex.org/W2168175751","https://openalex.org/W2483430316","https://openalex.org/W2567271240","https://openalex.org/W2952176586","https://openalex.org/W6722243183","https://openalex.org/W6732059171"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2081900870","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2094815465","https://openalex.org/W2156186572","https://openalex.org/W2554683084"],"abstract_inverted_index":{"Today's":[0],"demands":[1],"regarding":[2],"workpiece":[3],"quality":[4],"in":[5,142,162,222],"cutting":[6,19,191],"machine":[7,15,47,91,102,192],"tool":[8,106,194],"processing":[9],"require":[10],"automated":[11],"monitoring":[12,23,48,92,103,108],"of":[13,35,105,115,129,151,179,187,190,206,217,226,252],"both":[14],"condition":[16,107],"and":[17,33,57,167,196,209],"the":[18,99,143,154,180],"process.":[20],"Currently,":[21],"best-performing":[22],"approaches":[24],"rely":[25,66,77],"on":[26,67,78,183],"high-frequency":[27],"acoustic":[28],"emission":[29],"(AE)":[30],"sensor":[31,51],"data":[32,68,97,185],"definition":[34],"advanced":[36,116],"features,":[37,117],"which":[38,76],"involve":[39],"complex":[40],"computations.":[41],"This":[42],"approach":[43,182],"is":[44],"challenging":[45],"for":[46,89,98,148,153,174],"via":[49],"embedded":[50],"systems":[52],"with":[53,62,70,112,247],"constrained":[54,63],"computational":[55,113],"power":[56],"energy":[58],"budget.":[59],"To":[60,81,110],"cope":[61,111],"energy,":[64],"we":[65,95,118,125,136],"recording":[69],"microelectromechanical":[71],"system":[72],"(MEMS)":[73],"vibration":[74],"sensors,":[75],"lower-frequency":[79,85],"sampling.":[80],"clarify":[82],"whether":[83],"these":[84,223],"signals":[86,128,145],"bear":[87],"information":[88],"typical":[90],"prediction":[93],"tasks,":[94],"evaluate":[96],"most":[100,138,163,210],"generic":[101],"task":[104],"(TCM).":[109],"complexity":[114],"introduce":[119],"two":[120],"intelligent":[121],"preprocessing":[122,202],"algorithms.":[123],"First,":[124],"split":[126],"non-stationary":[127],"recurrent":[130],"structure":[131],"into":[132],"similar":[133],"segments.":[134],"Then,":[135],"identify":[137],"discriminative":[139,211],"spectral":[140,168],"differences":[141],"segmented":[144],"that":[146],"allow":[147],"best":[149],"separation":[150],"classes":[152],"given":[155],"TCM":[156,229],"task.":[157],"Subsequent":[158],"feature":[159,234,243],"extraction":[160,216],"only":[161],"relevant":[164],"signal":[165],"segments":[166,208],"regions":[169,225],"enables":[170,203],"high":[171],"expressiveness":[172],"even":[173],"simple":[175,218],"features.":[176],"Extensive":[177],"evaluation":[178],"outlined":[181],"multiple":[184],"sets":[186],"different":[188],"combinations":[189],"tools,":[193],"types":[195],"workpieces":[197],"confirms":[198],"its":[199],"sensibility.":[200],"Intelligent":[201],"reliable":[204],"identification":[205],"stationary":[207],"frequency":[212],"bands.":[213],"With":[214],"subsequent":[215],"but":[219],"tailor-made":[220],"features":[221],"spectral-temporal":[224],"interest":[227],"(Rols),":[228],"typically":[230],"framed":[231],"as":[232],"multi":[233],"classification":[235],"problem":[236,246],"can":[237],"be":[238],"converted":[239],"to":[240],"a":[241],"single":[242],"threshold":[244],"comparison":[245],"an":[248],"average":[249],"F1":[250],"score":[251],"97.89%.":[253]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}