{"id":"https://openalex.org/W4386072512","doi":"https://doi.org/10.1109/indin51400.2023.10218170","title":"Explaining Deep Neural Networks for Bearing Fault Detection with Vibration Concepts","display_name":"Explaining Deep Neural Networks for Bearing Fault Detection with Vibration Concepts","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4386072512","doi":"https://doi.org/10.1109/indin51400.2023.10218170"},"language":"en","primary_location":{"id":"doi:10.1109/indin51400.2023.10218170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin51400.2023.10218170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 21st International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2310.11450","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029656956","display_name":"Thomas Decker","orcid":"https://orcid.org/0000-0003-3814-8775"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Thomas Decker","raw_affiliation_strings":["Ludwig Maximilians Universit&#x00E4;t,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Ludwig Maximilians Universit&#x00E4;t,Munich,Germany","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015228757","display_name":"Michael Lebacher","orcid":"https://orcid.org/0000-0003-2984-7451"},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Lebacher","raw_affiliation_strings":["Siemens AG,Munich,Germany","Siemens AG, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Siemens AG,Munich,Germany","institution_ids":["https://openalex.org/I1325886976"]},{"raw_affiliation_string":"Siemens AG, Munich, Germany","institution_ids":["https://openalex.org/I1325886976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076463529","display_name":"Volker Tresp","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Volker Tresp","raw_affiliation_strings":["Ludwig Maximilians Universit&#x00E4;t,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Ludwig Maximilians Universit&#x00E4;t,Munich,Germany","institution_ids":["https://openalex.org/I8204097"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029656956"],"corresponding_institution_ids":["https://openalex.org/I8204097"],"apc_list":null,"apc_paid":null,"fwci":0.3516,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65815518,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9595999717712402,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9564999938011169,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7574080228805542},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6981582045555115},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6971465945243835},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.614521861076355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6109341382980347},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.5864360928535461},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.5805603265762329},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.5724585652351379},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5255797505378723},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.506791889667511},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.46624794602394104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44257745146751404},{"id":"https://openalex.org/keywords/actuator","display_name":"Actuator","score":0.08448737859725952}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7574080228805542},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6981582045555115},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6971465945243835},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.614521861076355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6109341382980347},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.5864360928535461},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.5805603265762329},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.5724585652351379},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5255797505378723},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.506791889667511},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.46624794602394104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44257745146751404},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.08448737859725952},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/indin51400.2023.10218170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin51400.2023.10218170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 21st International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2310.11450","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.11450","pdf_url":"https://arxiv.org/pdf/2310.11450","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2310.11450","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.11450","pdf_url":"https://arxiv.org/pdf/2310.11450","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386072512.pdf"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W243674440","https://openalex.org/W1964511482","https://openalex.org/W1974543974","https://openalex.org/W2112796928","https://openalex.org/W2194775991","https://openalex.org/W2219903032","https://openalex.org/W2282821441","https://openalex.org/W2306372667","https://openalex.org/W2516809705","https://openalex.org/W2530133016","https://openalex.org/W2618530766","https://openalex.org/W2791694051","https://openalex.org/W2962862931","https://openalex.org/W2963446712","https://openalex.org/W2963483561","https://openalex.org/W2970030610","https://openalex.org/W2979966119","https://openalex.org/W2981731882","https://openalex.org/W3009370740","https://openalex.org/W3085380432","https://openalex.org/W3094502228","https://openalex.org/W3112579230","https://openalex.org/W3135963926","https://openalex.org/W3167694779","https://openalex.org/W4221151022","https://openalex.org/W4224312241","https://openalex.org/W4281796627","https://openalex.org/W4285211372","https://openalex.org/W4288091267","https://openalex.org/W4296957138","https://openalex.org/W4298061300","https://openalex.org/W4312677365","https://openalex.org/W4320341247","https://openalex.org/W4372260222","https://openalex.org/W6728255800","https://openalex.org/W6737947904","https://openalex.org/W6748218292","https://openalex.org/W6750391026","https://openalex.org/W6764462969","https://openalex.org/W6774576976","https://openalex.org/W6783213970","https://openalex.org/W6784333009","https://openalex.org/W6796358590","https://openalex.org/W6809809157","https://openalex.org/W6849944227"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2035937180","https://openalex.org/W3196220745","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128"],"abstract_inverted_index":{"Concept-based":[0],"explanation":[1,69],"methods,":[2],"such":[3],"as":[4,38],"Concept":[5],"Activation":[6],"Vectors,":[7],"are":[8,88],"potent":[9],"means":[10],"to":[11,32,45,65,105,140],"quantify":[12],"how":[13,44,64],"abstract":[14],"or":[15],"high-level":[16],"characteristics":[17],"of":[18,24,74,98,111,123],"input":[19],"data":[20,57],"influence":[21],"the":[22,72,96,136],"predictions":[23],"complex":[25],"deep":[26,79],"neural":[27,80],"networks.":[28],"However,":[29],"applying":[30],"them":[31],"industrial":[33,112],"prediction":[34],"problems":[35],"is":[36,40,103],"challenging":[37],"it":[39],"not":[41],"immediately":[42],"clear":[43],"define":[46],"and":[47,55,109,128],"access":[48],"appropriate":[49],"concepts":[50,125],"for":[51],"individual":[52],"use":[53],"cases":[54],"specific":[56],"types.":[58],"In":[59],"this":[60],"work,":[61],"we":[62],"investigate":[63],"leverage":[66],"established":[67],"concept-based":[68],"techniques":[70],"in":[71,90,121],"context":[73],"bearing":[75],"fault":[76,100],"detection":[77,101],"with":[78],"networks":[81],"trained":[82],"on":[83],"vibration":[84,124],"signals.":[85],"Since":[86],"bearings":[87],"prevalent":[89],"almost":[91],"every":[92],"rotating":[93],"equipment,":[94],"ensuring":[95],"reliability":[97],"intransparent":[99],"models":[102,120],"crucial":[104],"prevent":[106],"costly":[107],"repairs":[108],"downtimes":[110],"machinery.":[113],"Our":[114],"evaluations":[115],"demonstrate":[116],"that":[117],"explaining":[118],"opaque":[119],"terms":[122],"enables":[126],"human-comprehensible":[127],"intuitive":[129],"insights":[130],"about":[131],"their":[132],"inner":[133],"workings,":[134],"but":[135],"underlying":[137],"assumptions":[138],"need":[139],"be":[141],"carefully":[142],"validated":[143],"first.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2023-08-23T00:00:00"}
