{"id":"https://openalex.org/W7152121361","doi":"https://doi.org/10.48550/arxiv.2604.05863","title":"LoRM: Learning the Language of Rotating Machinery for Self-Supervised Condition Monitoring","display_name":"LoRM: Learning the Language of Rotating Machinery for Self-Supervised Condition Monitoring","publication_year":2026,"publication_date":"2026-04-07","ids":{"openalex":"https://openalex.org/W7152121361","doi":"https://doi.org/10.48550/arxiv.2604.05863"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.05863","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05863","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.05863","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133192888","display_name":"Xiao Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133169064","display_name":"Xingyi Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Xingyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133164412","display_name":"Tong Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Tong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087382979","display_name":"Hatim Laalej","orcid":"https://orcid.org/0000-0002-4130-839X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laalej, Hatim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121991375","display_name":"Zepeng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zepeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133204462","display_name":"Yunpeng Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Yunpeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5121111809","display_name":"Ligang He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Ligang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.4690000116825104,"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":0.4690000116825104,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.04780000075697899,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.044599998742341995,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.7389000058174133},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5791000127792358},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5730999708175659},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5576000213623047},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4528999924659729},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.44190001487731934},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.426800012588501}],"concepts":[{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.7389000058174133},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5791000127792358},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5764999985694885},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5730999708175659},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5576000213623047},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4528999924659729},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.44190001487731934},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.426800012588501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4025999903678894},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3855000138282776},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3612000048160553},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3239000141620636},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.31929999589920044},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.31769999861717224},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C2776902269","wikidata":"https://www.wikidata.org/wiki/Q5165493","display_name":"Continuous monitoring","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.29100000858306885},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27309998869895935},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26460000872612},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.263700008392334}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.05863","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05863","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.05863","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05863","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"LoRM":[2,19,66,165],"(Language":[3],"of":[4,94],"Rotating":[5],"Machinery),":[6],"a":[7,32,72,101,113,126,141,167],"self-supervised":[8],"framework":[9],"for":[10],"multi-modal":[11,68],"rotating-machinery":[12,26],"signal":[13,175],"understanding":[14],"and":[15,44,64,159,173],"real-time":[16,157],"condition":[17,132,151],"monitoring.":[18],"is":[20,84,98,108,134,180],"built":[21],"on":[22,61,118],"the":[23,80,90,122],"idea":[24],"that":[25,59,164],"signals":[27,36],"can":[28,37,48],"be":[29,38,49],"viewed":[30],"as":[31,71,140],"machine":[33],"language:":[34],"local":[35],"tokenised":[39],"into":[40,100],"discrete":[41,102],"symbolic":[42],"units,":[43],"their":[45],"future":[46,91],"evolution":[47],"predicted":[50],"from":[51,129],"observed":[52,81],"multi-sensor":[53],"context.":[54],"Unlike":[55],"conventional":[56],"signal-processing":[57],"methods":[58],"rely":[60],"hand-crafted":[62],"transforms":[63],"features,":[65],"reformulates":[67],"sensor":[69],"data":[70,78],"token-based":[73],"sequence-prediction":[74],"problem.":[75],"For":[76],"each":[77,95],"window,":[79],"context":[82],"segment":[83,93],"retained":[85],"in":[86],"continuous":[87],"form,":[88],"while":[89],"target":[92],"sensing":[96],"channel":[97],"quantised":[99],"token.":[103],"Then,":[104],"efficient":[105],"knowledge":[106],"transfer":[107],"achieved":[109],"by":[110,136],"partially":[111],"fine-tuning":[112],"general-purpose":[114],"pre-trained":[115],"language":[116,171],"model":[117,128],"industrial":[119,174],"signals,":[120],"avoiding":[121],"need":[123],"to":[124],"train":[125],"large":[127],"scratch.":[130],"Finally,":[131],"monitoring":[133,152],"performed":[135],"tracking":[137,158],"token-prediction":[138],"errors":[139,146],"health":[142],"indicator,":[143],"where":[144],"increasing":[145],"indicate":[147],"degradation.":[148],"In-situ":[149],"tool":[150],"(TCM)":[153],"experiments":[154],"demonstrate":[155],"stable":[156],"strong":[160],"cross-tool":[161],"generalisation,":[162],"showing":[163],"provides":[166],"practical":[168],"bridge":[169],"between":[170],"modelling":[172],"analysis.":[176],"The":[177],"source":[178],"code":[179],"publicly":[181],"available":[182],"at":[183],"https://github.com/Q159753258/LormPHM.":[184]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-09T00:00:00"}
