{"id":"https://openalex.org/W4414040887","doi":"https://doi.org/10.1109/ieeeconf65522.2025.11137332","title":"An Insulator Defect Detection Method Based on the Integration of RF-DETR and LLM","display_name":"An Insulator Defect Detection Method Based on the Integration of RF-DETR and LLM","publication_year":2025,"publication_date":"2025-07-11","ids":{"openalex":"https://openalex.org/W4414040887","doi":"https://doi.org/10.1109/ieeeconf65522.2025.11137332"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf65522.2025.11137332","doi":"https://doi.org/10.1109/ieeeconf65522.2025.11137332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf65522.2025.11137332","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 26th China Conference on System Simulation Technology and its Applications (CCSSTA)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5005107218","display_name":"Jiaxuan Zhou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxuan Zhou","raw_affiliation_strings":["School of Information Science and Technology, University of Science and Technology of China,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, University of Science and Technology of China,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100615339","display_name":"Zhendong Sun","orcid":"https://orcid.org/0000-0003-0622-6652","observed_orcids":["https://orcid.org/0000-0003-0622-6652"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhendong Sun","raw_affiliation_strings":["School of Information Science and Technology, University of Science and Technology of China,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, University of Science and Technology of China,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035542752","display_name":"Yujie Wang","orcid":"https://orcid.org/0000-0001-5722-2673","observed_orcids":["https://orcid.org/0000-0001-5722-2673"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Wang","raw_affiliation_strings":["School of Information Science and Technology, University of Science and Technology of China,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, University of Science and Technology of China,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":3.8557,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91676466,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"12","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13715","display_name":"Power Line Inspection Robots","score":0.9916999936103821,"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/T13715","display_name":"Power Line Inspection Robots","score":0.9916999936103821,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.002899999963119626,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.0015999999595806003,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/insulator-defect-detection","display_name":"insulator defect detection","score":0.9990000128746033},{"id":"https://openalex.org/keywords/rf-detr","display_name":"RF-DETR","score":0.9919999837875366},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9589999914169312},{"id":"https://openalex.org/keywords/object-detection","display_name":"object detection","score":0.7519999742507935},{"id":"https://openalex.org/keywords/transformer-based-detection","display_name":"transformer-based detection","score":0.6959999799728394},{"id":"https://openalex.org/keywords/power-system-inspection","display_name":"power system inspection","score":0.8159999847412109},{"id":"https://openalex.org/keywords/smart-grid","display_name":"smart grid","score":0.7490000128746033},{"id":"https://openalex.org/keywords/defect-localization","display_name":"defect localization","score":0.30799999833106995}],"concepts":[{"id":"https://openalex.org/C212702","wikidata":"https://www.wikidata.org/wiki/Q178150","display_name":"Insulator (electricity)","level":2,"score":0.6215999722480774},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5199000239372253},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5038999915122986},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4986000061035156},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4788999855518341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4634999930858612},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.3928000032901764},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.36809998750686646},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36309999227523804},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.35249999165534973},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30239999294281006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2946999967098236},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2906999886035919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2782000005245209},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf65522.2025.11137332","doi":"https://doi.org/10.1109/ieeeconf65522.2025.11137332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf65522.2025.11137332","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 26th China Conference on System Simulation Technology and its Applications (CCSSTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8970999717712402,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"},{"score":0.8485000133514404,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2743706233","https://openalex.org/W3036934147","https://openalex.org/W3202448246","https://openalex.org/W4372347372","https://openalex.org/W4385988359","https://openalex.org/W4386501105","https://openalex.org/W4402754006","https://openalex.org/W4403587121","https://openalex.org/W4405029557"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4404995717","https://openalex.org/W2016187641","https://openalex.org/W4404725684","https://openalex.org/W4413159334","https://openalex.org/W4246450666","https://openalex.org/W4388998267","https://openalex.org/W4409278740"],"abstract_inverted_index":{"This":[0,94],"paper":[1],"presents":[2],"a":[3,21,97],"novel":[4],"method":[5,82],"for":[6,100],"insulator":[7,75],"defect":[8,54],"detection":[9,24,55,70,76],"through":[10],"the":[11,28,49,74,80,101,114],"integration":[12],"of":[13,38,53,103,116],"RF-DETR":[14],"and":[15,40,51,61,67,86,106],"large":[16],"language":[17],"models":[18],"(LLMs).":[19],"RF-DETR,":[20],"real-time":[22],"object":[23],"model":[25],"based":[26],"on":[27,73],"Transformer":[29],"architecture,":[30],"demonstrates":[31],"high":[32,84],"effectiveness":[33],"in":[34,108],"extracting":[35],"visual":[36],"features":[37],"insulators":[39],"potential":[41],"defects.":[42],"The":[43],"combination":[44],"with":[45],"LLMs":[46,107],"significantly":[47],"enhances":[48],"accuracy":[50],"reliability":[52],"by":[56],"leveraging":[57],"their":[58],"extensive":[59],"knowledge":[60],"text":[62],"generation":[63],"capabilities":[64],"to":[65,113],"analyze":[66],"optimize":[68],"RF-DETR's":[69],"results.":[71],"Experiments":[72],"dataset":[77],"show":[78],"that":[79],"proposed":[81],"achieves":[83],"precision":[85],"recall":[87],"rates,":[88],"outperforming":[89],"traditional":[90],"manual":[91],"inspection":[92],"methods.":[93],"study":[95],"provides":[96],"promising":[98],"direction":[99],"application":[102],"deep":[104],"learning":[105],"power":[109,118],"system":[110],"inspection,":[111],"contributing":[112],"development":[115],"intelligent":[117],"grids.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2025-10-10T00:00:00"}