{"id":"https://openalex.org/W4409475283","doi":"https://doi.org/10.1109/iceaai64185.2025.10956799","title":"Research on Model Matching and Anomaly Detection Method of Distribution Network Equipment Based on OCR and Image Recognition","display_name":"Research on Model Matching and Anomaly Detection Method of Distribution Network Equipment Based on OCR and Image Recognition","publication_year":2025,"publication_date":"2025-01-10","ids":{"openalex":"https://openalex.org/W4409475283","doi":"https://doi.org/10.1109/iceaai64185.2025.10956799"},"language":"en","primary_location":{"id":"doi:10.1109/iceaai64185.2025.10956799","doi":"https://doi.org/10.1109/iceaai64185.2025.10956799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceaai64185.2025.10956799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Electrical Automation and Artificial Intelligence (ICEAAI)","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/A5101003795","display_name":"Juan Bai","orcid":"https://orcid.org/0000-0001-7761-9854","observed_orcids":["https://orcid.org/0000-0001-7761-9854","https://orcid.org/0000-0003-0061-0469"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Juan Bai","raw_affiliation_strings":["Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhenjun Xie","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenjun Xie","raw_affiliation_strings":["Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100429546","display_name":"Chang Li","orcid":"https://orcid.org/0000-0003-2406-7085","observed_orcids":["https://orcid.org/0000-0003-2406-7085"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang Li","raw_affiliation_strings":["Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shulei Feng","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shulei Feng","raw_affiliation_strings":["Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016627749","display_name":"Yu Zou","orcid":"https://orcid.org/0009-0001-2575-5261","observed_orcids":["https://orcid.org/0009-0001-2575-5261"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu Zou","raw_affiliation_strings":["Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qinzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd,Qinzhou,Guangxi,535000","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10883639,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"139","last_page":"143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13715","display_name":"Power Line Inspection Robots","score":0.5443999767303467,"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":0.5443999767303467,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.12399999797344208,"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"}},{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.10270000249147415,"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/distribution-network-equipment","display_name":"distribution network equipment","score":0.968999981880188},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"anomaly detection","score":0.9900000095367432},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"optical character recognition","score":0.9620000123977661},{"id":"https://openalex.org/keywords/image-recognition","display_name":"image recognition","score":0.8119999766349792},{"id":"https://openalex.org/keywords/construction-quality-inspection","display_name":"construction quality inspection","score":0.7400000095367432}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.676694393157959},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.649644136428833},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6053482294082642},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5875601768493652},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5582134127616882},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5465965867042542},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5020840167999268},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.4693366587162018},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45195215940475464},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.43358302116394043},{"id":"https://openalex.org/C2987247673","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Character recognition","level":3,"score":0.41904258728027344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13993048667907715},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09290632605552673},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iceaai64185.2025.10956799","doi":"https://doi.org/10.1109/iceaai64185.2025.10956799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceaai64185.2025.10956799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Electrical Automation and Artificial Intelligence (ICEAAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":1.0,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W3205058276","https://openalex.org/W4229044824","https://openalex.org/W4389308150","https://openalex.org/W4393396137","https://openalex.org/W4404826346"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"The":[0,168],"acceptance":[1,191],"work":[2],"of":[3,16,30,76,129,137,163,194],"distribution":[4,17,32,40,78,92,195],"network":[5,18,41,93,196],"engineering":[6,19,42,165],"lines":[7,20],"is":[8,112],"an":[9],"important":[10,185],"link":[11],"to":[12,54,72,124],"ensure":[13],"the":[14,24,31,73,77,126,130,138,159,189],"quality":[15,166],"and":[21,26,47,64,87,98,109,134,151,161,178,192],"effectively":[22,157],"improve":[23,158],"safe":[25,74],"stable":[27],"operation":[28,75],"level":[29],"network.":[33,79],"However,":[34],"traditional":[35],"on-site":[36],"verification":[37],"methods":[38],"for":[39,91,188],"suffer":[43],"from":[44],"time-consuming,":[45],"labor-intensive,":[46],"error":[48],"prone":[49],"issues,":[50],"making":[51],"it":[52],"difficult":[53],"efficiently":[55],"identify":[56],"potential":[57],"hazards":[58],"such":[59],"as":[60],"construction":[61],"process":[62],"defects":[63],"equipment":[65,94,107,139],"model":[66,85,140],"mismatches,":[67],"which":[68,155],"pose":[69],"a":[70,84],"threat":[71],"Therefore,":[80],"this":[81,173],"article":[82],"proposes":[83],"matching":[86,133,153],"anomaly":[88,135],"detection":[89,136],"method":[90,145,174],"based":[95],"on":[96,106],"OCR":[97,116],"image":[99,121,147],"recognition":[100,122],"technology.":[101],"Firstly,":[102],"key":[103],"text":[104],"information":[105],"nameplates":[108],"identification":[110],"plates":[111],"automatically":[113],"extracted":[114],"through":[115],"technology;":[117],"Secondly,":[118],"by":[119],"combining":[120],"models":[123],"analyze":[125],"appearance":[127],"characteristics":[128],"equipment,":[131],"precise":[132],"can":[141,156],"be":[142],"achieved.":[143],"This":[144],"integrates":[146],"processing,":[148],"deep":[149],"learning,":[150],"database":[152],"techniques,":[154],"efficiency":[160],"accuracy":[162],"line":[164],"acceptance.":[167],"experimental":[169],"results":[170],"show":[171],"that":[172],"has":[175],"good":[176],"robustness":[177],"practicality":[179],"in":[180],"various":[181],"complex":[182],"scenarios,":[183],"providing":[184],"technical":[186],"support":[187],"intelligent":[190],"management":[193],"engineering.":[197]},"counts_by_year":[],"updated_date":"2026-09-24T07:57:37.273135","created_date":"2025-10-10T00:00:00"}
