{"id":"https://openalex.org/W7076053525","doi":"https://doi.org/10.1109/tsg.2025.3599262","title":"Power-SAM: An Advanced Abnormality Change Detection Algorithm for Intelligent Monitoring in Power Equipment","display_name":"Power-SAM: An Advanced Abnormality Change Detection Algorithm for Intelligent Monitoring in Power Equipment","publication_year":2025,"publication_date":"2025-08-15","ids":{"openalex":"https://openalex.org/W7076053525","doi":"https://doi.org/10.1109/tsg.2025.3599262"},"language":"en","primary_location":{"id":"doi:10.1109/tsg.2025.3599262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2025.3599262","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Smart Grid","raw_type":"journal-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":null,"display_name":"Chengming Song","orcid":"https://orcid.org/0009-0007-3277-9556"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengming Song","raw_affiliation_strings":["School of Computer Science and Control Engineering, Yantai University, Yantai, China"],"raw_orcid":"https://orcid.org/0009-0007-3277-9556","affiliations":[{"raw_affiliation_string":"School of Computer Science and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lingzhi Wu","orcid":"https://orcid.org/0009-0004-9427-907X"},"institutions":[{"id":"https://openalex.org/I4210091069","display_name":"Dongfang Electric Corporation (China)","ror":"https://ror.org/00az85j53","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091069"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingzhi Wu","raw_affiliation_strings":["Smart Vision Business Unit, Dongfang Electronics Company Ltd., Yantai, China"],"raw_orcid":"https://orcid.org/0009-0004-9427-907X","affiliations":[{"raw_affiliation_string":"Smart Vision Business Unit, Dongfang Electronics Company Ltd., Yantai, China","institution_ids":["https://openalex.org/I4210091069"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bo Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091069","display_name":"Dongfang Electric Corporation (China)","ror":"https://ror.org/00az85j53","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091069"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Gao","raw_affiliation_strings":["Smart Vision Business Unit, Dongfang Electronics Company Ltd., Yantai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Smart Vision Business Unit, Dongfang Electronics Company Ltd., Yantai, China","institution_ids":["https://openalex.org/I4210091069"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhendong Cui","orcid":"https://orcid.org/0000-0002-5503-1336"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhendong Cui","raw_affiliation_strings":["School of Computer Science and Control Engineering, Yantai University, Yantai, China"],"raw_orcid":"https://orcid.org/0000-0002-5503-1336","affiliations":[{"raw_affiliation_string":"School of Computer Science and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.4286233,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"6","first_page":"5200","last_page":"5214"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10591","display_name":"Theoretical and Computational Physics","score":0.03929999843239784,"subfield":{"id":"https://openalex.org/subfields/3104","display_name":"Condensed Matter Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10591","display_name":"Theoretical and Computational Physics","score":0.03929999843239784,"subfield":{"id":"https://openalex.org/subfields/3104","display_name":"Condensed Matter Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12613","display_name":"X-ray Diffraction in Crystallography","score":0.02630000002682209,"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/T12579","display_name":"Muon and positron interactions and applications","score":0.024800000712275505,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/feature","display_name":"Feature (linguistics)","score":0.680899977684021},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6488000154495239},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6280999779701233},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5134000182151794},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4961000084877014},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.42250001430511475},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4178999960422516},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4090999960899353},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4058000147342682}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.722000002861023},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.680899977684021},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6488000154495239},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6280999779701233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5181999802589417},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5134000182151794},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4961000084877014},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.42250001430511475},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4178999960422516},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4090999960899353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4058000147342682},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.37599998712539673},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.365200012922287},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.3434999883174896},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.33250001072883606},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.33169999718666077},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3240000009536743},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29820001125335693},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C2778774385","wikidata":"https://www.wikidata.org/wiki/Q4437810","display_name":"Power management","level":3,"score":0.287200003862381},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.2768999934196472},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.2676999866962433},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26339998841285706},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2621999979019165}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsg.2025.3599262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2025.3599262","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Smart Grid","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47497275471687317,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1561412798","https://openalex.org/W1979261208","https://openalex.org/W2091741383","https://openalex.org/W2143106663","https://openalex.org/W2170140722","https://openalex.org/W2552406626","https://openalex.org/W2750746331","https://openalex.org/W2794771604","https://openalex.org/W2887843685","https://openalex.org/W2962858109","https://openalex.org/W3014080415","https://openalex.org/W3117492306","https://openalex.org/W3120467244","https://openalex.org/W3168608898","https://openalex.org/W3180045188","https://openalex.org/W4226228401","https://openalex.org/W4290043202","https://openalex.org/W4300179783","https://openalex.org/W4311849222","https://openalex.org/W4312549298","https://openalex.org/W4320001385","https://openalex.org/W4384393272","https://openalex.org/W4386299129","https://openalex.org/W4388399114","https://openalex.org/W4390874575","https://openalex.org/W4391892563","https://openalex.org/W4394595673","https://openalex.org/W4400081502","https://openalex.org/W4400410086","https://openalex.org/W4400418792"],"related_works":[],"abstract_inverted_index":{"Timely":[0],"detection":[1,26,151],"and":[2,12,46,128,158,184,191],"management":[3],"of":[4,15,51,169,187],"abnormalities":[5],"are":[6],"critical":[7],"to":[8,61,80,89,91,113,137,165],"ensuring":[9],"the":[10,16,42,52,72,110,167,170,178],"safe":[11],"stable":[13],"operation":[14],"smart":[17,34],"grid.":[18],"To":[19],"address":[20],"this,":[21],"a":[22,96],"novel":[23],"abnormal":[24],"change":[25,150],"(ACD)":[27],"model,":[28],"termed":[29],"Power-SAM,":[30,138],"is":[31],"proposed":[32,171],"for":[33,65,85,142,148],"grids":[35],"based":[36],"on":[37],"Artificial":[38],"Intelligence.":[39],"Firstly,":[40],"integrate":[41],"strong":[43],"generalization":[44],"capabilities":[45],"efficient":[47],"image":[48,146],"segmentation":[49],"performance":[50,141,168],"Segment":[53],"Anything":[54],"Model":[55],"(SAM)":[56],"while":[57],"employing":[58],"fine-tuning":[59],"strategies":[60],"enhance":[62],"its":[63],"applicability":[64],"processing":[66],"images":[67],"in":[68,117],"power":[69,92,118,156],"scenarios.":[70],"Secondly,":[71],"Time":[73],"Difference":[74],"Feature":[75,124],"Generator":[76],"(TDFG)":[77],"was":[78,107,135,152,163],"designed":[79],"generate":[81],"feature":[82,97,102],"vectors":[83],"suitable":[84],"ACD,":[86],"allowing":[87],"SAM":[88],"adapt":[90],"ACD":[93,140,159],"tasks.":[94],"Thirdly,":[95],"fusion":[98],"network,":[99],"which":[100],"combined":[101],"aggregation":[103],"with":[104],"differential":[105],"computation,":[106],"adopted,":[108],"enhancing":[109],"model\u2019s":[111],"ability":[112],"detect":[114],"subtle":[115],"changes":[116],"scenes.":[119],"Lastly,":[120],"CBAM-FPN":[121],"by":[122],"integrating":[123],"Pyramid":[125],"Network":[126],"(FPN)":[127],"lightweight":[129],"Convolutional":[130],"Block":[131],"Attention":[132],"Module":[133],"(CBAM)":[134],"introduced":[136],"improving":[139],"multiscale":[143],"targets.":[144],"An":[145],"dataset":[147,162],"substation":[149],"constructed":[153],"from":[154],"real-world":[155],"scenarios":[157],"requirements.":[160],"This":[161],"used":[164],"evaluate":[166],"Power-SAM":[172],"model.":[173],"The":[174],"results":[175],"demonstrate":[176],"that":[177],"algorithm":[179],"achieves":[180],"precision,":[181],"recall,":[182],"F1-score,":[183],"IoU":[185],"metrics":[186],"95.25%,":[188],"93.35%,":[189],"94.41%,":[190],"89.41%,":[192],"respectively,":[193],"outperforming":[194],"current":[195],"state-of-the-art":[196],"artificial":[197],"intelligence":[198],"models.":[199]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}