{"id":"https://openalex.org/W1596971285","doi":null,"title":"POWER SYSTEM FAULT DETECTION AND CLASSIFICATION BY WAVELET TRANSFORMS AND ADAPTIVE RESONANCE THEORY NEURAL NETWORKS","display_name":"POWER SYSTEM FAULT DETECTION AND CLASSIFICATION BY WAVELET TRANSFORMS AND ADAPTIVE RESONANCE THEORY NEURAL NETWORKS","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W1596971285","mag":"1596971285"},"language":"en","primary_location":{"id":"pmh:oai:uknowledge.uky.edu:gradschool_theses-1455","doi":null,"is_oa":true,"landing_page_url":"https://uknowledge.uky.edu/gradschool_theses/452","pdf_url":"https://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1455&context=gradschool_theses","source":{"id":"https://openalex.org/S4306402623","display_name":"UKnowledge (University of Kentucky)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I143302722","host_organization_name":"University of Kentucky","host_organization_lineage":["https://openalex.org/I143302722"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"University of Kentucky Master's Theses","raw_type":"text"},"parent_works":[],"lineage":["https://openalex.org/W1596971285"],"child_works_count":0,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1455&context=gradschool_theses","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044677192","display_name":"Karthikeyan Kasinathan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Karthikeyan Kasinathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5044677192"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":5,"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/T10972","display_name":"Power Systems Fault Detection","score":0.9945999979972839,"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/T10972","display_name":"Power Systems Fault Detection","score":0.9945999979972839,"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/T12737","display_name":"Electrical Fault Detection and Protection","score":0.002199999988079071,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.0010000000474974513,"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/power-system-fault-detection","display_name":"power system fault detection","score":0.9850000143051147},{"id":"https://openalex.org/keywords/fault-classification","display_name":"fault classification","score":0.8830000162124634},{"id":"https://openalex.org/keywords/transmission-line-faults","display_name":"transmission line faults","score":0.9760000109672546},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"discrete wavelet transform","score":0.9980000257492065},{"id":"https://openalex.org/keywords/adaptive-resonance-theory","display_name":"adaptive resonance theory","score":0.8529999852180481},{"id":"https://openalex.org/keywords/unsupervised-neural-networks","display_name":"unsupervised neural networks","score":0.8119999766349792},{"id":"https://openalex.org/keywords/self-organizing-neural-networks","display_name":"self-organizing neural networks","score":0.8880000114440918},{"id":"https://openalex.org/keywords/large-data-sets","display_name":"large data sets","score":0.4740000069141388},{"id":"https://openalex.org/keywords/fault-simulation","display_name":"fault simulation","score":0.4970000088214874}],"concepts":[{"id":"https://openalex.org/C115755159","wikidata":"https://www.wikidata.org/wiki/Q352487","display_name":"Adaptive resonance theory","level":3,"score":0.8317347168922424},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6925246119499207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6032831072807312},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5750066637992859},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.5540421009063721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5224484801292419},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5174692273139954},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5064762830734253},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4415460228919983},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.425533652305603},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4251047670841217},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3786408305168152},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"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/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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":3,"locations":[{"id":"pmh:oai:uknowledge.uky.edu:gradschool_theses-1455","doi":null,"is_oa":true,"landing_page_url":"https://uknowledge.uky.edu/gradschool_theses/452","pdf_url":"https://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1455&context=gradschool_theses","source":{"id":"https://openalex.org/S4306402623","display_name":"UKnowledge (University of Kentucky)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I143302722","host_organization_name":"University of Kentucky","host_organization_lineage":["https://openalex.org/I143302722"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"University of Kentucky Master's Theses","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.634.1115","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.634.1115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://lib.uky.edu/ETD/ukycosc2006t00549/Karthik_Thesis.pdf","raw_type":"text"},{"id":"mag:1596971285","doi":null,"is_oa":false,"landing_page_url":"https://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1455&context=gradschool_theses","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:uknowledge.uky.edu:gradschool_theses-1455","doi":null,"is_oa":true,"landing_page_url":"https://uknowledge.uky.edu/gradschool_theses/452","pdf_url":"https://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1455&context=gradschool_theses","source":{"id":"https://openalex.org/S4306402623","display_name":"UKnowledge (University of Kentucky)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I143302722","host_organization_name":"University of Kentucky","host_organization_lineage":["https://openalex.org/I143302722"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"University of Kentucky Master's Theses","raw_type":"text"},"sustainable_development_goals":[{"score":0.428600013256073,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1596971285.pdf","grobid_xml":"https://content.openalex.org/works/W1596971285.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1541274513","https://openalex.org/W1679800570","https://openalex.org/W1986622592","https://openalex.org/W2000868189","https://openalex.org/W2004075725","https://openalex.org/W2012611887","https://openalex.org/W2015857587","https://openalex.org/W2028896432","https://openalex.org/W2084635683","https://openalex.org/W2100434867","https://openalex.org/W2111297697","https://openalex.org/W2122111042","https://openalex.org/W2138045323","https://openalex.org/W2144219012","https://openalex.org/W2144691177","https://openalex.org/W2157354887","https://openalex.org/W2165993471","https://openalex.org/W2423377521"],"related_works":["https://openalex.org/W1976335302","https://openalex.org/W2596104194","https://openalex.org/W2953689438","https://openalex.org/W2239860324","https://openalex.org/W7099071049","https://openalex.org/W2886478675","https://openalex.org/W2548621044","https://openalex.org/W2188972856","https://openalex.org/W2184620314","https://openalex.org/W2314459801"],"abstract_inverted_index":{"This":[0],"thesis":[1],"aims":[2],"at":[3],"detecting":[4],"and":[5,46,69,96],"classifying":[6],"the":[7,16,70,80,88,106],"power":[8],"system":[9],"transmission":[10],"line":[11],"faults.":[12],"To":[13],"deal":[14],"with":[15,24,79],"problem":[17],"of":[18,50,72,98],"an":[19],"extremely":[20],"large":[21,92],"data":[22,93],"set":[23],"different":[25,48],"fault":[26,61],"situations,":[27],"a":[28],"three":[29],"step":[30],"optimized":[31],"Neural":[32,56],"Network":[33],"approach":[34,39],"has":[35],"been":[36],"proposed.":[37],"The":[38,60,83],"utilizes":[40],"Discrete":[41],"Wavelet":[42],"Transform":[43],"for":[44,58],"detection":[45],"two":[47],"types":[49],"self-organized,":[51],"unsupervised":[52],"Adaptive":[53],"Resonance":[54],"Theory":[55],"Networks":[57],"classification.":[59],"scenarios":[62],"are":[63],"simulated":[64],"using":[65],"Alternate":[66],"Transients":[67],"Program":[68],"performance":[71],"this":[73],"highly":[74],"improved":[75],"scheme":[76],"is":[77,100],"compared":[78,104],"existing":[81,107],"techniques.":[82],"simulation":[84],"results":[85],"prove":[86],"that":[87],"proposed":[89],"technique":[90],"handles":[91],"more":[94],"efficiently":[95],"time":[97],"operation":[99],"considerably":[101],"less":[102],"when":[103],"to":[105],"methods.":[108]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2016-06-24T00:00:00"}