{"id":"https://openalex.org/W3085542849","doi":"https://doi.org/10.23919/ccc50068.2020.9188778","title":"The Study on The Application of BP Neural Network Based on Genetic Algorithm Optimization in Magnetic Flux Leakage (MFL) of Rail Top Surface Stripping Defects","display_name":"The Study on The Application of BP Neural Network Based on Genetic Algorithm Optimization in Magnetic Flux Leakage (MFL) of Rail Top Surface Stripping Defects","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3085542849","doi":"https://doi.org/10.23919/ccc50068.2020.9188778","mag":"3085542849"},"language":"en","primary_location":{"id":"doi:10.23919/ccc50068.2020.9188778","doi":"https://doi.org/10.23919/ccc50068.2020.9188778","is_oa":false,"landing_page_url":"https://doi.org/10.23919/ccc50068.2020.9188778","pdf_url":null,"source":{"id":"https://openalex.org/S4363607703","display_name":"Chinese Control Conference (CCC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 39th Chinese Control Conference (CCC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5058561733","display_name":"Wendong Gong","orcid":"https://orcid.org/0000-0002-6028-8857","observed_orcids":["https://orcid.org/0000-0002-6028-8857"]},"institutions":[{"id":"https://openalex.org/I4405282488","display_name":"Shandong Polytechnic","ror":"https://ror.org/05xc6df26","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096525","https://openalex.org/I4387155179","https://openalex.org/I4405282488"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wendong Gong","raw_affiliation_strings":["Shandong Polytechnics, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Polytechnics, Jinan, China","institution_ids":["https://openalex.org/I4405282488"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101621940","display_name":"Yuliang Lin","orcid":"https://orcid.org/0000-0002-8029-0559","observed_orcids":["https://orcid.org/0000-0002-8029-0559"]},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuliang Lin","raw_affiliation_strings":["School of Mechanical Engineering, Tiangong University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6078,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53016999,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":93},"biblio":{"volume":"2020","issue":null,"first_page":"7554","last_page":"7557"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9980000257492065,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9980000257492065,"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.0003000000142492354,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/magnetic-flux-leakage","display_name":"magnetic flux leakage","score":0.9589999914169312},{"id":"https://openalex.org/keywords/permanent-magnet-excitation","display_name":"permanent magnet excitation","score":0.878000020980835},{"id":"https://openalex.org/keywords/geometric-feature-extraction","display_name":"geometric feature extraction","score":0.8510000109672546},{"id":"https://openalex.org/keywords/back-propagation-neural-network","display_name":"BP neural network","score":0.8460000157356262},{"id":"https://openalex.org/keywords/genetic-algorithm-optimization","display_name":"genetic algorithm optimization","score":0.9679999947547913},{"id":"https://openalex.org/keywords/railway-track-inspection","display_name":"railway track inspection","score":0.5669999718666077}],"concepts":[{"id":"https://openalex.org/C20892748","wikidata":"https://www.wikidata.org/wiki/Q4390394","display_name":"Magnetic flux leakage","level":3,"score":0.8021535277366638},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5763323903083801},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.5593426823616028},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5500805974006653},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.5390272736549377},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.5024359226226807},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4618794620037079},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.43472376465797424},{"id":"https://openalex.org/C157479481","wikidata":"https://www.wikidata.org/wiki/Q177831","display_name":"Magnetic flux","level":3,"score":0.4242076873779297},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3922070264816284},{"id":"https://openalex.org/C16389437","wikidata":"https://www.wikidata.org/wiki/Q11421","display_name":"Magnet","level":2,"score":0.38090017437934875},{"id":"https://openalex.org/C115260700","wikidata":"https://www.wikidata.org/wiki/Q11408","display_name":"Magnetic field","level":2,"score":0.3436778783798218},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3375580906867981},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3355160355567932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.329577773809433},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.2187044322490692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18143311142921448},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13273891806602478},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.11858201026916504},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"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/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/ccc50068.2020.9188778","doi":"https://doi.org/10.23919/ccc50068.2020.9188778","is_oa":false,"landing_page_url":"https://doi.org/10.23919/ccc50068.2020.9188778","pdf_url":null,"source":{"id":"https://openalex.org/S4363607703","display_name":"Chinese Control Conference (CCC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 39th Chinese Control Conference (CCC)","raw_type":"proceedings-article"},{"id":"mag:3174782272","doi":null,"is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/detail?JGLOBAL_ID=202002227665990246","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4943999946117401}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1979373126","https://openalex.org/W2130372754","https://openalex.org/W2144658323","https://openalex.org/W2160276773","https://openalex.org/W2553446265","https://openalex.org/W2643702530","https://openalex.org/W2759796772","https://openalex.org/W2808808447","https://openalex.org/W2908588591","https://openalex.org/W2925329204","https://openalex.org/W2954593662"],"related_works":["https://openalex.org/W4379982039","https://openalex.org/W2387695217","https://openalex.org/W2358586775","https://openalex.org/W4381892628","https://openalex.org/W2562329809","https://openalex.org/W7096798867","https://openalex.org/W2111334394","https://openalex.org/W2378715402","https://openalex.org/W4361216643","https://openalex.org/W7128031617"],"abstract_inverted_index":{"The":[0,75,102,126],"stripping":[1],"defect":[2,119,149],"of":[3,18,51,78,118,133,151],"rail":[4,23,73,152],"top":[5,153],"surface":[6,154],"seriously":[7],"affects":[8],"the":[9,15,19,40,48,52,79,115,131,138,148],"safety.":[10],"In":[11],"order":[12],"to":[13,46,66,113],"predict":[14],"accurate":[16],"size":[17],"defect,":[20],"firstly,":[21],"a":[22],"MFL":[24],"car":[25],"with":[26],"3D-":[27],"Magnetic":[28],"sensor":[29,63],"is":[30],"designed,":[31],"and":[32,61,97,121,137],"rectangular":[33,124],"pit":[34],"defects":[35,155],"are":[36,44,64],"artificially":[37],"manufactured":[38],"on":[39,58,107],"rail.":[41,53],"Permanent":[42],"magnets":[43],"used":[45,65,112],"excitation":[47],"detection":[49],"area":[50],"Data":[54],"acquisition":[55],"device":[56],"based":[57,106],"ARM":[59],"microcontroller":[60],"3D-Magnetic":[62],"detect":[67],"magnetic":[68,82],"leakage":[69,83],"signals":[70],"generated":[71],"by":[72,143],"defects.":[74],"geometric":[76,134],"features":[77],"3D":[80],"main":[81],"signal":[84],"curve,":[85],"such":[86],"as":[87],"peak":[88],"height,":[89],"waveform":[90],"width,":[91,99],"envelope":[92],"area,":[93],"perimeter,":[94],"graph":[95],"centroid":[96],"peak-valley":[98],"were":[100],"extracted.":[101],"BP":[103,139],"neural":[104,140],"network":[105,141],"genetic":[108,144],"algorithm":[109,145],"optimization":[110],"was":[111],"establish":[114],"prediction":[116],"model":[117],"diameter":[120],"depth":[122],"in":[123],"pits.":[125],"experimental":[127],"results":[128],"show":[129],"that":[130],"method":[132],"eigenvalue":[135],"extraction":[136],"optimized":[142],"can":[146],"realize":[147],"quantification":[150],"accurately.":[156]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2020-09-21T00:00:00"}