{"id":"https://openalex.org/W4399224472","doi":"https://doi.org/10.3390/s24113551","title":"Swing Trend Prediction of Main Guide Bearing in Hydropower Units Based on MFS-DCGNN","display_name":"Swing Trend Prediction of Main Guide Bearing in Hydropower Units Based on MFS-DCGNN","publication_year":2024,"publication_date":"2024-05-31","ids":{"openalex":"https://openalex.org/W4399224472","doi":"https://doi.org/10.3390/s24113551","pmid":"https://pubmed.ncbi.nlm.nih.gov/38894342"},"language":"en","primary_location":{"id":"doi:10.3390/s24113551","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24113551","pdf_url":"https://www.mdpi.com/1424-8220/24/11/3551/pdf?version=1717144821","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/24/11/3551/pdf?version=1717144821","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102127458","display_name":"Xu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Li","raw_affiliation_strings":["School of Water Resources and Hydroelectric Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China","School of Water Resources and Hydroelectric Engineering, Xi'an University of Technology, Xi'an 710048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Water Resources and Hydroelectric Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China","institution_ids":["https://openalex.org/I4210131919"]},{"raw_affiliation_string":"School of Water Resources and Hydroelectric Engineering, Xi'an University of Technology, Xi'an 710048, China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083567405","display_name":"Zhuofei Xu","orcid":"https://orcid.org/0000-0003-1477-7067"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuofei Xu","raw_affiliation_strings":["School of Water Resources and Hydroelectric Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China","School of Water Resources and Hydroelectric Engineering, Xi'an University of Technology, Xi'an 710048, China"],"raw_orcid":"https://orcid.org/0000-0003-1477-7067","affiliations":[{"raw_affiliation_string":"School of Water Resources and Hydroelectric Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China","institution_ids":["https://openalex.org/I4210131919"]},{"raw_affiliation_string":"School of Water Resources and Hydroelectric Engineering, Xi'an University of Technology, Xi'an 710048, China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056265693","display_name":"Pengcheng Guo","orcid":"https://orcid.org/0000-0002-1249-2300"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengcheng Guo","raw_affiliation_strings":["School of Water Resources and Hydroelectric Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China","School of Water Resources and Hydroelectric Engineering, Xi'an University of Technology, Xi'an 710048, China"],"raw_orcid":"https://orcid.org/0000-0002-1249-2300","affiliations":[{"raw_affiliation_string":"School of Water Resources and Hydroelectric Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China","institution_ids":["https://openalex.org/I4210131919"]},{"raw_affiliation_string":"School of Water Resources and Hydroelectric Engineering, Xi'an University of Technology, Xi'an 710048, China","institution_ids":["https://openalex.org/I4210131919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5083567405"],"corresponding_institution_ids":["https://openalex.org/I4210131919"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.0695,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7165949,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"24","issue":"11","first_page":"3551","last_page":"3551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11220","display_name":"Water Systems and Optimization","score":0.9646000266075134,"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"}},"topics":[{"id":"https://openalex.org/T11220","display_name":"Water Systems and Optimization","score":0.9646000266075134,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9549999833106995,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.942300021648407,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/swing","display_name":"Swing","score":0.6588482856750488},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.58458411693573},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5822864770889282},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.511816680431366},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.49253949522972107},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4785400331020355},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.45550820231437683},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3631897568702698},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35525965690612793},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1943112015724182},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16578137874603271},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.0917392373085022}],"concepts":[{"id":"https://openalex.org/C65655974","wikidata":"https://www.wikidata.org/wiki/Q14867674","display_name":"Swing","level":2,"score":0.6588482856750488},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.58458411693573},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5822864770889282},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.511816680431366},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.49253949522972107},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4785400331020355},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.45550820231437683},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3631897568702698},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35525965690612793},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1943112015724182},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16578137874603271},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0917392373085022},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s24113551","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24113551","pdf_url":"https://www.mdpi.com/1424-8220/24/11/3551/pdf?version=1717144821","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:38894342","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38894342","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11175333","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11175333","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11175333/pdf/sensors-24-03551.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:ac87b4ebe30b42faac710db7d62d63d2","is_oa":false,"landing_page_url":"https://doaj.org/article/ac87b4ebe30b42faac710db7d62d63d2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 24, Iss 11, p 3551 (2024)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/24/11/3551/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s24113551","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s24113551","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24113551","pdf_url":"https://www.mdpi.com/1424-8220/24/11/3551/pdf?version=1717144821","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5400000214576721,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G5170148704","display_name":null,"funder_award_id":"22JP057","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7199766794","display_name":null,"funder_award_id":"2020-29","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8698099601","display_name":"\u6c34\u529b\u88c5\u5907\u77ac\u6001\u8fc7\u7a0b\u975e\u7a33\u6001\u6d41\u52a8\u53ca\u5176\u8bf1\u53d1\u632f\u52a8\u95ee\u9898\u7814\u7a76","funder_award_id":"51839010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4399224472.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2260771218","https://openalex.org/W2342480889","https://openalex.org/W2473281166","https://openalex.org/W2591055632","https://openalex.org/W2604847698","https://openalex.org/W2756203131","https://openalex.org/W2788000335","https://openalex.org/W2801476357","https://openalex.org/W2890096158","https://openalex.org/W2898240335","https://openalex.org/W2908875359","https://openalex.org/W2997003477","https://openalex.org/W3006585575","https://openalex.org/W3007845852","https://openalex.org/W3034330439","https://openalex.org/W3039070036","https://openalex.org/W3044202631","https://openalex.org/W3045468192","https://openalex.org/W3047766662","https://openalex.org/W3082119399","https://openalex.org/W3103720336","https://openalex.org/W3108376771","https://openalex.org/W3164376315","https://openalex.org/W3206094308","https://openalex.org/W4205539737","https://openalex.org/W4211219607","https://openalex.org/W4229016799","https://openalex.org/W4315780025","https://openalex.org/W4383337188","https://openalex.org/W4392206294","https://openalex.org/W6692628530","https://openalex.org/W6780876565"],"related_works":["https://openalex.org/W2360051520","https://openalex.org/W2798244654","https://openalex.org/W3168108534","https://openalex.org/W34871393","https://openalex.org/W4206135463","https://openalex.org/W1486689224","https://openalex.org/W2094697992","https://openalex.org/W4229574949","https://openalex.org/W2368813785","https://openalex.org/W4226363941"],"abstract_inverted_index":{"Hydropower":[0],"units":[1,20],"are":[2],"the":[3,12,28,44,54,68,72,81,94,102,112,129,133,153,162,167,171,177,190,200,206,209,218,227,238],"core":[4],"equipment":[5],"of":[6,18,30,47,56,71,132,155,170,208],"hydropower":[7],"stations,":[8],"and":[9,15,27,33,63,93,106,165,203,216,224,226,234],"research":[10],"on":[11,67,142],"fault":[13],"prediction":[14,191,239],"health":[16],"management":[17],"these":[19,48],"can":[21,34,151],"help":[22],"improve":[23],"their":[24],"safety,":[25],"stability,":[26],"level":[29],"reliable":[31],"operation":[32],"effectively":[35,188,242],"reduce":[36],"costs.":[37],"Therefore,":[38],"it":[39,187],"is":[40,86,99,125],"necessary":[41],"to":[42,88,127],"predict":[43,128],"swing":[45,65,69,78,130],"trend":[46,79,131],"units.":[49],"Firstly,":[50],"this":[51],"study":[52],"considers":[53],"influence":[55],"various":[57],"factors,":[58,66],"such":[59],"as":[60],"electrical,":[61],"mechanical,":[62],"hydraulic":[64],"signal":[70],"main":[73,134],"guide":[74,135],"bearing":[75],"y-axis.":[76],"Before":[77],"prediction,":[80],"multi-index":[82],"feature":[83,97],"selection":[84],"algorithm":[85,150,211],"used":[87,126],"obtain":[89],"suitable":[90],"state":[91],"variables,":[92],"low-dimensional":[95],"effective":[96],"subset":[98],"obtained":[100],"using":[101],"Pearson":[103],"correlation":[104,108],"coefficient":[105,109],"distance":[107],"algorithms.":[110],"Secondly,":[111],"dilated":[113,122],"convolution":[114,123],"graph":[115,144,163,172,183],"neural":[116],"network":[117],"(DCGNN)":[118],"algorithm,":[119],"with":[120,199],"a":[121],"graph,":[124],"bearing.":[136],"Existing":[137],"GNN":[138],"methods":[139],"rely":[140],"heavily":[141],"predefined":[143],"structures":[145],"for":[146],"prediction.":[147],"The":[148,193],"DCGNN":[149,210],"solve":[152],"problem":[154,179],"spatial":[156],"dependence":[157],"between":[158],"variables":[159],"without":[160],"defining":[161],"structure":[164],"provides":[166],"adjacency":[168],"matrix":[169],"learning":[173],"layer":[174],"simulation,":[175],"avoiding":[176],"over-smoothing":[178],"often":[180],"seen":[181],"in":[182],"convolutional":[184],"networks;":[185],"furthermore,":[186],"improves":[189],"accuracy.":[192],"experimental":[194],"results":[195],"showed":[196],"that,":[197],"compared":[198],"RNN-GRU,":[201],"LSTNet,":[202],"TAP-LSTM":[204],"algorithms,":[205],"MAEs":[207],"decreased":[212,220],"by":[213,221,231],"6.05%,":[214],"6.32%,":[215],"3.04%;":[217],"RMSEs":[219],"9.21%,":[222],"9.01%,":[223],"2.83%;":[225],"CORR":[228],"values":[229],"increased":[230],"0.63%,":[232],"1.05%,":[233],"0.37%,":[235],"respectively.":[236],"Thus,":[237],"accuracy":[240],"was":[241],"improved.":[243]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-03T07:22:36.454288","created_date":"2025-10-10T00:00:00"}
