{"id":"https://openalex.org/W2990549040","doi":"https://doi.org/10.1109/access.2019.2955932","title":"Bayesian Hierarchical Model-Based Information Fusion for Degradation Analysis Considering Non-Competing Relationship","display_name":"Bayesian Hierarchical Model-Based Information Fusion for Degradation Analysis Considering Non-Competing Relationship","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2990549040","doi":"https://doi.org/10.1109/access.2019.2955932","mag":"2990549040"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2955932","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2955932","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08913564.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08913564.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079921526","display_name":"Junyu Guo","orcid":"https://orcid.org/0000-0001-9462-9501"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junyu Guo","raw_affiliation_strings":["School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-9462-9501","affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039983728","display_name":"Hualin Zheng","orcid":"https://orcid.org/0000-0002-6374-4213"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hualin Zheng","raw_affiliation_strings":["School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-6374-4213","affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100649273","display_name":"Binglin Li","orcid":"https://orcid.org/0000-0002-2424-5657"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binglin Li","raw_affiliation_strings":["School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-2424-5657","affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086449098","display_name":"Guo\u2010Zhong Fu","orcid":"https://orcid.org/0000-0002-0977-9802"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo-Zhong Fu","raw_affiliation_strings":["Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-0977-9802","affiliations":[{"raw_affiliation_string":"Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079921526"],"corresponding_institution_ids":["https://openalex.org/I165745306"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.5547,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.92250438,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"175222","last_page":"175227"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11357","display_name":"Risk and Safety Analysis","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12423","display_name":"Software Reliability and Analysis Research","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/degradation","display_name":"Degradation (telecommunications)","score":0.7136660814285278},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6827298998832703},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6673033237457275},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5084489583969116},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.47761768102645874},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.45388704538345337},{"id":"https://openalex.org/keywords/bayesian-hierarchical-modeling","display_name":"Bayesian hierarchical modeling","score":0.44955146312713623},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.44357478618621826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43602627515792847},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.435573011636734},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.43048423528671265},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39316701889038086}],"concepts":[{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.7136660814285278},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6827298998832703},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6673033237457275},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5084489583969116},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.47761768102645874},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45388704538345337},{"id":"https://openalex.org/C191413810","wikidata":"https://www.wikidata.org/wiki/Q17100952","display_name":"Bayesian hierarchical modeling","level":4,"score":0.44955146312713623},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.44357478618621826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43602627515792847},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.435573011636734},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.43048423528671265},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39316701889038086},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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":2,"locations":[{"id":"doi:10.1109/access.2019.2955932","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2955932","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08913564.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b50e95e78bf94b0fb33ea28713908f2d","is_oa":true,"landing_page_url":"https://doaj.org/article/b50e95e78bf94b0fb33ea28713908f2d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 175222-175227 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2955932","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2955932","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08913564.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Responsible consumption and production","id":"https://metadata.un.org/sdg/12","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2990549040.pdf","grobid_xml":"https://content.openalex.org/works/W2990549040.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W343083875","https://openalex.org/W1974741912","https://openalex.org/W1975174792","https://openalex.org/W1980849422","https://openalex.org/W1988286714","https://openalex.org/W2008825253","https://openalex.org/W2023083702","https://openalex.org/W2037355783","https://openalex.org/W2040287221","https://openalex.org/W2043129860","https://openalex.org/W2059401976","https://openalex.org/W2069719474","https://openalex.org/W2079550842","https://openalex.org/W2112935810","https://openalex.org/W2176539232","https://openalex.org/W2344640383","https://openalex.org/W2345145213","https://openalex.org/W2561529988","https://openalex.org/W2712753561","https://openalex.org/W2757101479","https://openalex.org/W2759551697","https://openalex.org/W2760903766","https://openalex.org/W2765311403","https://openalex.org/W2788941837","https://openalex.org/W2791131283","https://openalex.org/W2793673910","https://openalex.org/W2800502447","https://openalex.org/W2801888775","https://openalex.org/W2802718394","https://openalex.org/W2804159081","https://openalex.org/W2809385501","https://openalex.org/W2809670936","https://openalex.org/W2898683876","https://openalex.org/W2912773041","https://openalex.org/W2918612717","https://openalex.org/W2953792091","https://openalex.org/W2964604532","https://openalex.org/W4248188303"],"related_works":["https://openalex.org/W786367546","https://openalex.org/W4220780651","https://openalex.org/W3119278052","https://openalex.org/W2407375987","https://openalex.org/W2505726097","https://openalex.org/W2950975704","https://openalex.org/W2010643158","https://openalex.org/W3049691116","https://openalex.org/W2106867672","https://openalex.org/W4310268968"],"abstract_inverted_index":{"Degradation":[0],"analysis":[1],"methods":[2],"are":[3,97],"increasingly":[4],"used":[5],"in":[6,21,61,111],"reliability":[7],"assessment":[8],"of":[9,19,105,108],"long-life":[10],"products.":[11,63],"The":[12,40],"small":[13,37],"sample":[14,38],"size":[15],"problem":[16],"is":[17,28,54,79,114],"worthy":[18],"attention":[20],"the":[22,55,83,90,94,118],"degradation":[23,33,44,58,73,87,125],"analysis.":[24],"Bayesian":[25,68,91,120],"hierarchical":[26,69,121],"method":[27,74,92,96],"employed":[29,98],"for":[30,81,99],"fusing":[31],"multi-source":[32],"information":[34,71,123],"to":[35,116],"handle":[36],"problems.":[39],"competing":[41],"relationship":[42,85],"multiple":[43,57,86],"models":[45],"have":[46],"been":[47],"widely":[48],"researched":[49],"and":[50,93],"applied.":[51],"However,":[52],"there":[53],"non-competing":[56,84],"situation":[59],"exist":[60],"mechanical":[62],"In":[64],"this":[65],"paper,":[66],"a":[67],"model-based":[70,122],"fusion":[72,124],"with":[75],"gamma":[76],"process":[77],"model":[78],"introduced":[80],"describing":[82],"process.":[88],"Therefore,":[89],"MCMC":[95],"parameters":[100],"estimation.":[101],"A":[102],"numerical":[103],"example":[104],"spool":[106],"valve":[107],"hydraulic":[109],"system":[110],"exoskeleton":[112],"robot":[113],"provided":[115],"demonstrate":[117],"proposed":[119],"method.":[126]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}