摘要
相关向量机(RVM)是目前最受关注的新一代模式识别技术之一,阐述了基于相关向量机的故障诊断方法、应用前景等。介绍相关向量机的分类、回归模型及其国内外研究进展;对RVM提出至今在故障诊断和退化评估与寿命预测中的应用研究进行综述;最后分析在故障诊断中RVM方法存在的弊端及其未来研究趋势。
Relevance vector machine is currently one of the most concerned new generation pattern recognition technologies.The fault diagnosis methods and application prospects based on RVM were described.The classification and regression models of RVM and its research progress at home and abroad were introduced.The application research of RVM in fault diagnosis,degradation assessment and life prediction so far were summarized.The drawbacks of RVM method in fault diagnosis and the trend of future research were analyzed.
作者
陈康
熊建斌
苏乃权
王颀
余得正
李春林
CHEN Kang;XIONG Jianbin;SU Naiquan;WANG Qi;YU Dezheng;LI Chunlin(School of Automation, Guangdong Polytechnic Normal University, Guangzhou Guangdong 510665, China;School of Mechanical and Electrical Engineering, Guangdong University of Petrochemical Technology, Maoming Guangdong 525000, China)
出处
《机床与液压》
北大核心
2022年第3期176-186,共11页
Machine Tool & Hydraulics
基金
国家自然科学基金项目(62073090)
广东省自然科学基金项目(2019A1515010700)
广东省重点项目(2019KZDXM020,2019KZDZX1004,2019KZDZX1042)
广东技术师范大学人才引进项目(991512203,991560236)。
关键词
相关向量机
故障诊断
退化评估与寿命预测
Relevance vector machine
Fault diagnosis
Degradation assessment and life prediction
