沈阳航空航天大学学报2024，Vol.41Issue(1)：54-60,7.DOI:10.3969/j.issn.2095-1248.2024.01.007
基于PCA多模型融合的滚动轴承性能退化指标构建
Construction of performance degradation indicators for rolling bearings based on PCA multi-model fusion
摘要
Abstract
The performance health indicator of rolling bearings constructed from a single model can on-ly describes the performance degradation states of rolling bearings from a single perspective,which has certain limitations.To solve this problem,a method for constructing HI based on PCA multi-model fusion was proposed.The idea was to use SVDD,AAKR,and GMM models to construct the corre-sponding single model HI,and then fuse them through PCA.The first principal component was select-ed as SAG-HI,containing"multi angle"performance degradation information.Experimental results shows that compared to the HI of each single model,SAG-HI achieved 98.06%grey confidence level in maintaining reliability with rolling bearings,and its correlation,monotonicity,and robustness were the best.Envelope spectrum analysis verified its ability to accurately monitor early fault occurrences.关键词
滚动轴承/支持向量数据/自联想核回归/高斯混合模型/主成分分析/性能退化指标/多模型融合Key words
rolling bearings/support vector data/auto-associative kernel regression/gaussian mix-ture model/PCA/performance degradation indicators/multi-model fusion分类
机械制造引用本文复制引用
蒋丽英,郭濠,李贺,刘明昆,张雷鸣..基于PCA多模型融合的滚动轴承性能退化指标构建[J].沈阳航空航天大学学报,2024,41(1):54-60,7.基金项目
国家自然科学基金(项目编号:62003223) （项目编号:62003223）
