华中科技大学学报（自然科学版）2017，Vol.45Issue(1)：91-96,6.DOI:10.13245/j.hust.170117
基于自适应LTSA算法的滚动轴承故障诊断
Fault diagnosis of rolling bearing based on adaptive LTSA algorithm
摘要
Abstract
Improved local tangent space alignment (ILTSA) method with adaptive neighborhood selec‐tion was presented ,aiming at solving the problem of over‐high dimensions and redundancy in the mixed fault feature set .As traditional neighborhood selection method was not applicable to the varied curvature and non‐uniformly sampled manifold ,to keep the local linearity by considering the sample density ,the local curvature and the deflection angle of local tangent space ,method of selecting the neighborhood adaptively was proposed to improve the robustness of the algorithm .An improved Fish‐er criterion method of feature selection was also proposed to improve the accuracy of fault diagnosis . Firstly the low redundant features were selected to make the high dispersion between classes and low dispersion within a class .Then the sensitive features were compressed to reduce dimensions with the ILTSA method .Finally ,the feature subset was fed into the k nearest neighbor classification (KNNC) to identify the fault .T he test on different fault position and severities of rolling bearing verified the validity of the proposed method .关键词
滚动轴承/故障诊断/Fisher准则/自适应邻域选择/局部切空间排列Key words
rolling bearing/fault diagnosis/Fisher criterion/adaptive neighborhood selection/local tangent space alignment分类
信息技术与安全科学引用本文复制引用
佘博,田福庆,汤健,李克玉..基于自适应LTSA算法的滚动轴承故障诊断[J].华中科技大学学报（自然科学版）,2017,45(1):91-96,6.基金项目
国家自然科学基金资助项目（61573364）． （）
