吉林大学学报（信息科学版）2023，Vol.41Issue(5)：780-786,7.
融合邻域分布LLE算法轴承故障信号检测
Bearing Signal Detection for the Fusion Neighborhood Distribution of LLE Algorithm
张彦生 1张利来 1刘远红1
作者信息
- 1. 东北石油大学电气信息工程学院,黑龙江大庆 163318||东北石油大学东北石油大学国家大学科技园,黑龙江大庆 163318
- 折叠
摘要
Abstract
For the problem that LLE(Local Linear Embedding)fails to adequately preserve the structure between neighborhoods in high-dimensional data,a new local linear embedding algorithm is proposed for fused neighborhood distribution properties.The algorithm calculates the neighborhood distribution of each sample data,then calculates the respective nearest neighborhood distribution difference of the KL(Kullback-Leibler)divergence measure between the different neighborhood point and its central sample,and finally optimizes the reconstructed weight coefficient to obtain more accurate low-dimensional motor data.The effectiveness of the algorithm is verified by three evaluations of visualization.Fisher measurement and identification accuracy.关键词
局部线性嵌入/邻域分布/降维算法/电机轴承Key words
local linear embedding/neighborhood distribution/dimension reduction algorithm/motor bearing分类
信息技术与安全科学引用本文复制引用
张彦生,张利来,刘远红..融合邻域分布LLE算法轴承故障信号检测[J].吉林大学学报（信息科学版）,2023,41(5):780-786,7.
