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

作　　者：张彦生[1,2] 张利来 刘远红 ZHANG Yansheng;ZHANG Lilai;LIU Yuanhong(School of Electrical and Information Engineering,Northeast Petroleum University,Daqing 163318,China;Northeast Petroleum University National Science Park,Northeast Petroleum University,Daqing 163318,China)

机构地区：[1]东北石油大学电气信息工程学院,黑龙江大庆163318 [2]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

出　　处：《吉林大学学报（信息科学版）》2023年第5期780-786,共7页Journal of Jilin University（Information Science Edition）

摘　　要：针对降维算法局部线性嵌入算法LLE(Local Linear Embedding)未能充分保留高维数据中邻域之间的结构的问题,提出了一种新的融合邻域分布属性的局部线性嵌入算法。该算法通过计算每个样本数据的邻域分布以及KL(Kullback-Leibler)散度度量不同邻域点与其中心样本各自的近邻分布差异,并利用其差值优化重构的权重系数,从而获得更精确的低维电机数据。通过可视化、Fisher测量和识别精度3个评价结果验证了该算法挖掘电机轴承检测数据高维结构的有效性。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 

分 类 号：TN911.23[电子电信—通信与信息系统]