自然科学版 英文版
自然科学版 英文版
自然科学版 英文版

您目前所在的位置:首页 - 期刊简介 - 详细页面

中南大学学报(自然科学版)

Journal of Central South University

第46卷    第6期    总第250期    2015年6月

[PDF全文下载]    [Flash在线阅读]

    

文章编号:1672-7207(2015)06-2059-06
基于改进半监督局部保持投影算法的故障诊断
杨望灿,张培林,吴定海,陈彦龙

(军械工程学院 七系,河北 石家庄,050003)

摘 要: 为解决在少量标记样本的条件下故障诊断困难的问题,提出一种基于改进半监督局部保持投影(ISS-LPP)的故障诊断方法。ISS-LPP算法利用部分标记样本的标签信息调整原始特征空间中样本间的权值矩阵,并根据所有样本在特征空间的分布情况自适应的调整邻域参数,寻找数据的低维本质流形,得到原始特征空间样本数据的低维特征向量和投影转换矩阵。以得到的低维特征向量为输入,建立分类器,识别和判断故障类型。将ISS-LPP算法应用于滚动轴承的故障诊断。实验结果表明:该方法能够在标记样本较少时,提高轴承的故障诊断精度。

 

关键字: 故障诊断;改进半监督局部保持投影;权值矩阵;邻域参数;滚动轴承

Fault diagnosis based on improved semi-supervised locality preserving projections
YANG Wangcan, ZHANG Peilin, WU Dinghai, CHEN Yanlong

Seventh Department, Ordnance Engineering College, Shijiazhuang 050003, China

Abstract:In order to diagnose the fault effectively with a small number of labeled samples, a method of fault diagnosis based on improved semi-supervised locality preserving projections was proposed. The method of ISS-LPP used the information of some labeled samples to adjust the weight matrix among all samples in the original characteristic space. The neighborhood parameter could be adjusted automatically according to the distribution of the all samples. Therefore, the low-dimensional manifold could be found. So the low-dimensional eigenvectors and the projection matrix were achieved from the original characteristic space by ISS-LPP. With the low-dimensional eigenvectors as inputs, classifiers were established for identifying fault types. The method of ISS-LPP was applied for the fault diagnosis of roller bearing. The results indicate that the proposed method can diagnose bearing fault in high accuracy with a small number of labeled samples.

 

Key words: fault diagnosis; improved semi-supervised locality preserving projections; weight matrix; neighborhood parameter; roller bearing

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
版权所有:《中南大学学报(自然科学版、英文版)》编辑部
地 址:湖南省长沙市中南大学 邮编: 410083
电 话: 0731-88879765(中) 88836963(英) 传真: 0731-88877727
电子邮箱:zngdxb@csu.edu.cn 湘ICP备09001153号