基于提升小波和递归增量聚类的实时故障诊断方法

doi:10.3969/j.issn.1001-506X.2013.01.27

Journal of Systems Engineering and Electronics ›› 2013, Vol. 35 ›› Issue (1): 161-167.doi: 10.3969/j.issn.1001-506X.2013.01.27

基于提升小波和递归增量聚类的实时故障诊断方法

杨青1,2, 汤剑桥1, 刘畅1, 刘念1

1. 沈阳理工大学信息科学与工程学院，辽宁沈阳 110159；
2. 长春理工大学光电工程学院，吉林长春 130022

出版日期:2013-01-23 发布日期:2010-01-03

Real time fault diagnosis approach based on lifting wavelet and recursive incremental clustering

ANG Qing1,2，TANG Jian-qiao1，LIU Chang1，LIU Nian1

1. School of Information Science and Engineering，Shenyang Ligong University, Shenyang 110159, China; 2. College of Optical and Electronical Engineering，Changchun University of Science and Technology，Changchun 130022, China

Online:2013-01-23 Published:2010-01-03

摘要/Abstract

摘要：

针对复杂时变工业过程实时故障诊断问题，提出了一种基于提升小波( lifting wavelet, LW) 与递归增量聚类（recursive incremental clustering, RICLUSTER）相结合的实时故障诊断方法（lifting wavelet recursive incremental clustering， LW-RICLUSTER）。该方法首先通过LW变换对数据实时去噪，再通过RICLUSTER实时监控。由于采用LW与RICLUSTER相结合的方法，节省存储空间和运算时间的同时提高了诊断精度。实验结果表明，LWRICLUSTER集合方法能有效实现时变过程监控, 在诊断精度、速度和适应性方面，优于传统单一型CLUSTER方法。

Abstract:

An ensemble realtime fault diagnosis method based on lifting wavelet (LW) and recursive incremental clustering（RICLUSTER）, called LW-RICLUSTER, is proposed to realize realtime monitoring for complex time varying industrial processes. Firstly, data are denoised by LW transform in real time, then RICLUSTER is used for realtime monitoring. With the ensemble approach, storage space is saved and computing time is shortened, while the precision of diagnostic is increased. Experiment results show that the LW -RICLUSTER algorithm can monitor timevarying process. The LW-RICLUSTER is superior to the traditional single CLUSTER in diagnosis precision, rate and adaptability.

杨青, 汤剑桥, 刘畅, 刘念. 基于提升小波和递归增量聚类的实时故障诊断方法[J]. Journal of Systems Engineering and Electronics, 2013, 35(1): 161-167.

ANG Qing，TANG Jian-qiao，LIU Chang，LIU Nian. Real time fault diagnosis approach based on lifting wavelet and recursive incremental clustering[J]. Journal of Systems Engineering and Electronics, 2013, 35(1): 161-167.

基于提升小波和递归增量聚类的实时故障诊断方法

Real time fault diagnosis approach based on lifting wavelet and recursive incremental clustering

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