An integrated approach to bearing fault diagnostics and prognostics

被引：120

作者：

Zhang, XD ^{[1
]}

Xu, R ^{[1
]}

Kwan, CM ^{[1
]}

Liang, SY ^{[1
]}

Xie, QL ^{[1
]}

Haynes, L ^{[1
]}

机构：

[1] Intelligent Automat Inc, Rockville, MD 20855 USA

来源：

ACC: PROCEEDINGS OF THE 2005 AMERICAN CONTROL CONFERENCE, VOLS 1-7 | 2005年

关键词：

D O I：

10.1109/ACC.2005.1470385

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an integrated fault diagnostic and prognostic approach for bearing health monitoring and condition-based maintenance. The proposed scheme consists of three main components including principal component analysis (PCA), hidden Markov model (HMM), and an adaptive stochastic fault prediction model. The principal signal features extracted by PCA are utilized by HMM to generate a component health/degradation index, which is the input to an adaptive prognostics component for on-line remaining useful life prediction. The effectiveness of the scheme is shown by simulation studies using experimental vibration data obtained from a bearing health monitoring testbed.

引用

页码：2750 / 2755

页数：6

共 11 条

[1]

ATLAS L, 2001, P 2001 IEEE AER C BI

[2] Tool wear condition monitoring in drilling operations using hidden Markov models (HMMs) [J].