Nonlinear sensor fault diagnosis using mixture of probabilistic PCA models
详细信息 查看全文
- 作者：Reza Sharifia ; reza.sharifi@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Reza Langarib ; rlangari@tamu.edu" class="auth_mail" title="E-mail the corresponding author
- 关键词：Fault diagnosis ; Sensor fault detection ; Principal Component Analysis ; Mixture of Probabilistic PCA ; Nonlinear fault detection
- 刊名：Mechanical Systems and Signal Processing
- 出版年：2017
- 出版时间：15 February 2017
- 年：2017
- 卷：85
- 期：Complete
- 页码：638-650
- 全文大小：2448 K
文摘
- •
Data driven approach using a Mixture of Probabilistic Principal Component Analysis to nonlinear sensor fault diagnosis.
- •
Sensor detectability index (SDI) based on the internal relationships of the system variables.
- •
Application to multiple processes to experimentally validate approach.
- •
Gaussian model found effective in representing noise.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |