Process Monitoring Based on Improved Principal Component Analysis

DOI

10.2991/iccita-16.2016.8How to use a DOI?

Keywords

Principal component analysis; Process monitoring; Principal-component-related variable; Double-effect evaporator process

Abstract

The information provided by T2 and squared prediction error (SPE) test of principal component analysis (PCA) is not corresponding. An improved PCA is proposed which uses principal-component-related variable residual statistic and common variable residual statistic to replace SPE statistic. Then a simulated double-effect evaporator is monitored by using the proposed method and comparisons with the conventional PCA are made. The simulation result shows that the improved PCA can avoid the conservation of SPE statistical test and provide more explicit information about the process conditions. So the improved PCA has an enhanced fault diagnosing performance.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yingwang Xiao
PY  - 2016/05
DA  - 2016/05
TI  - Process Monitoring Based on Improved Principal Component Analysis
BT  - Proceedings of the 2016 International Conference on Computer and Information Technology Applications
PB  - Atlantis Press
SP  - 42
EP  - 45
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccita-16.2016.8
DO  - 10.2991/iccita-16.2016.8
ID  - Xiao2016/05
ER  -