Journal
COMPUTERS & CHEMICAL ENGINEERING
Volume 34, Issue 3, Pages 349-353Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2009.11.003
Keywords
Partial Least Squares; Kernel methods; Condition monitoring
Ask authors/readers for more resources
A warning system for detection of excessive vibration in a centrifuge system of a product treatment plant is built using a database of past faults and an equivalent amount of normal operating null data. A logistic Partial Least Squares (PLS) model is derived using wavelet coefficients to approximately decorrelate the time series data. This model provides a baseline to evaluate any improvement through kernel methods. The kernel paradigm is introduced from a Bayesian perspective and used to develop a detector with significantly less false positives and missed detections. (C) 2009 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available