Article ID Journal Published Year Pages File Type
173298 Computers & Chemical Engineering 2010 5 Pages PDF
Abstract

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.

Related Topics
Physical Sciences and Engineering Chemical Engineering Chemical Engineering (General)
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