Data analysis and inference for an industrial deethanizer

Document Type

Conference Proceeding

Publication Date

1-1-2009

Abstract

In this paper, we present an application of data derived approaches for analyzing and monitoring an industrial deethanizer column. The discussed methods are used in visualizing process measurements, extracting operational information and designing an estimation model. Emphasis is given to the modeling of the data obtained with standard paradigms like the Self-Organizing Map (SOM) and the Multi-Layer Perceptron (MLP). Here, the effectiveness of these data-derived techniques is validated on a full-scale application where the goal is to identify significant operational modes and most sensitive process variables before developing an alternative control scheme. Copyright © 2009, AIDIC Servizi S.r.l.

Publication Source (Journal or Book title)

Chemical Engineering Transactions

First Page

1197

Last Page

1202

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