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Proceedings Paper

Process signal classification for aluminum cells
Author(s): Larry E. Banta; Philip L. Biedler; Congxia Dai
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Paper Abstract

The control of the aluminum reduction process is typically done based on measurements of cell voltage and current. Both signals are very noisy. Voltage fluctuations come from numerous sources such as CO2 bubble generation, current fluctuations, metal pad motion, anode movement, electrical arcing, and changes in alumina concentration. The latter is an important control variable, but its effects on cell voltage are small and are often swamped by the signals from other sources. To date, control system designers have attempted to deal with this problem by extreme low-pass filtering and by suspension of all anode movements and alumina feed operations during the measurement period. This strategy is fairly effective, but leads in most case to sub- optimal cell operation most of the time. Research at West Virginia University and Century Aluminum seeks to improve upon the traditional strategies by incorporating knowledge about the process and prior cell control actions in the data analysis operation. For example, selective bandpass filtering and model-based feature detection strategies can be used to identify and isolate various portions of the composite signal. This paper discuses the methods being developed and the results of their application to this critical industrial process.

Paper Details

Date Published: 3 October 2001
PDF: 10 pages
Proc. SPIE 4565, Intelligent Systems in Design and Manufacturing IV, (3 October 2001); doi: 10.1117/12.443120
Show Author Affiliations
Larry E. Banta, West Virginia Univ. (United States)
Philip L. Biedler, West Virginia Univ. (United States)
Congxia Dai, West Virginia Univ. (United States)


Published in SPIE Proceedings Vol. 4565:
Intelligent Systems in Design and Manufacturing IV
Angappa Gunasekaran; Bhaskaran Gopalakrishnan, Editor(s)

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