Paper
26 March 2001 Wavelet packet time series analysis of aluminum electrolytic cells
Arthur Johnson III, Ching-Chung Li
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Abstract
For decades the process of aluminum electrolysis has facilitated the production of aluminum. The process occurs within aluminum electrolytic cells, where alumina (Al2O3) is dissolved in liquid cryolite (Na3AlF6). The dissolved alumina is reduced by the carbon anode and forms carbon dioxide. Complexes containing aluminum ions migrate to the cathode surface (bath-metal interface) where aluminum metal is produced. The monitoring of the electrolysis process is done through the use of the cell resistance. Using resistance set point values that are indirectly related to the desired alumina concentration in the bath (cryolite), the computed resistance can indicate if the cell is operating within acceptable production conditions. The resistance time series is a nonstationary random process. We have applied the principal component method to shortsegments of each time series to identify key components. However the principal components are data dependent. In order to study the time series' localized structure we use a wavelet packet based approach to analyze this nonstationary process. We use Daubechies 3 orthonormal wavelet and scaling function as our basis functions and model each short segment of the resistance time series as a locally stationary wavelet process. The use of wavelet packets increases the separability of the innovations into individual packets. Hence each wavelet packet time series represents a single subprocess. The analysis of individual subprocesses yields information for making inference of how the process evolves during unstable operating conditions.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arthur Johnson III and Ching-Chung Li "Wavelet packet time series analysis of aluminum electrolytic cells", Proc. SPIE 4391, Wavelet Applications VIII, (26 March 2001); https://doi.org/10.1117/12.421204
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Cited by 3 scholarly publications.
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KEYWORDS
Wavelets

Aluminum

Resistance

Process modeling

Statistical analysis

Ions

Carbon

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