Diagnosis of the Cane Sugar Crystallization Process by Multifractal Analysis of Temperature Time Series

The monitoring and diagnosis of crystallization processes are difficult due to the interaction of nucleation and crystal growth phenomena. In recent years, image and time series analysis using fractal methodologies showed potential as an alternative for monitoring crystal growth, although the available results are scarce. In this work, the multifractal detrended fluctuation analysis (MF-DFA) was applied to temperature time series obtained from a laboratory-scale cane sugar crystallization operated at different operating conditions. MF-DFA reflects that the crystallization process exhibits multifractal properties associated with the dynamic behavior of the underlying phenomena. Thus, multifractal analysis can identify how operational changes influence the crystal growth and formed crystal mass.