MULTISCALE AND FRACTAL ANALYSIS OF SILICON CONTENT TIME SERIES OBSERVED IN BLAST FURNACE HOT METAL USING HURST EXPONENT CHAIN

Abstract

Hurst exponent is an important measure of nonlinearity of dynamical time series. In this paper, using rescaled-range ([Formula: see text]/[Formula: see text]) analysis, multi-fractal detrended fluctuation analysis (MF-DFA) methods, the multiscale Hurst exponent (MHE) and the multiscale generalized Hurst exponent (MGHE) of coarse-grained silicon content ([Si]) time series in blast furnace (BF) hot metal were calculated. First, we collected these [Si] time series from No. 1 BF of Nanchang Iron and Steel Co. and No. 10 BF of Xinyu Iron and Steel Co. in Jiangxi Province, China. Then, we analyzed and compared the estimated Hurst exponents and the generalized Hurst exponent of these observed time series with some simulated time series. Our results show that the observed time series from these BFs have negative correlation with the Hurst exponent less than 0.5, the generalized Hurst exponent [Formula: see text] is a nonlinear function of [Formula: see text], and such negative correlation and local various structure persist in their moving averages of the observed time series up to lag 5 or 10.