HSIC modeling of P80 for an industrial-scale ball mill circuit, P. Semsari Parapari, S. Liaghat, A. Tohry, J. Rosenkranz, and S. Chehreh Chelgani

The Southern African Institute of Mining and Metallurgy
P. Semsari Parapari S. Liaghat A. Tohry J. Rosenkranz S. Chehreh Chelgani
Organization:
The Southern African Institute of Mining and Metallurgy
Pages:
10
File Size:
1068 KB
Publication Date:
Jan 1, 2020

Abstract

It is commonly accepted that the energy consumption for comminution within mineral processing is responsible for around 3% of the global electrical energy usage. However, it was clearly noted that inside mills, less than 1% of this energy efficiency is actually consumed for particle size reduction. Therefore, monitoring of grinding parameters and modelling of product particle size distribution (e.g. characterised by the 80% passing size P80) play an essential role in operating costs of a mineral processing plant. Several empirical models have been introduced for the prediction of the P80. Since in the industrial scale usually a few numbers of grinding variables are monitored, these models cannot identically be used in plants. In addition, these empirical models do not always indicate the magnitude of correlations between milling variables. This study proposes to introduce the Hilbert-Schmidt independence criterion (HSIC) as an intelligent model for exploring linear and nonlinear relationships between grinding variables and P80 for an industrial scale data assessment. HSIC can rank variables based on their importance and help to select the most effective one for the generation of predictive models. HSIC modelling through various monitored grinding variables (ball charge, feed input rate, F80, power draw and work index) of an industrial plant indicated that F80 as a feed property has the highest effect on P80 of the ball mill products. Modelling results highlighted that the P80 can be accurately predicted, based on effective variables by using a HSIC model. These outcomes showed that HSIC as a powerful modelling tool can assess the relationships between monitored grinding parameters, select the most effective grinding parameters and satisfactorily predict the P80. Keywords: Product particle size, variable importance measurement, Hilbert-Schmidt independence criterion, mill charge
Citation

APA: P. Semsari Parapari S. Liaghat A. Tohry J. Rosenkranz S. Chehreh Chelgani  (2020)  HSIC modeling of P80 for an industrial-scale ball mill circuit, P. Semsari Parapari, S. Liaghat, A. Tohry, J. Rosenkranz, and S. Chehreh Chelgani

MLA: P. Semsari Parapari S. Liaghat A. Tohry J. Rosenkranz S. Chehreh Chelgani HSIC modeling of P80 for an industrial-scale ball mill circuit, P. Semsari Parapari, S. Liaghat, A. Tohry, J. Rosenkranz, and S. Chehreh Chelgani. The Southern African Institute of Mining and Metallurgy, 2020.

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