Title: Optimisation of opencast mining machinery noise using differential evolutionary algorithm

Authors: Debi Prasad Tripathy; D.S. Rao

Addresses: Department of Mining Engineering, National Institute of Technology, Rourkela 769008, India ' National Institute of Technology, Rourkela 769008, India

Abstract: Noise levels produced by various mining equipment's are high and exposure to such levels is considered as a severe problem. The aim of this paper is to develop and analyse the ability of a differential evolution (DE) algorithm to locate global optima of the far field noise levels produced by mining machineries in the mine. The objective function formulated is maximisation of sound pressure level (SPL) so as to determine optimal distance, optimal directivity index, optimal sound power level (SWL) and other optimal attenuation parameters. The most essential challenge in optimisation problems is CPU time. Comparison with the best known variants of DE over the objective function reflects the superiority of the parameter tuning scheme in terms of accuracy, convergence speed and robustness. Results show that DE/RAND/2 is able to converge, find optimum values faster compared to other mutation variants and seems to be a promising approach for machinery noise optimisation problems.

Keywords: differential evolution algorithm; machinery noise; CPU time; SPL; sound pressure level; mutation variants; stochastic optimisation.

DOI: 10.1504/IJMME.2017.087951

International Journal of Mining and Mineral Engineering, 2017 Vol.8 No.4, pp.294 - 309

Received: 14 Nov 2016
Accepted: 19 Apr 2017

Published online: 05 Nov 2017 *

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