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Paste-filling weighing control system optimization based on neural network

Guimei Wang (College of Mechanical and Electrical Engineering, Hebei University of Engineering, Handan, China)
Yong Shuo Zhang (College of Mechanical and Electrical Engineering, Hebei University of Engineering, Handan, China)
Lijie Yang (College of Mechanical and Electrical Engineering, Hebei University of Engineering, Handan, China)
Shuai Zhang (Panorama Scientific Limited Company, Beijing, China)

World Journal of Engineering

ISSN: 1708-5284

Article publication date: 10 April 2017

158

Abstract

Purpose

This paper aims to optimize the weighing control system and compensate weighing error for weighing control system of coal mine paste-filling weighing control system.

Design/methodology/approach

The process of the paste-filling weighing control system is analyzed and the mathematical model of the paste-filling material weight is established. Then, the back-propagation (BP) neural network is used to optimize the control system and compensate the weighing error.

Findings

Without the BP neural network, the weighing error of the paste-filling control system is more than 3 per cent, whereas after optimization with the BP neural network, the weighing error is less than 1 per cent. With the simulation results, it is seen that the weighing error of the paste-filling control system decreases and the accuracy of the weighing control system improves and optimizes.

Originality/value

The method can be further used to improve the control precision of the coal mine paste-filling system.

Keywords

Acknowledgements

This project was supported by the Science and Technology project of Hebei Province (16394102D).

Citation

Wang, G., Zhang, Y.S., Yang, L. and Zhang, S. (2017), "Paste-filling weighing control system optimization based on neural network", World Journal of Engineering, Vol. 14 No. 2, pp. 155-158. https://doi.org/10.1108/WJE-10-2016-0108

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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