Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering

Coal Conveying Fault Diagnosis Design of Coal mining machine Based On Software Control

Authors
Jingyuan Gao
Corresponding Author
Jingyuan Gao
Available Online April 2015.
DOI
https://doi.org/10.2991/amcce-15.2015.260How to use a DOI?
Keywords
coal mining machine; coal conveying system; neural network; fault diagnosis; genetic algorithm and particle swarm algorithm (GA-PSO)
Abstract
The coal conveying system is the most important composition unit of continuous mining machine, the performance of coal conveying system plays a decisive role in production efficiency, this equipment is easy to cause the fault, in this paper, the faults often appeared in this equipment and the fault reasons are analyzed, genetic algorithm (GA) and particle swarm optimization (PSO) are taken as the optimization tool, and then combined with the method of BP neural network, the fault diagnosis of coal conveying system is researched. The analysis results show that, this method can make the BP neural network away from local minima effectively, the accuracy of the equipment is increased, and then the fault diagnosis of equipment can be carried out quickly, conveniently and accurately.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Jingyuan Gao
PY  - 2015/04
DA  - 2015/04
TI  - Coal Conveying Fault Diagnosis Design of Coal mining machine Based On Software Control
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.260
DO  - https://doi.org/10.2991/amcce-15.2015.260
ID  - Gao2015/04
ER  -