Analysis and Diagnosis of Coal Shearer Machine Fault Based on Improved Support Vector Theory

DOI

10.2991/eame-15.2015.63How to use a DOI?

Keywords

cool shearer; support vector machine; multiple fault diagnostics; diagnosis fault

Abstract

In coal shearer monitoring system, the early detecting of fault is key technique for preventing the shearer fail. In this paper, the improved support vector machine theory is introduced to detected shearer fault under the mine underground, the improved algorithm based on support vector machine theory is analyzed, the multiple fault classifier is used to judge the fault types of coal shearer. The temperature fault types of coal shearer are reconstructed. Simulation results verify the validity of this method for early detecting fault under strong noise background in the coal shearer monitoring system.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - X. Zhang
AU  - X.M. Ma
AU  - Z.S. Yang
PY  - 2015/07
DA  - 2015/07
TI  - Analysis and Diagnosis of Coal Shearer Machine Fault Based on Improved Support Vector Theory
BT  - Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering
PB  - Atlantis Press
SP  - 231
EP  - 233
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-15.2015.63
DO  - 10.2991/eame-15.2015.63
ID  - Zhang2015/07
ER  -