Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling

Application and Research of SVM in Coal Mine Fan Condition Monitoring

Authors
Guo Xiucai, Wang Kaixuan
Corresponding Author
Guo Xiucai
Available Online June 2015.
DOI
https://doi.org/10.2991/kam-15.2015.38How to use a DOI?
Keywords
coal mine; fan; support vector machine; state prediction.
Abstract
In order to real time control of coal mine fan equipment running status, A kind of mine fan state monitoring system based on ZigBee has been designed, Through collect and processing the fan operation parameters, such as temperature, vibration, realize the function that real-time monitoring the fan’s state. For mine fan condition monitoring in the process of the character of sample data is limited, support vector machine will be used to predict the trend of fan vibration signal, realize the prediction of running status of fan, provide a reference basis to Fan maintenance person. The experimental results show that support vector machine (SVM) model to predict the correctness and feasibility of fan vibration signal.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
Series
Advances in Intelligent Systems Research
Publication Date
June 2015
ISBN
978-94-62520-87-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/kam-15.2015.38How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Guo Xiucai
AU  - Wang Kaixuan
PY  - 2015/06
DA  - 2015/06
TI  - Application and Research of SVM in Coal Mine Fan Condition Monitoring
BT  - Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
PB  - Atlantis Press
SP  - 136
EP  - 139
SN  - 1951-6851
UR  - https://doi.org/10.2991/kam-15.2015.38
DO  - https://doi.org/10.2991/kam-15.2015.38
ID  - Xiucai2015/06
ER  -