Application of Fuzzy Clustering Algorithm in Rotary Drill on Fault Diagnosis

DOI

10.2991/lemcs-15.2015.83How to use a DOI?

Keywords

Rotary drills; Intelligent fault diagnosis; Fuzzy clustering analysis method; Detection; Forecast

Abstract

As one of the key equipment of mining, rotary drills have a high incidence of failure. In the actual application, it is hard to fault diagnosis for roller transfer. In order to solve this problem, design a roller transfer control of fault self-diagnosis system with the fuzzy clustering analysis method combined with intelligent fault diagnosis technology, realizing the fault detection and prediction of rock drills, which can timely malfunctioning rotary drills. The fault information is given, determining the location, type and severity of the fault. For the improvement of rotary drills fault forecasting, judgment and processing have a vital role.

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  - Hongbo Wei
AU  - Wen You
AU  - Binglin Li
PY  - 2015/07
DA  - 2015/07
TI  - Application of Fuzzy Clustering Algorithm in Rotary Drill on Fault Diagnosis
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 431
EP  - 434
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-15.2015.83
DO  - 10.2991/lemcs-15.2015.83
ID  - Wei2015/07
ER  -