Application of Fuzzy Clustering Algorithm in Rotary Drill on Fault Diagnosis
- https://doi.org/10.2991/lemcs-15.2015.83How to use a DOI?
- Rotary drills; Intelligent fault diagnosis; Fuzzy clustering analysis method; Detection; Forecast
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/lemcs-15.2015.83 ID - Wei2015/07 ER -