Title :
Mine Main Fan Intelligent Fault Diagnosis Model Research
Author :
Xiaohua, Liu ; Xiangling, Ma
Author_Institution :
Naval Aeronaut. Eng. Univ., Yantai, China
Abstract :
In view of the urgent needs of the intelligent fault diagnosis of the current mine main fan, and according to the fault type characteristic of mine main fan and analyzing to generate unavoidably the causes that depending on a single information detection conduct fault diagnosis, mine main fan intelligent fault diagnosis model based on multi-sensor information fusion is presented by this paper. It provides forceful support for system monitoring and fault diagnosis in mining production processing.
Keywords :
fans; fault diagnosis; mining equipment; production engineering computing; sensor fusion; information detection; information fusion; intelligent fault diagnosis; mine main fan; mining production processing; multi-sensor; Analytical models; Data mining; Data models; Fault diagnosis; Feature extraction; Fuel processing industries; Monitoring; Information fusion; Main fan; Multi-sensor; intelligent fault diagnosis;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
Conference_Location :
Shenzhen, Guangdong
Print_ISBN :
978-1-61284-289-9
DOI :
10.1109/ICICTA.2011.214
