Title :
On-line fault diagnosis study for roller bearing based on fuzzy fault tree
Author :
Yao, Zheng ; Lou, Guohuan ; Song, Xuemei ; Zhou, Yuan
Author_Institution :
Coll. of Comput. & Autom. Control, Hebei Polytech. Univ., Tangshan, China
Abstract :
The roller bearings are commonly used in rotating machinery and play an important role. In this paper fuzzy theory and fault tree are used for On-line fault diagnosis of roller bearing. The principle of fuzzy diagnosis is taken as basics and symptom sets and faults sets are extracted through fault tree analysis. According to judgement rules the location of faults is made sure. Experiments show this method is effective for fault diagnosis of roller bearing.
Keywords :
fault diagnosis; fault trees; fuzzy set theory; mechanical engineering computing; rolling bearings; turbomachinery; fuzzy fault tree; fuzzy theory; online fault diagnosis; roller bearing; rotating machinery; Asia; Automatic control; Educational institutions; Fault diagnosis; Fault trees; Fuzzy control; Fuzzy set theory; Machinery; Robotics and automation; Rolling bearings; fault diagnosis; fault tree; fuzzy theory;
Conference_Titel :
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5192-0
Electronic_ISBN :
1948-3414
DOI :
10.1109/CAR.2010.5456874