Title :
Application of fuzzy neural network in fault diagnosis of hydraulic system
Author :
Li Zhang ; Yong Zhao ; Yihe Xu
Author_Institution :
No.7 Dept., Naval Aeronaut. & Astronaut. Univ., Yantai, China
Abstract :
Hydraulic system is a complex mechanical-electronic-hydraulic system, its faults have multiple, uncertain and hidden features. Through embedding sensors in the hydraulic system, the paper can real-time monitor the status of the system. At the same time, through making full use of information processing capability of fuzzy theory and self-learning and function approximation capability of neural network, the paper could integrate the state parameters and diagnose faults of hydraulic system. With simulation example, the paper can find that application of fuzzy neural network in fault diagnosis of hydraulic system has advantages of simple operation, high reliability and high automatization.
Keywords :
fault diagnosis; feature extraction; function approximation; fuzzy neural nets; hydraulic systems; intelligent sensors; maintenance engineering; complex mechanical-electronic-hydraulic system; embedding sensor; fault diagnosis; function approximation capability; fuzzy neural network; fuzzy theory; hidden feature; hydraulic system; information processing capability; real-time monitor; selflearning; Biological neural networks; Fault diagnosis; Fuzzy neural networks; Hydraulic systems; Sensor systems; Temperature sensors; fault diagnosis; fuzzy neural network; hydraulic system;
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang, China
Print_ISBN :
978-1-61284-087-1
DOI :
10.1109/EMEIT.2011.6023274
