DocumentCode :
2682183
Title :
Application of hydraulic system in condition measurement and fault diagnose based on of information fusion
Author :
Liang, Guihang ; Mu Chunyan ; Yu Jingnuo ; Feng, Baofu
Author_Institution :
Sch. of Traffic, Ludong Univ., Yantai, China
Volume :
5
fYear :
2010
fDate :
27-29 March 2010
Firstpage :
86
Lastpage :
89
Abstract :
A method for fault diagnoses of hydraulic system for construction machinery and equipment based on the information fusion logic theory is put forward. The theory of the method is described. It can get the data of hydraulic system for construction machinery and equipment by various type sensors. The model of hydraulic system for construction machinery and equipment condition measurement and fault diagnoses is set up by using the state data as learning samples. And the hydraulic system for construction machinery and equipment state is identified by the model. The results after tested show that this method has the advantages that various tested information of fault symptoms can be made full use of to diagnose accurately faults of the hydraulic system for construction machinery and equipment. It can improve the veracity for diagnose the fault of hydraulic system.
Keywords :
condition monitoring; construction equipment; fuzzy neural nets; hydraulic systems; machinery; production engineering computing; sensor fusion; condition measurement; construction equipment; construction machinery; fault diagnosis; fuzzy neural network; hydraulic system; information fusion logic theory; sensors; Condition monitoring; Data analysis; Educational institutions; Fuzzy neural networks; Hydraulic systems; Information analysis; Machinery; Sensor fusion; Sensor systems; System testing; condition measurement; fault diagnosis; fuzzy neural network; information fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-5845-5
Type :
conf
DOI :
10.1109/ICACC.2010.5487291
Filename :
5487291
Link To Document :
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