Title :
Intelligent fault diagnosis methodology of hydraulic traveling system for construction machinery
Author :
Li, Yunhua ; Feng, Xiaogang ; Yang, Liman
Author_Institution :
Coll. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China
Abstract :
This paper established a simulation platform of intelligent fault diagnosis of traveling hydraulic system for multi-axle driving construction machinery using AMESim software. The corresponding parameter variations under the fault condition can be simulated by changing the parameters of related components in the simulation model, then the system response while the fault can be calculated so that fault sample data can be generated to train the Neural Network. Based on MATLAB, the fault diagnosis process was realized and the knowledge base was established. The simulation results illustrates that this method has the better precision, and can be used to realize the intelligent fault diagnose of traveling hydraulic system for construction machinery.
Keywords :
construction equipment; construction industry; fault diagnosis; hydraulic systems; knowledge based systems; learning (artificial intelligence); machinery; AMESim software; MATLAB; fault condition; fault sample data; hydraulic traveling system; intelligent fault diagnosis methodology; knowledge base; multiaxle driving construction machinery; neural network training; parameter variations; simulation model; Fault diagnosis; Load modeling; Mathematical model; Neural networks; Valves; AMESim; Neural Network; construction machinery; fault diagnosis; traveling hydraulic system;
Conference_Titel :
Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-0312-5
DOI :
10.1109/INDIN.2012.6301377
