Title :
Parameter Estimation of Reliability Model of Hydraulic System for Vibratory Roller Based on Adaptive Linear Neural Network
Author :
Heqing Li ; Qing Tan
Author_Institution :
Sch. of Mech. & Electr. Eng., Center South Univ., Changsha
Abstract :
Aimed at reliability model of hydraulic system of the vibratory roller, combined adaptive linear neural network technique with system reliability engineer theory, a way for parameter estimation of reliability model based on adaptive linear neural network was developed. The model parameters and function of reliability for the first fault time of hydraulic system of the vibratory roller was gained by this means. The parameters estimation of the reliability model could quickly obtained if the life data of the known probability distribution was input to the model of the adaptive linear neural network. Compared with graphic method and analytic method, this method was operated more easily in the engineering.
Keywords :
hydraulic systems; mechanical engineering computing; neural nets; parameter estimation; rollers (machinery); adaptive linear neural network; graphic method; hydraulic system; parameter estimation; probability distribution; system reliability engineer theory; vibratory roller; Adaptive systems; Artificial neural networks; Biological neural networks; Hydraulic systems; Neural networks; Neurons; Parameter estimation; Reliability theory; Transfer functions; Vectors;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
DOI :
10.1109/ICICTA.2008.377
