Title: Modelling approach of a cymene-Si-Oil damping shock absorber based on neural network algorithm
Authors: Yang Ping, Tan Jiqing, Liao Ningbo, Yang Jianbo
Addresses: School of Mechanical Engineering, Jiangsu University, Zhenjiang, 212013, China. ' Research Center of Advanced Design and Manufacturing, Guilin University of Electronic Technology, Guilin, 541004, China. ' School of Mechanical Engineering, Jiangsu University, Zhenjiang, 212013, China. ' Research Center of Advanced Design and Manufacturing, Guilin University of Electronic Technology, Guilin, 541004, China
Abstract: A new kind of shock absorber with oil damping through coupling the cymene-Si-oil and spring is designed for reinforcement of electronic-information equipment. It is important to evaluate the damping force properties of the shock absorber. The objective of this paper is to apply a BP neural-network model to simulate non-linear characteristics occurring within the shock absorber. Comparisons between the experimental data and simulation confirm the validity of the model. So the research work submits a valid perspective for design and evaluation of the new cymene-Si-oil damping shock absorber.
Keywords: backprogagation networks; neural networks; cymene-Si-oil damping; shock absorbers; modelling; simulation; oil damping.
International Journal of Product Development, 2008 Vol.6 No.1, pp.81 - 93
Published online: 29 Jun 2008 *
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