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International Standard Serial Number:
ISSN 1001-4551
Sponsor:
Zhejiang University;
Zhejiang Machinery and Electrical Group
Edited by:
Editorial of Journal of Mechanical & Electrical Engineering
Chief Editor:
ZHAO Qun
Vice Chief Editor:
TANG ren-zhong,
LUO Xiang-yang
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86-571-87041360,87239525
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No.9 Gaoguannong,Daxue Road,Hangzhou,China
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meem_contribute@163.com
Abstract: Aiming at the problem of difficult to ensure the strength and dynamic characteristics of diaphragm coupling under high speed and compound working conditions, the strength and dynamic characteristics of the existing disc coupling were studied, an optimization method based on back-propagation neural network (BPNN) and multi-objective optimization genetic algorithm (MOOGA) was proposed. Firstly, in order to obtain the key parameters required for optimization, based on the method of orthogonal experiment combined with multivariate analysis of variance, the key parameters were selected. Then, based on the BPNN model, the objective function of the key parameters and cross-sectional stress was constructed, as well as the objective function of the key parameters and bending stiffness was constructed, the accuracy of the polynomial solution objective function was compared, and the accuracy of the BPNN method in solving the objective function was verified. Finally, multi-objective optimization of the coupling design parameters was carried out through MOOGA, the optimization results were compared with those before optimization. The research results indicate that the proposed method is used to optimize the design parameters of the coupling, and the dangerous cross-sectional stress of the disc can be effectively reduced under the condition of meeting the stiffness requirements of the coupling. After optimization, the dangerous stress of the coupling is reduced by 18.2%, the bending stiffness of the coupling is reduced by 5.05%, and the angular compensation capacity of the coupling is increased by 0.1°. The effectiveness of the simulation is proved and a reference is provided for the parameter optimization design of flexible couplings.