Deyang, China
Deyang, China

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Zheng B.,Sichuan University | Yin G.,Sichuan University | Huang H.,DYTECH Machine Tool Co. | Chen Q.,DYTECH Machine Tool Co. | Fang H.,Sichuan University
Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis | Year: 2014

In order to deal with the bending deformation of long span and heavy load crossbeams, a method is proposed to improve the geometric precision of the crossbeam, which combines FEA numerical computation and BP neural networks to predict the bending deformation curve of the crossbeam and prefabricate the compensation curve. The slide carriage is located at a series of working states, and the deformation is calculated using ANSYS software in order to obtain the training samples. By adjusting the appropriate parameters in Matlab software, the BP neural network is established to satisfy the error requirement. The deformation and compensation curve of the crossbeam are predicted through the trained neural network and the crossbeam is thus manufactured according to the compensation curve. The results of the bending deformation measurement demonstrate that the predicted values of the neural network match well with the experimental results, in which the relative error is less than 15% and the computing time is just 0.27 seconds. This method can accurately predict the bending deformation of the crossbeam and carry on compensation. Moreover, it provides new ideas for research as well as technical guidance for improving the crossbeam structure design and obtaining a perfect arch in advance.


Zheng B.,Sichuan University | Yin G.-F.,Sichuan University | Huang H.,DYTECH Machine Tool Co. | Chen Q.,DYTECH Machine Tool Co. | Fang H.,Sichuan University
Journal of Donghua University (English Edition) | Year: 2013

In order to decrease the deformation and stress and increase the natural frequency of the fixed table, a method of optimization driven by the sensitivity and topology analyses is proposed. The finite element model of the fixed table is constructed and analyzed by using ANSYS software. Based on the results of static analysis and modal analysis, the maximum deformation, the maximum stress, and natural frequencies are obtained. Then, the sensitivity analysis and topology optimization are carried out to find out the parameters to be optimized. The fixed table is reconstructed according to optimal design scheme. In the comparison of the results between original model and the optimized one, the maximum deformation and stress are decreased by 71.73% and 60.27% respectively. At the same time, the natural frequencies from the first mode to the sixth mode are increased by 30.28%, 29.57%, 29.51%, 31.52%, 22.19%, and 21.80%, respectively. The method can provide technology guide for the design and optimization of machining structure. Copyright © 2013 Editorial Department of Journal of Donghua University.

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