# [1]伍建国,孙庆鸿,毛海军,等.基于BP神经网络模型的磨床部件动态灵敏度分析[J].东南大学学报(自然科学版),2002,32(4):601-604.[doi:10.3969/j.issn.1001-0505.2002.04.014] 　Wu Jianguo,Sun Qinghong,Mao Haijun,et al.Dynamic sensitivity analysis of grinder parts based on the BP neural network model[J].Journal of Southeast University (Natural Science Edition),2002,32(4):601-604.[doi:10.3969/j.issn.1001-0505.2002.04.014] 点击复制 基于BP神经网络模型的磨床部件动态灵敏度分析() 分享到： var jiathis_config = { data_track_clickback: true };

32

2002年第4期

601-604

2002-07-20

## 文章信息/Info

Title:
Dynamic sensitivity analysis of grinder parts based on the BP neural network model

1 (东南大学机械工程系,南京 210096; 2 无锡机床股份有限公司,无锡 210061
Author(s):
1 Department of Mechanical Engineering, Southeast University, Nanjing 210096, China
2 Wuxi Machine Tool Ltd.,Wuxi 210061, China

Keywords:

TB115
DOI:
10.3969/j.issn.1001-0505.2002.04.014

Abstract:
With the help of parametrization model, the dynamic properties of the grinder part were calculated and the train sample of the BP neural network was obtained quickly. The dynamic analysis models based on the neural network are built up. The relationship between dimensions and dynamic properties of the grinder’s part is defined as the mathematic relationship between inputs and outputs of the BP neural network. Thus the analysis of dynamic sensitivity for grinder’s part can be carried out conveniently and quickly. This method is particularly suitable for calculation of design optimization for large and complex parts.

## 参考文献/References:

[1] 申铉国,张铁强.人工神经网络在机械部件设计中的应用研究[J].机械工程学报,1992,28(6):82-85.
Shen Xuanguo,Zhang Tieqiang.A study on artifical network using in machine design[J].Chinese Journal of Mechanical Engineering,1992,28(6):82-85.(in Chinese)
[2] 黄洪钟,黄文培.神经网络技术在机械工程中的应用与展望[J].机械科学与技术,1995(4):35-39.
Huang Hongzhong,Huang Wenpei.Neural network and application to mechanical engineering[J].Mechanical Science and Technology,1995(4):35-39.(in Chinese)
[3] 黄洪钟,黄文培.前馈神经网络的一种权重分析方法及其在机械结构分析中的应用[J].机械科学与技术,1996(6):851-854.
Huang Hongzhong,Huang Wenpei.An approach to the weights analysis of feedforward neural networks and its application to the analysis of mechanical structures[J].Mechanical Science and Technology,1996(6):851-854.(in Chinese)
[4] 王金诺,黄文培.BP神经网络在起重机箱形主梁优化设计中的应用[J].起重运输机械,1998(6):22-25.
Wang Jinnuo,Huang Wenpei.Application of BP neural networks to the optimization design of the crane box grids[J]. Hoisting Transportation Machinery,1998(6):22-25.(in Chinese)
[5] Levin R T,Lieven A J.Dynamic finite element model updating using neural networks[J].Journal of Sound & Vibration,1998,210(5):593-607.
[6] Hecht-Nielsen.Theory of the back propagation neural networks[A].In:Proc of the IEEE 1st ICNN[C].IEEE Press,1987(3):453-462.
[7] Choi K K.Design sensitivity analysis of structure-induced noise and vibration[J]. Journal of Vibration and Acoustics,1997,119:173-179.
[8] Kenneth F Alvin.Efficient computation of eigenvector sensitivities for structural dynamic[J].AIAA J,1997,35(11):1760-1766.

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