| 基本变形弹塑性问题的人工神经网络解法探讨 |
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| 引用本文： | 何芝仙,孙萍,李震.基本变形弹塑性问题的人工神经网络解法探讨[J].试验技术与试验机,2006,46(1):24-27. |
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| 作者姓名： | 何芝仙 孙萍 李震 |
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| 作者单位： | 安徽工程科技学院机械系,安徽芜湖241000 |
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| 基金项目： | 安徽省自然科学基金项目（03042306） |
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| 摘 要： | 利用体积不变原理，通过拉伸试验测量真实应力应变关系的试验数据，再利用人工神经网络（BP网络）进行逼近，从而得到用BP网络表示的应力应变本构关系。并以梁的纯弯曲和圆轴的扭转弹塑性问题为例，提出了基于人工神经网络的求解新方法，计算结果验证了其方法的合理性。
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| 关 键 词： | 应力应变 人工神经网络 弹塑性 塑性极限载荷 |
| 收稿时间： | 2005-11-21 |
| 修稿时间： | 2005-11-21 |
Solution on the Elastic-Plastic Problem for Simple Transformation Based on Artificial Neural Network |
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| He Xianzhi, Sun Ping,Li Zhen.Solution on the Elastic-Plastic Problem for Simple Transformation Based on Artificial Neural Network[J].Test Technology and Testing Machine,2006,46(1):24-27. |
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| Authors: | He Xianzhi Sun Ping Li Zhen |
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| Affiliation: | Department of Mechanical Engineering Anhui University of Technology and Science , Wuhu Anhui 241000 |
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| Abstract: | In this paper test data of real stress-strain relationship are acquired by tensioning test according to the law of volume invariable. A back propagation network is applied to build up a real stress-strain relationship by training the network with the test data. A novel method related to the BP network is presented and it can be solved some elastic-plastic problems It has been seen that the method is available according to the examples such as pure bending of a beam and torsion of a shaft. |
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| Keywords: | stress strain artificial neural networks elastic plastic limit load of plasticity |
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