基于BP神经网络的TB17钛合金热变形行为研究

石尚; 董洪波; 姜智勇; 王新南; 朱知寿

doi:10.15980/j.tzzz.2019.04.022

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基于BP神经网络的TB17钛合金热变形行为研究
Hot Deformation Behavior of TB17 Titanium Alloy Based on BP Neural Network
2019年39卷第4期页码：434-438
纸质出版日期： 2019 ，
DOI： 10.15980/j.tzzz.2019.04.022

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[1]石尚,董洪波,姜智勇,王新南,朱知寿.基于BP神经网络的TB17钛合金热变形行为研究[J].特种铸造及有色合金,2019,39(04):434-438.

Shi Shang, Dong Hongbo, Jiang Zhiyong, et al. Hot Deformation Behavior of TB17 Titanium Alloy Based on BP Neural Network[J]. Special Casting & Nonferrous Alloys, 2019,39(4):434-438.
[1]石尚,董洪波,姜智勇,王新南,朱知寿.基于BP神经网络的TB17钛合金热变形行为研究[J].特种铸造及有色合金,2019,39(04):434-438. DOI： 10.15980/j.tzzz.2019.04.022.

Shi Shang, Dong Hongbo, Jiang Zhiyong, et al. Hot Deformation Behavior of TB17 Titanium Alloy Based on BP Neural Network[J]. Special Casting & Nonferrous Alloys, 2019,39(4):434-438. DOI： 10.15980/j.tzzz.2019.04.022.

摘要

利用Gleeble-3500热模拟试验机

在变形温度为800～1 000℃

应变速率为0.001～10s-1条件下对TB17钛合金进行等温恒应变速率压缩试验

获得不同参数下合金的流动应力数据。通过金相组织观察

研究了热变形过程中的合金组织的变化规律。建立了具有BP算法的人工神经网络

利用所建立的BP网络模型对TB17钛合金的流动应力进行预测

发现预测值与试验值符合较好

验证了该BP网络本构关系模型的准确性。

Abstract

The hot deformation behavior of TB17 titanium alloy was investigated with Gleeble-3500 simulator at strain rates of 0.001～10 s-1 and 800～1 000℃

obtaining the flow stress data at varied temperatures and varied strain rates as well as different true strain.Microstructure change can be observed through metallographic observation.Based on experimental data and neural network knowledge

an artificial neural network with back propagation algorithm was established

and knowledge based constitutive relations model was developed after training.The flow stress in the alloys was predicted by the BP neural network.The results are well in agreement with the experimental ones

confirming the availability of the model.

关键词

TB17钛合金热变形行为BP神经网络热加工工艺

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新型低成本钛合金的热变形行为研究