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基于BP神經(jīng)網(wǎng)絡(luò)的TC11鈦合金工藝-性能模型預(yù)測(cè)
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國(guó)家“973”計(jì)劃 (2007CB613807)；新世紀(jì)優(yōu)秀人才支持計(jì)劃 (NCET-07-0696)；凝固技術(shù)國(guó)家重點(diǎn)實(shí)驗(yàn)室開(kāi)放課題 (35-TP-2009)


Model Prediction of Processing-Property of TC11 Titanium Alloy Using Artificial Neural Network
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    摘要:

    材料工藝與性能的關(guān)系具有復(fù)雜、非線性交互等特點(diǎn)。本文根據(jù)TC11鈦合金力學(xué)性能與其影響因素之間的映射關(guān)系，以大量的試驗(yàn)數(shù)據(jù)為基礎(chǔ)，建立了BP神經(jīng)網(wǎng)絡(luò)模型。模型的輸入包括鍛造溫度、鍛后冷卻方式等熱加工工藝參數(shù)；輸出為常用的力學(xué)性能指標(biāo)，即抗拉強(qiáng)度、屈服強(qiáng)度、延伸率和斷面收縮率。運(yùn)用該模型對(duì)TC11鈦合金力學(xué)性能進(jìn)行了預(yù)測(cè)，并通過(guò)試驗(yàn)數(shù)據(jù)對(duì)模型的預(yù)測(cè)精度進(jìn)行了可靠性驗(yàn)證。同時(shí)，運(yùn)用已建立的神經(jīng)網(wǎng)絡(luò)模型對(duì)TC11鈦合金工藝參數(shù)與力學(xué)性能的關(guān)系進(jìn)行了分析。結(jié)果表明，所建立的力學(xué)性能預(yù)測(cè)模型具有良好的外推能力，并且可以很好地反映出該合金的工藝-性能之間的復(fù)雜關(guān)系

    Abstract:

    The relationship between processing and property of materials is complex. In the present investigation, based on a lot of experimental data, the technique of artificial neural network was employed to develop the prediction model of processing and property for TC11 titanium alloy. The inputs of the neural network were different forging process parameters such as forging temperature, forging style and cooling style. The outputs of the model were the tensile properties, including ultimate tensile strength, yield strength, elongation and reduction of area. The mechanical properties of TC11 titanium alloy were predicted by the established model, and the accuracy of the prediction was compared with the experimental data. Besides, the model was used to study the influence of the processing on the properties of TC11 titanium alloy. Results show that the model can predict the properties of this alloy with high accuracy and reliability, and the complex relationship between processing and properties can be well presented by the trained neural network, which is consistent with the metallurgical trends

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孫 宇,曾衛(wèi)東,趙永慶,邵一濤,韓遠(yuǎn)飛,馬 雄.基于BP神經(jīng)網(wǎng)絡(luò)的TC11鈦合金工藝-性能模型預(yù)測(cè)[J].稀有金屬材料與工程,2011,40(11):1951~1955.[Sun Yu, Zeng Weidong, Zhao Yongqing, Shao Yitao, Han Yuanfei, Ma Xiong. Model Prediction of Processing-Property of TC11 Titanium Alloy Using Artificial Neural Network[J]. Rare Metal Materials and Engineering,2011,40(11):1951~1955.]
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  • 收稿日期:2010-11-25
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