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Effect of Quenching Media and Tempering Temperature on Fatigue Property and Fatigue Life Estimation Based on RBF Neural Network of 0.44 % Carbon Steel

机译:淬火介质和回火温度对0.44%碳钢RBF神经网络的疲劳性能和疲劳寿命估计的影响

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In this work, the effect of the quenching media (brine, water, and two types of naphthenic mineral oils) and the tempering temperature (200, 400, 600 °C) on the static mechanical properties and the fatigue life has been investigated using 300 fatigue and 36 static tension tests. S–N curves and standard deviations of fatigue life under each heat treatment condition were calculated and shown. The fracture surfaces of the selected 11 specimens were observed by the scanning electron microscope and the reasons of affecting the fatigue life were discussed. To estimate the mean fatigue life under the conditions of any given tempering temperature and cycle stress amplitude based on 300 fatigue tests, the mean fatigue life estimation method based on RBF neural network was presented and verified by 12 other fatigue tests. The test results have shown that (1)?the mean fatigue life decreases with the increase of tempering temperature for the same quenching media, (2)?the mean fatigue life using brine is more than water which is more than naphthenic mineral oils for the same tempering temperature, and (3)?the proposed method based on RBF neural network could accurately estimate the mean fatigue life when the tempering temperature and cyclic stress amplitude are given for each quenching medium.
机译:在这项工作中,使用300,研究了淬火培养基(盐水,水和两种环氧矿物油)和回火温度(200,400,600℃)的效果和疲劳寿命的影响疲劳和36个静态张力试验。计算并显示了在每个热处理条件下疲劳寿命的S-N曲线和标准偏差。通过扫描电子显微镜观察所选择的11样品的断裂表面,讨论了影响疲劳寿命的原因。为了估计基于300疲劳试验的任何给出的回火温度和循环应力幅度的条件下的平均疲劳寿命,提出了基于RBF神经网络的平均疲劳寿命估计方法,并通过12个其他疲劳试验验证。测试结果表明(1)?平均疲劳寿命随着相同淬火培养基的回火温度的增加而降低,(2)?使用盐水的平均疲劳寿命大于含环碱矿物油相同的回火温度和(3)?基于RBF神经网络的所提出的方法可以准确地估计每个淬火介质给出回火温度和循环应力振幅时的平均疲劳寿命。

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