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    张恒, 尹鸿祥, 吴毅, 李翔. 含不同尺寸菱形压痕EA4T钢车轴的疲劳性能[J]. 机械工程材料, 2021, 45(3): 61-65,82. DOI: 10.11973/jxgccl202103012
    引用本文: 张恒, 尹鸿祥, 吴毅, 李翔. 含不同尺寸菱形压痕EA4T钢车轴的疲劳性能[J]. 机械工程材料, 2021, 45(3): 61-65,82. DOI: 10.11973/jxgccl202103012
    ZHANG Heng, YIN Hongxiang, WU Yi, LI Xiang. Fatigue Performance of EA4T Steel Axle with Diamond Indentation of Different Size[J]. Materials and Mechanical Engineering, 2021, 45(3): 61-65,82. DOI: 10.11973/jxgccl202103012
    Citation: ZHANG Heng, YIN Hongxiang, WU Yi, LI Xiang. Fatigue Performance of EA4T Steel Axle with Diamond Indentation of Different Size[J]. Materials and Mechanical Engineering, 2021, 45(3): 61-65,82. DOI: 10.11973/jxgccl202103012

    含不同尺寸菱形压痕EA4T钢车轴的疲劳性能

    Fatigue Performance of EA4T Steel Axle with Diamond Indentation of Different Size

    • 摘要: 采用菱形压头挤压的方式在取自EA4T钢车轴的弯曲疲劳试样上预制压痕缺陷,研究了压痕深度对疲劳强度的影响;采用修正Murakami模型预测了疲劳强度,并引入疲劳指示参数构建了疲劳寿命预测模型;采用有限元法对压痕附近的应变进行了分析。结果表明:试样的疲劳强度随压痕深度的增加而降低,与无压痕试样相比,压痕深度为0.052 mm时,疲劳强度略微降低,压痕深度为0.112,0.504 mm时,疲劳强度显著降低;疲劳裂纹萌生于应力集中较大的预制压痕短对角线处,有限元模拟结果较准确;修正的Murakami模型能较准确地预测含压痕缺陷试样的疲劳强度,构建的疲劳寿命预测模型具有较高的精度,实测值与预测值之比均在2倍误差因子范围内。

       

      Abstract: Indentation defects were prefabricated on the bending fatigue specimen taken from EA4T steel axel by diamond indenter extrusion method. The influence of indentation depth on the fatigue strength was studied. The revised Murakami model was used to predict the fatigue strength and the fatigue indicator parameter was introduced to construct the fatigue life prediction model. The strain near indentation was analyzed by the finite element method. The results show that the fatigue strength of the sample decreased with increasing indentation depth. Compared with the sample without indentation, the fatigue strength was slightly reduced with the indentation depth of 0.052 mm, and significantly reduced with the indentation depth of 0.112 mm and 0.504 mm. The fatigue cracks were initiated at the prefabricated indentation short diagonal with large stress concentration, the finite element simulation results was accurate. The revised Murakami model could accurately predict the fatigue strength of the sample with indentation defect, and the constructed fatigue life prediction model had high accuracy. The ratio of the measured value to the predicted value was within the range of two times the error factor.

       

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