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Fatigue Life Prediction Model with Back Stress Energy Method Based on the Machined Surface Layer of High Strength Steel
- Acta Armamentarii Vol. 44, Issue 3, Pages: 806-815(2023)
- 作者机构：
1. 太原理工大学 机械与运载工程学院，山西 太原 030024
2. 北京理工大学 机械与车辆学院，北京 100081
3. 山西柴油机工业有限责任公司，山西 大同 037036
- 作者简介：
- 基金信息：
DOI：10.12382/bgxb.2021.0828
CLC：Received：05 December 2021，
Published：28 March 2023
- 稿件说明：
移动端阅览
Yong WANG, Xibin WANG, Zhibin WANG, et al. Fatigue Life Prediction Model with Back Stress Energy Method Based on the Machined Surface Layer of High Strength Steel[J]. Acta Armamentarii, 2023, 44(3): 806-815.
Yong WANG, Xibin WANG, Zhibin WANG, et al. Fatigue Life Prediction Model with Back Stress Energy Method Based on the Machined Surface Layer of High Strength Steel[J]. Acta Armamentarii, 2023, 44(3): 806-815. DOI： 10.12382/bgxb.2021.0828.
摘要
循环应变能法从疲劳损伤机理的角度对疲劳寿命进行预测，能够很好地解释疲劳断裂行为，故得到广泛应用。然而，对材料整体性能的大量试验研究中常常不考虑加工表面完整性，从而影响了能量法的预测精度，为此提出一种考虑加工表面完整性的循环背应力能法疲劳寿命预测修正模型，通过引入残余应力随深度围成的面积作为影响因子来考虑加工表面层力学特征对总背应力能的影响，将微裂纹不扩展阈值作为影响因子表征表面层几何和组织特征对总背应力能的作用。研究结果表明：针对淬火回火前的重载车辆扭力轴高强度钢材料，考虑加工表面完整性的修正模型疲劳寿命预测误差分散带缩小38%，预测精度提高25%，与疲劳断裂后实时统计单周次循环背应力能密度的模型具有相同的误差分散带(1.25倍)，克服了传统能量法需要在疲劳试验后才能进行寿命预测的缺点；针对淬火回火后的超高强度钢材料，考虑加工表面完整性的修正模型疲劳寿命预测精度从72.7%提升到了92.2%，克服了疲劳断裂后实时统计单周次循环背应力能密度预测模型的失效性，误差分散带从3.30倍降到了1.41倍；新模型提高了能量法在不同加工表面层特征的适用性，实现了面向服役性能的加工表面完整性评价。
Abstract
The cyclic strain energy method has been widely used because it can predict fatigue life from the perspective of fatigue damage mechanism and explain many fatigue phenomena which cannot be explained by other methods. However
in the large amount of empirical study of the overall properties of materials
the machined surface layer is often not considered
which affects the prediction accuracy of the energy method. Based on the energy method
a new fatigue life prediction model with back stress energy based on the machined surface layer of high strength steel was proposed. The effect of surface mechanical characteristics on total back stress energy was considered by introducing the area of residual stress with depth as the influence factor
while the effect of surface layer geometry and metallurgy on strain energy was considered by taking the non-propagation threshold of microcrack as the influence factor. The results showed that: the dispersion band of fatigue life prediction error for the modified model considering surface integrity was reduced by 38% and the prediction accuracy improved by 25%; it had the same error dispersion band (1.25 times) as the model for the real-time statistical single cycle energy density after fatigue fracture
which overcomes the disadvantage that the fatigue life can be predicted only after the fatigue test of the traditional energy method; for quenched and tempered high strength steel
the average accuracy of fatigue life prediction of the modified model considering surface integrity was improved from 72.7% to 90.6%; compared with the real-time statistics after fatigue fracture
the error dispersion band of the single cycle energy density prediction model was reduced from 3.30 times to 1.41 times. This model provides a method to assess the fatigue service performance of the machined surface layer
and improves the applicability of strain energy in different machined surface layer characteristics.
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references
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