1.浙江理工大学 机械工程学院,杭州 310018
2.浙江理工大学 计算机科学与技术学院,杭州 310018
吴亚莲,女,2000年生,江苏泰州人,在读硕士研究生;主要研究方向为疲劳寿命预测;E-mail:15869175259@163.com。
收稿:2024-07-14,
纸质出版:2026-01-15
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吴亚莲,叶子和,钱淼,等. 基于红外热像技术和固有损伤耗散的金属疲劳寿命预测[J]. 机械强度,2026,48(1):42-47.
WU Yalian,YE Zihe,QIAN Miao,et al. Prediction of metal fatigue life based on the infrared thermographic technique and the intrinsic damage dissipation[J]. Journal of Mechanical Strength,2026,48(1):42-47.
吴亚莲,叶子和,钱淼,等. 基于红外热像技术和固有损伤耗散的金属疲劳寿命预测[J]. 机械强度,2026,48(1):42-47. DOI: 10.16579/j.issn.1001.9669.2026.01.005.
WU Yalian,YE Zihe,QIAN Miao,et al. Prediction of metal fatigue life based on the infrared thermographic technique and the intrinsic damage dissipation[J]. Journal of Mechanical Strength,2026,48(1):42-47. DOI: 10.16579/j.issn.1001.9669.2026.01.005.
目的
2
针对传统成组法测试金属疲劳
S-N
曲线周期长、成本高,且现有红外热像法关联模型靶向性不足的问题,提出基于固有损伤耗散的疲劳寿命预测方法,实现
S-N
曲线的快速精准测定。
方法
2
首先,基于连续介质损伤力学和不可逆热力学,推导出固有损伤耗散表征模型。其次,结合温升与疲劳损伤的关联假设,构建疲劳寿命预测模型。最后,以铝合金2A12为研究对象开展红外热像法试验,将预测
S-N
曲线与成组法结果对比验证。
结果
2
结果表明,所提方法仅需单根试样即可完成测试,所得
S-N
曲线与成组法结果高度吻合,验证了模型有效性,大幅降低了测试成本与周期,为金属疲劳
S-N
曲线测定提供了高效方案。
Objective
2
Aiming at the problems of long cycle
high cost of traditional group method for testing metal fatigue
S-N
curves and insufficient targeting of existing infrared thermographic correlation models
a fatigue life prediction method based on intrinsic damage dissipation was proposed to achieve rapid and accurate determination of
S-N
curves.
Methods
2
Firstly
an intrinsic damage dissipation characterization model was derived based on continuum damage mechanics and irreversible thermodynamics. Secondly
a fatigue life prediction model was constructed by combining the correlation assumption between temperature rise and fatigue damage. Finally
infrared thermographic tests were conducted with aluminum alloy 2A12 as the research object
and the predicted
S-N
curves were compared with the results of the group method for verification.
Results
2
This method only required a single sample to complete the test
and the obtained
S-N
curves are highly consistent with those of the group method
which verified the effectiveness of the model. It significantly reduced the test cost and cycle
providing an efficient scheme for the determination of metal fatigue
S-N
curves.
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