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Fatigue Life Prediction of Metallic Materials Based on the Combined Nonlinear Ultrasonic Parameter

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Abstract

The fatigue life prediction of metallic materials is always a tough problem that needs to be solved in the mechanical engineering field because it is very important for the secure service of mechanical components. In this paper, a combined nonlinear ultrasonic parameter based on the collinear wave mixing technique is applied for fatigue life prediction of a metallic material. Sweep experiments are first conducted to explore the influence of driving frequency on the interaction of two driving signals and the fatigue damage of specimens, and the amplitudes of sidebands at the difference frequency and sum frequency are tracked when the driving frequency changes. Then, collinear wave mixing tests are carried out on a pair of cylindrically notched specimens with different fatigue damage to explore the relationship between the fatigue damage and the relative nonlinear parameters. The experimental results show when the fatigue degree is below 65% the relative nonlinear parameter increases quickly, and the growth rate is approximately 130%. If the fatigue degree is above 65%, the increase in the relative nonlinear parameter is slow, which has a close relationship with the microstructure evolution of specimens. A combined nonlinear ultrasonic parameter is proposed to highlight the relationship of the relative nonlinear parameter and fatigue degree of specimens; the fatigue life prediction model is built based on the relationship, and the prediction error is below 3%, which is below the prediction error based on the relative nonlinear parameters at the difference and sum frequencies. Therefore, the combined nonlinear ultrasonic parameter using the collinear wave mixing method can effectively estimate the fatigue degree of specimens, which provides a fast and convenient method for fatigue life prediction.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Number 51365006) and the manufacturing system and advanced manufacturing technology of Guangxi key laboratory project (Contact Number 14-045-15S05).

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Authors and Affiliations

  1. Institute of Light Industrial and Food Engineering, Guangxi University, Nanning, 530004, China

    Yuhua Zhang

  2. College of Mechanical Engineering, Guangxi University, Nanning, 530004, China

    Xinxin Li, Zhenyong Wu, Zhenfeng Huang & Hanling Mao

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  1. Yuhua Zhang
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  2. Xinxin Li
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  3. Zhenyong Wu
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  4. Zhenfeng Huang
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  5. Hanling Mao
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Correspondence to Hanling Mao.

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Zhang, Y., Li, X., Wu, Z. et al. Fatigue Life Prediction of Metallic Materials Based on the Combined Nonlinear Ultrasonic Parameter. J. of Materi Eng and Perform 26, 3648–3656 (2017). https://doi.org/10.1007/s11665-017-2811-7

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  • DOI: https://doi.org/10.1007/s11665-017-2811-7

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