Zhenfeng Huang
Guangxi University
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Featured researches published by Zhenfeng Huang.
Nondestructive Testing and Evaluation | 2018
Hanling Mao; Yuhua Zhang; Xinxin Li; Zhenfeng Huang; Jihua Liao; Zongkuo Guo
ABSTRACT For the fatigue crack embedded in metallic components, the non-collinear transverse wave mixing technique is applied to detect them and image the fatigue damage around crack. When two non-collinear transverse waves with same frequency meet in components, a resonance longitudinal wave can be generated if the resonance condition is satisfied; the mixing nonlinear parameter is applied to evaluate the nonlinearity of detection positions. The non-collinear wave mixing experiments are conducted on components with different length of fatigue crack. By changing the relative position of transducers, different detection positions can be controlled. According to the distribution of mixing nonlinear parameter at vertical direction, the length of fatigue crack at vertical direction can be measured. Furthermore, the mixing nonlinear parameters of different detection positions around fatigue crack are measured, the image of mixing nonlinear parameter can visualise the damage around fatigue crack which is very easy to assess the fatigue damage of components.
Journal of Materials Engineering and Performance | 2017
Yuhua Zhang; Xinxin Li; Zhenyong Wu; Zhenfeng Huang; Hanling Mao
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.
Advances in Materials Science and Engineering | 2017
Yuhua Zhang; Xinxin Li; Xianghong Wang; Zhenfeng Huang; Hanling Mao; Hanying Mao
Residual stress has significant influence on the performance of mechanical components, and the nondestructive estimation of residual stress is always a difficult problem. This study applies the relative nonlinear coefficient of critical refraction longitudinal ( ) wave to nondestructively characterize the stress state of materials; the feasibility of residual stress estimation using the nonlinear property of wave is verified. The nonlinear ultrasonic measurements based on wave are conducted on components with known stress state to calculate the relative nonlinear coefficient. Experimental results indicate that the relative nonlinear coefficient monotonically increases with prestress and the increment of relative nonlinear coefficient is about 80%, while the wave velocity only decreases about 0.2%. The sensitivity of the relative nonlinear coefficient for stress is much higher than wave velocity. Furthermore, the dependence between the relative nonlinear coefficient and deformation state of components is found. The stress detection resolution based on the nonlinear property of wave is 10 MPa, which has higher resolution than wave velocity. These results demonstrate that the nonlinear property of wave is more suitable for stress characterization than wave velocity, and this quantitative information could be used for residual stress estimation.
2016 International Conference on Advanced Electronic Science and Technology (AEST 2016) | 2016
Hanying Mao; Yuhua Zhang; Hanling Mao; Zhenfeng Huang
The effectiveness of chaos and fractal theory in analyzing ultrasonic nonlinear modulation signal was theoretically verified and a new way of using chaos and fractal theory in nondestructive testing is provided based on the simulation signal of ultrasonic nonlinear modulation effect. By constructing the simulation signal of modulation effect, the simulation signal with the chaotic character was found, and the nonlinear parameter and characteristic values of chaos theory were calculated to analyze the nonlinearity of specimens. By comparisons, the conclusion could be found that the Lyapunov exponent was sensitive to weaker nonlinearity and unsusceptible to noise.
Ndt & E International | 2009
X.H. Wang; C.M. Zhu; H.L. Mao; Zhenfeng Huang
Archive | 2008
Hanying Mao; Hanling Mao; Deliang Zeng; Zhenfeng Huang; Jianwen Fan; Tongfeng Wu; Xiaoping Li
Results in physics | 2017
Yuhua Zhang; Hanling Mao; Hanying Mao; Zhenfeng Huang
Journal of Sound and Vibration | 2017
Honglan Huang; Hanying Mao; Hanling Mao; Weixue Zheng; Zhenfeng Huang; Xinxin Li; Xianghong Wang
Journal of Central South University of Technology | 2009
Xiang-hong Wang; Chang-ming Zhu; Hanling Mao; Zhenfeng Huang
Results in physics | 2018
Hanying Mao; Yuhua Zhang; Hanling Mao; Zhenfeng Huang; Jianwen Fan; Xinxin Li; Xiaoping Li