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Volume 40 Issue 4
Apr.  2018
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Article Contents
ZHANG Jin, CHAI Meng-yu, XIANG Jing-hai, DUAN Quan. Fatigue damage evaluation of 316LN stainless steel using acoustic emission monitoring[J]. Chinese Journal of Engineering, 2018, 40(4): 461-468. doi: 10.13374/j.issn2095-9389.2018.04.009
Citation: ZHANG Jin, CHAI Meng-yu, XIANG Jing-hai, DUAN Quan. Fatigue damage evaluation of 316LN stainless steel using acoustic emission monitoring[J]. Chinese Journal of Engineering, 2018, 40(4): 461-468. doi: 10.13374/j.issn2095-9389.2018.04.009

Fatigue damage evaluation of 316LN stainless steel using acoustic emission monitoring

doi: 10.13374/j.issn2095-9389.2018.04.009
  • Received Date: 2017-06-21
  • The initiation and growth of fatigue cracks usually lead to serious fatigue failure of steel structures such as pressure vessels and pipelines. Therefore, for the safety and reliability of engineering structures, monitoring the fatigue crack growth and evaluating the severity of fatigue damage are important. An investigation of fatigue damage evaluation of 316LN stainless steel was presented by using the in situ acoustic emission (AE) monitoring technique. Fatigue crack propagation tests of 316LN stainless steel were carried out. The direct-current potential-drop method was used to measure fatigue crack propagation. At the same time, the AE technique was used to monitor propagation of the fatigue cracks in real time. The fatigue damage of 316LN stainless steel was qualitatively assessed by AE multi-parametric analyses such as the AE count, energy, and amplitude. Moreover, the quantitative relationships among AE parameters and the linear elastic fracture mechanics parameters were established for predicting the remaining fatigue life. The results show that the AE technique is effective for evaluating the severity of fatigue damage of 316LN stainless steel. The transition point on the curves of cumulated count, energy, and amplitude indicates that the fatigue crack propagates into the rapid crack propagation stage. This obvious change in AE could potentially provide failure warnings for researchers or engineers. Furthermore, the analyses of waveform and frequency show that the noise signal with low amplitude and long duration contains complex frequency components, whereas the crack propagation signal is a type of burst signal and the frequency is mainly distributed in the range from 80 to 170 kHz. In addition, the quantitative relations between fatigue crack propagation rate and AE rates such as the count rate, energy rate, and the amplitude rate were found to be linear, and these relations were used to predict fatigue crack length. The predicted fatigue crack lengths showed good agreement with the measured crack lengths. The results of the present investigation will be helpful for providing fatigue failure warnings and predicting the remaining fatigue life of engineering structures.

     

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