266
C. Ye et al.
5] reported that the hydrogen bubble burst AE signal has a longer rise time and a
higher count with a longer duration resonant waveform. These characteristics are also
consistent with the characteristics of the second phase of the AE signal of this test.
In combination with the observation during the test, the AE source corresponding to
the second stage AE signal should be bubble rupture.
22.4 Conclusion
1. AE technology has the ability to monitor the corrosion damage of zirconium
metal and is a powerful tool for studying pitting corrosion of zirconium metal.
2. The characteristics of AE signals in different stages of pitting corrosion of zirconium metal are quite different, and different damage stages of pitting can be
identified according to signal characteristics.
3. Compared with the pitting nucleation stage, the AE signal in the extended stage
has large activity, low amplitude, and small counting, energy, rise time and
duration.
4. There are two main types of zirconium metal pitting signal waveforms, in which
the pitting nucleation stage mainly produces short-wavelengths with small duration, and the pitting extension stage mainly produces resonance waves with longer
duration.
5. Zirconium metal pitting signal waveform mode is composed of flexual wave and
expansion wave. During the pitting extension phase, the AE signal is dominated
by the low-frequency bending mode.
6. Passivation film destruction and hydrogen bubble rupture are the two main AE
sources of zirconium metal pitting process.
References
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steel by means of acoustic emission and potentiodynamic methods. Corros. Sci. 45, 1747–1756
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2. M. Fregonese, H. Idrissi, H. Mazille, L. Renaud, Y. Cetre, Initiation and propagation steps in
pitting corrosion of austenitic stainless steels: monitoring by acoustic emission. Corros. Sci.
43, 627–641 (2001)
3. J. Xu, X. Wu, E.-H. Han, Acoustic emission during pitting corrosion of 304 stainless steel.
Corros. Sci. 53, 1537–1546 (2011)
4. C. Jirarungsatian, A. Prateepasen, Pitting and uniform corrosion source recognition using
acoustic emission parameters. Corros. Sci. 52, 187–197 (2010)
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AISI 316L austenitic stainless steel by acoustic emission technique: choice of representative
acoustic parameters. J. Mater. Sci. 36, 557–563 (2001)
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