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| Analysis of Electrochemical Noise by Hilbert-Huang Transform and Its Application |
| SHI Wei, DONG Zehua, GUO Xingpeng |
| School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China |
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Abstract Time-frequency transition plays a key role in the pattern identification of electrochemical noise (EN) signal. In this paper, we studied the EN of carbon steel in simulated concrete pore solution by Hilbert-Huang transform (HHT), and found that, in comparison with discrete wavelet transform (DWT), HHT exhibited much higher resolution and stability at time-frequency domain for the identification of EN transients. Moreover, HHT can improve the resolving accuracy of metastable pit signals coupled in EN. According to the EN characteristics of carbon steel at different corrosion status, such as passive, metastable, and stably growing pits, we proposed a pitting factor (PF) as an index for identification and quantification of localized corrosion type based on HHT algorithm, aiming at the diagnosis of corrosion type and severity of industrial installation by online EN monitoring instrument.
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Received: 15 May 2013
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