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| Content Provider | Directory of Open Access Journals (DOAJ) |
|---|---|
| Author | Junlei Tang Junyang Li Hu Wang Yingying Wang Geng Chen |
| Abstract | The acoustic emission (AE) technique was applied to monitor the pitting corrosion of carbon steel in $NaHCO_{3}$ + NaCl solutions. The open circuit potential (OCP) measurement and corrosion morphology in-situ capturing using an optical microscope were conducted during AE monitoring. The corrosion micromorphology was characterized with a scanning electron microscope (SEM). The propagation behavior and AE features of natural pitting on carbon steel were investigated. After completion of the signal processing, including pre-treatment, shape preserving interpolation, and denoising, for raw AE waveforms, three types of AE signals were classified in the correlation diagrams of the new waveform parameters. Finally, a 2D pattern recognition method was established to calculate the similarity of different continuous AE graphics, which is quite effective to distinguish the localized corrosion from uniform corrosion. |
| e-ISSN | 20763417 |
| DOI | 10.3390/app9040706 |
| Journal | Applied Sciences |
| Issue Number | 4 |
| Volume Number | 9 |
| Language | English |
| Publisher | MDPI AG |
| Publisher Date | 2019-02-01 |
| Publisher Place | Switzerland |
| Access Restriction | Open |
| Subject Keyword | Technology Engineering (general). Civil Engineering (general) Biology (general) Physics Chemistry Carbon Steel Pitting Corrosion Acoustic Emission Wavelets Pattern Recognition |
| Content Type | Text |
| Resource Type | Article |
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