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| Protective Performance of Coating Based on Self-organizing Neural Network and Support Vector Machine |
| Received:February 01, 2018 Revised:May 25, 2018 |
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| DOI：10.7643/ issn.1672-9242.2018.05.013 |
| KeyWord:organic coating Self-organizing neural network support vector machine |
| Author | Institution |
| XU An-tao |
a.Delivery Equipment Support Department, Army Military Transportation University, Tianjin , China |
| LI Xi-dong |
b.Postgraduate Training Brigade, Company Five, Army Military Transportation University, Tianjin , China |
| ZHOU Hui |
b.Postgraduate Training Brigade, Company Five, Army Military Transportation University, Tianjin , China |
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| Abstract: |
| Objective To avoid possible problems of EIS and EN, and establish an accurate and efficient evaluation model to evaluate the performance of active military organic coatings. Methods Through the analysis on corrosion behaviors of two organic coating of military vehicle in the cyclic exposure test, the impedance in low frequency region and the noise resistance Rn, were extracted with EIS and EN. These two electrochemical evaluation parameters were extracted as input training samples of self-organizing neural network (SOM). At the same time, combined with support vector machine (SVM) method, the coating protection performance classifier was established. Results The failure processes of coating were divided into three stages spontaneously: protective properties being good, being reduced and failure. Conclusion The SOM-SVM combined classifier is feasible for assistant analysis on protective performance of coating |
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