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| Study of Corrosion Grade Assessment Method Based on Invariant Moment Theory |
| Received:July 17, 2011 |
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| DOI： |
| KeyWord:invariant moment probabilistic neural network corrosion grade |
| Author | Institution |
| SU Wei-guo |
Postgraduate Team，Qingdao Branch of Naval Aeronautical Engineering Academy，Qingdao，China |
| GUO Shao-chen |
Unit92367of PLA，Qingdao，China |
| ZHOU Ji-guang |
Naval Aviation Military Representative Office in Nanchang，Nanchang，China |
| SONG Qing |
Unit92286of PLA，Qingdao，China |
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| Abstract: |
| Digital image technique and theory of invariant moments were applied to the characteristic extraction of corrosion morphology based on corrosion images containing a large amount of corrosion information.7invariant moment characteristics of corrosion image were used to express corrosion morphology. The invariant moments were considered as characteristic parameters and inputs in the probabilistic neural network, and the grade of corrosion was evaluated as output. Accelerated corrosion test in EXCO (exfoliation corrosion) solution was taken as example. The results showed that as a highly concentrated image feature,invariant moment can represent the mapping relationship from corrosion feature to corrosion morphology. This method is simple and has a high recognition accuracy of87.95%, which can meet engineering requirements. |
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