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| Research on Influence on Fatigue Life Attenuation Based Corrosion Damage Characterization Factors |
| Received:February 26, 2011 Revised:August 15, 2011 |
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| DOI： |
| KeyWord:cumulative corrosion fatigue life model MIT LMS cumulative fatigue life attenuation rate neural network |
| Author | Institution |
| XING Wei |
Qingdao Branch of Naval Aeronautical Engineering Academy，Qingdao ，China |
| MU Zhi-tao |
Qingdao Branch of Naval Aeronautical Engineering Academy，Qingdao ，China |
| ZHOU Li-jian |
Qingdao Branch of Naval Aeronautical Engineering Academy，Qingdao ，China |
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| Abstract: |
| Corrosion damage characterization factors of LY12CZ aluminum alloy were filtrated using MIT（Mean Impact Value）method. Five corrosion damage characterization factors were obtained, which has significant influence on fatigue life attenuation. The functions of cumulative corrosion fatigue life and cumulative fatigue life attenuation rate were defined. The cumulative corrosion fatigue life model was established and its accuracy was verified. Corrosion damage characterization factors and the cumulative fatigue life attenuation function were taken as specimen. The fatigue lives of LY12CZ aluminum alloy of different service time were predicted with BP neural network and LMS algorithm. The results were than compared with experimentation results. It was proved that the error generated by BP neural network and LMS algorithm can be accepted in engineering. |
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