机场环境下飞机LY12CZ结构腐蚀损伤预测方法研究

摘要

依据LY1 2CZ材料的EXCO溶液浸泡加速腐蚀试验数据、飞机LY 12CZ构件在机场环境下的真实腐蚀损伤数据以及腐蚀损伤等效原则和当量关系原理,获得了该材料在2种环境下腐蚀的当量因子均值(α) =0.023 6,构建了LY12CZ材料于EXCO溶液中浸泡腐蚀的神经网络腐蚀深度预测模型.在此基础上提出了利用所建的神经网络模型和所获的当量因子进行机场环境下飞机用LY12CZ材料腐蚀损伤预测研究方法.预测结果表明该方法有效、可行.%Accelerated corrosion test of LY12CZ aluminum alloy was carried out in EXCO solution and the corrosion depth of the alloy was measured. Further more corrosion damage of aircraft LY12CZ structure with different service periods in true airport environment was counted. Based on the corrosion damage data of the two different environments and the corrosion damage equivalent relation, the equivalent relation factor between the EXCO solution and true airport environment was found. Then the neural network model based on EXCO solution test data with the BP algorithm was established. The corrosion damage of aircraft LY12CZ structure in the true airport environment was forecasted with the built model and the equivalent relation factor was found to be 0.023 6 under the two environments. The prediction results showed that the forecasting method is effective and applicable for LY12CZ corrosion damage estimation.