论文部分内容阅读
依据LY12CZ材料的EXCO溶液浸泡加速腐蚀试验数据、飞机LY12CZ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。
Based on the accelerated corrosion test data of EXCO solution of LY12CZ material, the real corrosion damage data of aircraft LY12CZ under airport environment and the principle of equivalence and equivalence of corrosion damage, the average equivalent factor α = 0.023 6. The corrosion prediction model for the corrosion of LY12CZ material in EXCO solution was constructed. Based on this, a method of predicting corrosion damage of aircraft LY12CZ material under airport environment is put forward based on the proposed neural network model and the equivalent factor obtained. The prediction results show that the method is effective and feasible.