【摘要】 针对现阶段我国在飞机结构腐蚀监控方面手段落后、效率低的现状,开发基于线性极化法的能够实时监测飞机铝合金结构腐蚀速率的微型传感器,并设计加速腐蚀试验对该传感器的有效性进行了验证。同时,开展基于人工神经网络的铝合金结构腐蚀速率预测研究。结果表明,线性极化腐蚀传感器所测腐蚀深度与铝合金试样实测值随腐蚀时间变化趋势相同,其能够有效地对飞机结构腐蚀状况进行实时监测;构建的网络模型在不同环境下预测的腐蚀速率平均误差不到8%,能够有效实现对铝合金结构瞬时腐蚀速率的预测。更多还原

【Abstract】 In order to fix the weakness of domestic aircraft structural corrosion monitoring, the micro-sized linear polarization resistance sensor was developed to monitor the corrosion rates of aluminum alloy structures in real time.Accelerated corrosion experiments were carried out to verify the feasibility of the developed sensors. The results indicated that the corrosion depth measured by sensors had the same trend as that of aluminum alloy samples with time, which showed the sensors can monitor the corrosion rates of aircraft structures in real time effectively.Meanwhile, the prediction model for corrosion rates of aluminum alloys was established based on BP neural network.The established network model can predict the corrosion rates of aluminum alloy structures in different environments with the average error less than 8%.更多还原