To predict the service life of protective coatings of aircrafts and ships, improved degradation kinetics model and neural network model were put forward on the basis of the existing degradation kinetics model. AF1410 as the base material was shot peened, zinc sprayed, primer sprayed, and enamel spayed. Then comprehensive accelerated tests were carried out with the specimens after surface treatment in the external environment of Sanya( ultraviolet, thermal shock, low temperature fatigue and salt spray) . Electrochemical impedance spectroscopy is used to measure electrochemical impedance modulus of the composite coatings on the base material of AF1410 during the degradation process. Based on these data, three kinds of prediction models were tested. The results show that improved degradation kinetics model and neural network model have obviously higher prediction accuracy than traditional degradation kinetics, and the predictions by the neural network model make greater progress.%为预测舰船航空飞行器防护涂层的服役寿命,在现有的老化动力学预测模型基础上,提出了改进的老化动力学模型与神经网络模型两种新的预测模型。对基材为AF1410,表面处理依次为喷丸、喷锌、喷底漆、喷磁漆的试样,进行三亚外部环境(紫外、热冲击、低温疲劳、盐雾)的综合加速试验,采用电化学阻抗谱技术测得了试样涂层腐蚀老化过程中的阻抗模值数据,并利用试验数据针对3种预测模型进行测试。测试结果表明,改进的老化动力学神经网络模型预测精度较传统老化动力学模型明显提高,且神经网络模型预测精度提高程度更明显。
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