高电压技术2017，Vol.43Issue(5)：1453-1459,7.DOI:10.13336/j.1003-6520.hve.20170428009
碳纤维复合材料雷电损伤预测
Lightning Damage Prediction of Carbon Fiber Composite Materials
摘要
Abstract
Compared with traditional metal materials,carbon fiber composite materials are more sensitive to lightning,and the damage caused by lighting is even more serious.So,carbon fiber composite materials must be tested to meet the specific requirements of lightning protection design.The experiments were carried out by referring to the relevant standards.Firstly,the prediction model of lightning damage was established based on the damage data,which could be obtained by ultrasonic testing.Then,the influences of lightning environment parameters on the properties of carbon fibercomposite material were analyzed based on the model,and the corresponding damage characteristic curve was obtained.Finally,the breakdown characteristics of carbon fiber composite materials under two kinds of lightning protection mode,which were flame spraying aluminum protective mode and laying aluminum mesh surface protective mode,were analyzed through the model comparison.The results show that the depth of damage is affected by the action integral and charge quantity,and the maximum damage depth increases monotonically with the increase of the action integral and the charge quantity.When the volume of charge quantity remains unchanged at 150 C,the breakdown threshold of the action integral of the former model is about 1.801 × 106 A2s,which is larger than that of the latter one,1.0× 106 A2s.When the action integral remains unchanged at 1.5× 106 A2s,the breakdown threshold of the charge quantity of the former model is about 289.87 C,which is larger than that of the latter one,97.50 C.So it is revealed that the protective effect of the former model is better than the latter.关键词
复合材料/雷电流/损伤模型/无损探伤/参数优化/击穿阈值Key words
composite materials/lightning current/damage prediction/ultrasonic testing/parameter optimization/breakdown threshold引用本文复制引用
司晓亮,李志宝,刘辉平,仇善良,段泽民..碳纤维复合材料雷电损伤预测[J].高电压技术,2017,43(5):1453-1459,7.基金项目
预研基金(9140A33010314HK85466).Project supported by Advanced Research Funds(9140A33010314HK85466). （9140A33010314HK85466）
