中文摘要：

电子铝箔腐蚀发孔时影响铝箔扩面效果的因素很多，各因素之间存在交互作用。建立基于遗传算法优化的BP神经网络预测模型，分析盐酸、硫酸浓度和配比等因素对铝箔发孔的作用机理。结果表明：盐酸与硫酸存在交互作用，在特定配比下，蚀孔的引发与抑制达到平衡，铝箔腐蚀扩面后实际比表面积最大。通过SEM分析验证，所建立的GA-BP神经网络模型能有效分析盐酸、硫酸等对铝箔发孔质量的影响，为整体优化铝箔腐蚀工艺奠定理论基础。

英文摘要：

When pitting corrosion occurs, the extending surface of aluminum foil was influenced by many factors, among which exists interaction. A prediction model of BP neural network based on genetic algorithm was built to analyze the impaction of many factors on the pitting corrosion, which includes hydrochloric acid concentration, sulfuric acid concentration and different ratios. The results show that there is interaction between hydrochloric acid and sulfuric acid. In certain proportion, the balance of pitting initiation and inhibition can be achieved during the corrosion, and the max realistic area of etched aluminum foil was researched. By the analysis of SEM, the influence of hydrochloric acid and sulfuric acid on pitting corrosion of aluminum foil can be effectively analyzed by using the forecast model of GA-BP neural network. This work is beneficial for the optimization of aluminum foil etching process.