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自制了一套干湿环境交替、SO_2和H_2S混合气体浓度可调的模拟实验装置,采用室内加速腐蚀、电化学分析、微观表征等方法,研究了干湿交替环境中SO_2和H_2S混合气体对紫铜T2的腐蚀特性和规律,运用BP神经网络模型建立了紫铜T2的腐蚀速率预测模型,并对其可靠性进行了检验。结果表明,实验初期腐蚀速率增加较迅速,后期增加缓慢;腐蚀产物出现蚀坑且有裂痕,主要成分是Cu_2Cl(OH)_3,Cu_2S和Cu_4SO_4(OH)_6;所建立的模型预测结果误差小于10%,表明该模型具有良好的可靠预测性。
In this paper, a set of simulated experimental devices with alternating wet and dry environments and adjustable concentrations of SO 2 and H 2 S mixtures were fabricated by accelerated corrosion, electrochemical analysis and microscopic characterization. The effects of SO 2 and H 2 S mixed gases on copper T2 corrosion characteristics and laws, the use of BP neural network model to establish a copper T2 corrosion rate prediction model, and its reliability was tested. The results show that the corrosion rate increases rapidly at the beginning of the experiment and increases slowly in the late stage. The corrosion products appear pits and cracks, and the main components are Cu_2Cl (OH) _3, Cu_2S and Cu_4SO_4 (OH) _6. The prediction error of the model is less than 10 %, Indicating that the model has good reliability and predictability.