BP NEURAL NETWORKS MODEL FOR ATMOSPHERE CORROSION FORECAST OF LY12 ALUMINUM ALLOYS

摘要：

BP neural networks model is built and trained with accelerated corrosion data of LY12 aluminum alloys for atmosphere corrosion forecast. Temperature, humidity, Cl-, SO2 sedimentation and time are designed as the networks input, while corrosion weight gain and maximum corrosion depth as the networks output. Practical application showed the model has good accuracy for corrosion forecast of LY12 aluminum alloys served in oceanic atmosphere.

作者: HAN Desheng LI Di

作者单位: School of Physics and Mechanical & Electrical Engineering, Xiamen University, Xiamen 361005 School of Material Science and Engineering, Beijing University of Aeronautics and Astronautics, Beij

会议类型: 国际会议

会议名称: 第九届工程结构完整性国际会议(The Ninth International Conference on Engineering Structural Integrity Assessment)

会议地点: 北京

会议语种:英文

在线出版日期: 2007-10-15（万方平台首次上网日期，不代表论文的发表时间）