摘要
在复合电沉积工艺中,通过适当控制工艺条件可以获得具有特殊性能的纳米复合镀层。运用正交试验法优化对复合沉积层显微硬度有较大影响的各工艺参数,然后用BP神经网络分析方法对正交试验的结果进行分析处理。预测并得到较正交试验法所得最优工艺水平组合时更高的复合沉积层显微硬度,证实了将神经网络模型应用于复合沉积层性能预测和工艺优化的可行性和有效性。
In composite electrodeposition, nanocomposite deposites which possess excellent properties can be gained by controlling suitable technological conditions. The optimized process parameters that have major influence on hardness of composite deposite were obtained by orthogonal test, and the result was further analyzed by BP neural network. The micro-hardness of nanocomposite deposite was predicted and greater micro-hardness of nanocomposite deposite was gained. It is proved that the BP neural network technology is applicable for predicting the performance of composite deposites and optimizing technological parameters.
出处
《机械工程材料》
CAS
CSCD
北大核心
2004年第2期44-46,54,共4页
Materials For Mechanical Engineering
基金
国家自然科学基金资助项目(50075040)
关键词
复合电沉积
正交试验
BP神经网络
显微硬度
预测
composite electrodeposition
orthogonal test
BP neural network
micro-hardness
prediction
