摘要
在纳米复合电沉积工艺中,通过优选工艺参数可以获得纳米颗粒复合量较高的复合沉积层,以使其具有某些优越的性能。笔者首先运用正交实验法优选了对复合沉积层中纳米颗粒复合量有较大影响的工艺参数,诸如镀液中ZrO2颗粒悬浮量、阴极电流密度和镀液温度等,然后用BP神经网络分析方法对其结果进行分析处理。预测并得到纳米颗粒复合量更高的复合沉积层,观察了纳米复合沉积层的表面形貌,并对其中纳米颗粒分布的均匀性进行了分析。
In the nano-composite electrodeposition, higher nanoparticle content in nanocomposite coatings is a- chieved by optimizing the process parameters, so that these composite coatings have excellent properties. In this pa- per, the optimized process parameters that have major influence on nanopartiele content were obtained by orthogonal test, such as the ZrO： concentration in electrolyte, the current density and the temperature of the electrolyte. The result was further analyzed by back-propagation（BP） neural network. Nanoparticle content in nanocomposite coat- ings was predicted and the composite coating which has the highest nanopartiele content was gained. The surface morphology of the nanocomposite coating was surveyed and the spread of distribution of nanoparticles in the nanocomposite coating was analyzed.
出处
《机械科学与技术》
CSCD
北大核心
2011年第3期386-389,共4页
Mechanical Science and Technology for Aerospace Engineering
基金
江苏省高校自然科学重大基础研究项目(09KJA460001)
陕西省特种加工重点实验室项目资助
关键词
纳米复合电沉积
工艺参数
正交实验
BP神经网络
复合量
nano-composite electrodeposition
technology parameter
orthogonal test
BP neural network
nanop- article content
