SiC-CVD过程的人工神经网络建模

ＳｉＣ－ＣＶＤ过 本质复杂性制约 了碳／碳复合材料表面有效地制备高性能抗氧化涂层。本研究在对ＣＶＤ工艺过程及机理试验研究的基础上，采用人工神经网络技术对ＳｉＣ－ＣＶＤ过程进行了辨识与模拟研究，建立了ＳｉＣ－ＣＶＤ过程的神经网络的模型。

NEURAL NETWORK MODELING METHOD FOR SILICON CARBIDE CHEMICAL VAPOR DEPOSITION PROCESS

A neural network (NN) model of the gas_phase and chemical kinetics in a silicon carbide chemical vapor deposition (CVD) process were developed. The model, which was learned from the experiment using 21 parameters within 7 experimental factors and adjusted the network structure automatically, can predict the SiC-CVD results correctly under any given experimental condition in a vertical reactor. It can also be used in the determination of the affections among different parameters and in the analysis of changes happened in CVD process as the deposition continues. A good agreement is founded between the model predicted results and experimental results, the predicted results also indicate that gas_phase mass conservation kinetic process may be very important in SiC-CVD process.