Prediction of the plasma distribution using an artificial neural network

• 来源期刊: 中国物理B（英文版）
• 关键词: artificial neural network ECR-PECVD plasma distribution
• 年，卷（期）: 2009,（6）
• 页码范围: 2441-2444
• 页数: 4页
• 语种: 英文

摘要

In this work, an artificial neural network (ANN) model is established using a back-propagation training algorithm in order to predict the plasma spatial distribution in an electron cyclotron resonance (ECR) - plasma-enhanced chemical vapor deposition (PECVD) plasma system. In our model, there are three layers: the input layer, the hidden layer and the output layer. The input layer is composed of five neurons: the radial position, the axial position, the gas pressure,the microwave power and the magnet coil current. The output layer is our target output neuron: the plasma density.The accuracy of our prediction is tested with the experimental data obtained by a Langmuir probe, and ANN results show a good agreement with the experimental data. It is concluded that ANN is a useful tool in dealing with some nonlinear problems of the plasma spatial distribution.