论文标题
人工神经网络的应用来确定薄膜的厚度
Application of artificial neural network to determine the thickness profile of thin film
论文作者
论文摘要
在本文中，我们引入了一种新型的人工神经网络（ANN）方案，以估计沉积在给定底物上的薄膜的厚度。在这里，我们考虑了平面波和与薄膜表面反射的发散波之间的可见干扰模式，该薄膜表面记录了薄膜的厚度信息。我们假设膜的厚度均匀度。但是，随着沉积的发生，厚度会增加。我们通过干扰模式的中心提取强度数据。我们通过使用许多已知厚度概况的线信息来训练我们的网络。然后，通过估计未知表面的厚度来测试受过训练的网络的性能。数值模拟结果表明，所提出的技术对于迅速，实时的自动测量非常有用
In this paper, we introduce a novel artificial neural network (ANN) based scheme to estimate the thickness of thin films deposited on a given substrate. Here we consider the visible interference pattern between a plane wave and a diverging wave reflected from the thin film surface that records the thickness information of the thin film. We assume a uniform thickness profile of the film. However, the thickness increases as the deposition takes place. We extract the intensity data along a line through the center of the interference pattern. We train our network by using a number of such line information of known thickness profiles. The performance of the trained network is then tested by estimating the thickness of unknown surfaces. The numerical simulation results show that the proposed technique can be very much useful for automated measurement of thickness, quickly and in real time, during deposition
