神经网络在光电位置坐标传感器中的应用

光电位置敏感器件(PSD)是一种可直接对其光敏面上的光斑进行检测的光电器件,基于PSD可以构成多种非接触的高精度动态位移监测仪器.在PSD器件使用中的一个关键问题是如何克服器件本身的非线性,以提高监测的精度和可靠性.提出一种基于神经网络的PSD非线性补偿方法,利用神经网络具有逼近任意非线性函数的特点,通过训练使神经网络建立在PSD输出与其理想值之间的非线性映射关系,实现PSD非线性补偿.计算机仿真表明,该方法不仅能有效地消除非线性的影响,而且能在神经网络的输出端得到期望的线性输出.

Neural network application in position sensitive detector

The position sensitive detector(PSD) is an photo-electronic sensor which can detect the continuous position of a light spot traveling over its surface,and convert the position of light spot to simple electric current signal.Based upon PSD,many types of precision and contactless motion detection instruments could be constructed.The most important problem to use the PSD is how to overcome the influence of non-linear action on the PSD.Therefore to improve the precision and reliablity of the instrument.Based on artificial neural network,a non-linear compensation method of PSD is presented in this paper. In order to non-linear compensation over a full range, the neural network is trained to represent the non-linear mapping between sensor reading and their represent output accurately properly.It is revealed from the computer simulation result that not only the influence of non-linear fluctuation can be eliminated effectively, but also a desired linear relationship between the sensor input and the neural network output can be obtained.