高分辨网栅型Au-Si表面势垒探测器的制备和性能

制备了对紫外光灵敏且有较高能量分辨的网栅型Au-Si表面势垒探测器,其有效面积为12.56cm^2,金网栅电极厚195×10^(-10)m。对^(241)Am 5.486 MeV α粒子在室温和低真空条件下能量分辨是55-80 keV。探讨了制备工艺并测试了性能。

Parameters optimization and nonlinearity analysis of grating eddy current displacement sensor using neural network and genetic algorithm

A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The parameters optimization of the sensor is essential for economic and efficient production.This paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.