摘要 : This paper describes an experimental method for the estimation of transducer non linearity, its testing and calibration using artificial neural networks. Attempts have been made to devise an important submodule of an autocalibrati... 展开 This paper describes an experimental method for the estimation of transducer non linearity, its testing and calibration using artificial neural networks. Attempts have been made to devise an important submodule of an autocalibration system, working in a real time environment for interpolating the static response characteristics of different types of sensors and transducers. Object oriented, fourth generation, high performance graphical programming language (Test point) is used to implement the user interactive versatile virtual calibrator. Experimental results of the comparative study in modelling the static response characteristics of a hydrostatic strain gauge pressure transducer using adaptive linear network (ADALINE), multi layered feed forward back propagation (MLFFBP) network and radial basis function (RBF) network are presented. 收起