Sensor calibration using artificial neural networks

Abstract

Summary form only given, as follows. The calibration of a 2-D displacement sensor that suffers from nonlinearities and crosstalking using an artificial neural network (ANN) is described. The ANN is used as a pattern associator that is trained to perform the mapping between the sensor's readings and the actual sensed properties. For comparison purposes a few methods were explored: a three-layer ANN, with a different number of hidden units, trained by the backpropagation method; a cerebellar model arithmetic computer with a fixed number of quantizing functions; and a polynomial curve fitting technique. The results of the calibration procedure and recommendation are discussed.<>