Sensor calibration methods: performance study

Oren Masory; Arturo Luis Aguirre

doi:10.1117/12.21200

1 August 1990 Sensor calibration methods: performance study

Oren Masory, Arturo Luis Aguirre

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21200
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

The calibration of a 2-D displacement sensor that suffers from nonlinearities and cross talking using an Artificial Neural Networks (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: 1 ) A three-layer ANN with a different number of hidden units trained by the Back Propagation (BP) method 2) Cerebellar Model Arithmetic Computer (CMAC) with a fixed number of quantizing functions and 3) Polynomial curve fitting technique. The results of the calibration procedure and recommendations are discussed. 2.

Citation Download Citation

Oren Masory and Arturo Luis Aguirre "Sensor calibration methods: performance study", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21200

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