Title :
Neural networks applied to continuous range amplitude measurements of small sinusoidal vibrations [using Michelson interferometer]
Author :
Cimponeriu, Andrei
Author_Institution :
Dept. of Meas. & Opt. Electron., Polytech.. Univ. of Timisoara, Romania
Abstract :
A novel method for computing the amplitude of small sinusoidal vibrations measured with the Michelson interferometer is proposed. The method is a particular case of nonlinear adaptive inverse modeling, using neural networks. The feasibility of the method is proved by simulation, and the noise behavior is examined. The results are of practical interest: they show that the method is applicable to practical, noisy signals and the precision can be very good
Keywords :
Bessel functions; Michelson interferometers; adaptive filters; backpropagation; feedforward neural nets; filtering theory; inverse problems; light interferometry; mean square error methods; measurement by laser beam; modelling; nonlinear filters; signal sampling; vibration measurement; Bessel functions; Michelson interferometer; backpropagation; continuous range amplitude measurements; filtering; high precision; mean square error; neural networks; noise behavior; nonlinear adaptive inverse modeling; simulation; small sinusoidal vibrations; Computational modeling; Computer networks; Equations; Frequency measurement; Inverse problems; Lighting; Mirrors; Neural networks; Particle measurements; Vibration measurement;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1999. IMTC/99. Proceedings of the 16th IEEE
Conference_Location :
Venice
Print_ISBN :
0-7803-5276-9
DOI :
10.1109/IMTC.1999.776023
