RT Generic
T1 Evaluation of artificial neural network method applied to probe diagnostics in plasma
A1 Villegas Prados, David
AB Plasma diagnostics consist on predicting the plasma parameter by measuring their properties.Models to predict these parameters are based on theoretical equations, which sometimes arecomplicated and tedious to solve. This thesis aims to evaluate a new method to obtain theseplasma parameters using a branch of artificial intelligence, the Artificial Neural Network.To develop this thesis, the software MATLAB was used to create the neural network. Two theorieswere tested: Planar Langmuir Probe and Orbital Motion Limited. And two problems were solved:forward problem to obtain the properties from the parameters and the inverse problem to obtainthe parameters from the properties. The later approach is used to evaluate the parameters obtainedby network with experimental data from laboratory measurements.Artificial Neural Network was implemented successfully in both forward and inverse problemswith incredible accuracy. The results obtained have created a theoretical framework for plasmadiagnostic using neural networks and it has been concluded that they can work with any theorypresented, as long as as proper database is obtained. Regarding the simulation with experimentaldata, the results were not good respect the measurements taken. Although the network performedwell, the database used for training and simulation had discrepancies from realistic data since it wasobtained from equations. Sources of error of this last problem are found and different approachesand work to be developed in the future are proposed.
YR 2018
FD 2018-07
LK https://hdl.handle.net/10016/29092
UL https://hdl.handle.net/10016/29092
LA eng
DS e-Archivo
RD 19 may. 2024