Date Available
12-7-2011
Year of Publication
2005
Document Type
Thesis
College
Engineering
Department
Electrical Engineering
First Advisor
YuMing Zhang
Abstract
The need and desire to create robust and accurate joining of materials has been one of up most importance throughout the course of history. Many forms have often been employed, but none exhibit the strength or durability as the weld. This study endeavors to explore some of the aspects of welding, more specifically relating to the Double Sided Arc Welding process and how best to model the dynamic non-linear response of such a system. Concepts of the Volterra series, NARMAX approximation and neural networks are explored. Fundamental methods of the neural network, including radial basis functions, and Back-propagation are investigated.
Recommended Citation
Fugate, Earl L., "NONLINEAR SYSTEM MODELING UTILIZING NEURAL NETWORKS: AN APPLICATION TO THE DOUBLE SIDED ARC WELDING PROCESS" (2005). University of Kentucky Master's Theses. 259.
https://uknowledge.uky.edu/gradschool_theses/259
