Automatic sintonization of SOM neural network using evolutionary algorithms: An application in the SHM problem

Abstract

This paper is a contribution to the Structural Health Monitoring problem, solved by using case based reasoning and Self Organizing Maps. The expert system described in this paper is able to detect, locate and quantify stiffness percentage changes in a mechanical engineering structure. In order to overcome issues relating large number of parameters involved in the training stage it was applyed differential evolutive algorithms. Proper indexes to evaluate the training quality were proposed in order to increase diagnosis reliability. The algorithms were tested using the UBC ASCE Benchmark. The numerical implementation shows decreasing in the identification errors with respect to those obtained by selecting manually network training parameters. © 2014 Springer International Publishing Switzerland.