Elastic Wave Field Neural Networks for Structural Health Monitoring: An Analytical and Numerical Study of Multiple Neurons

Abstract

The purpose of this study is to develop a novel concept of smart structural systems recognizing their own structural integrity by an embodied high density sensor network. In our concept, a number of sensor nodes are embedded in the host structure, each of which reacts point-wise to the structural vibration with a simple rule. This allows the whole nodes to be mutually coupled through the elastic field, forming a neural network that incorporates the dynamic characteristics of the host structure as the coupling weights. In the previous study, we presented that a single-neuron network as its minimum configuration can exhibit a bifurcation of its dynamics behavior, which can be used to detect the change of the network due to damages. In this study, the formulation of networks with multiple neurons deployed in a structure with single-mode approximation is presented particularly focusing on the bi- furcation analysis to reveal how the behavior of the network is drastically altered depending of the network and structural parameters. Numerical analysis is conducted to examine the validity of the bifurcation analysis.