<title>Avoiding the need for baseline data: an information-theoretic approach to detecting damage-induced nonlinearities in structures</title>

Abstract

An information-theoretic approach is described for detecting damage-induced nonlinearities in structures. Both the time-delayed mutual information and time-delayed transfer entropy are presented as methods for computing the amount of information transported between points on a structure. By comparing these measures to linearized surrogate data sets, the presence and degree of nonlinearity in a system may be deduced. For a linear, five-degree-of-freedom system both mutual information and transfer entropy are derived. An algorithm is then described for computing both quantities from time-series data and is shown to be in agreement with theory. The approach successfully deduces the amount of damage to the structure even in the presence of simulated temperature fluctuations. We then demonstrate the approach to be effective in detecting varying levels of impact damage in a thick composite plate structure.