No abstract

Structural health monitoring (SHM) using guided waves is one of the only ways in which damage anywhere in a structure can be detected using a sparse array of permanently attached sensors. To distinguish damage from structural features, some form of comparison with damage-free reference data is essential, and here subtraction is considered. The detectability of damage is determined by the amplitude of residual signals from structural features remaining after the subtraction of reference data. These are non-zero due to changing environmental conditions such as temperature. In this paper, the amplitude of the residual signals is quantified for different guided-wave SHM strategies. Comparisons are made between two methods of reference signal subtraction and between two candidate sensor configurations. These studies allow estimates to be made of the number of sensors required per unit area to reliably detect a prescribed type of damage. It is shown that the number required is prohibitively high, even in the presence of modest temperature fluctuations, hence some form of temperature compensation is absolutely essential for guided-wave SHM systems to be viable. A potential solution is examined and shown to provide an improvement in signal suppression of approximately 30 dB, which corresponds to two orders of magnitude reduction in the number of sensors required.

No abstract

This paper describes the formulation of a maximum-likelihood estimate of damage location for guided-wave structural health monitoring (GWSHM) using a minimally informed, Rayleigh-based statistical model of scattered wave measurements. Also introduced are two statistics-based methods for evaluating localization performance: the localization probability density function estimate and the localizer operating characteristic curve. Using an ensemble of measurements from an instrumented plate with stiffening stringers, the statistical performance of the so-called Rayleigh maximumlikelihood estimate (RMLE) is compared with that of seven previously reported localization methods. The RMLE proves superior in all test cases, and is particularly effective in localizing damage using very sparse arrays consisting of as few as three transducers. The probabilistic basis used for modelling the complicated wave scattering behaviour makes the algorithm especially suited for localizing damage in complicated structures, with the potential for improved performance with increasing structure complexity.

This letter reports on the application of the non-collinear mixing technique to the ultrasonic measurement of material nonlinearity to assess plasticity and fatigue damage. Non-collinear mixing is potentially more attractive for assessing material state than other nonlinear ultrasonic techniques because system nonlinearities can be both independently measured and largely eliminated. Here, measurements made on a sample after plastic deformation and on a sample subjected to low-cycle fatigue show that the non-collinear technique is indeed capable of measuring changes in both, and is therefore a viable inspection technique for these types of material degradation.