A scalable data-driven approach to temperature baseline reconstruction for guided wave structural health monitoring of anisotropic carbon-fibre-reinforced polymer structures

Abstract

To account for the temperature effect on guided wave signals in complex structures, a significant amount of baseline measurements typically need to be collected over a large temperature range to serve as a library of signals at all possible temperatures, which, if not impossible, is highly impractical. This article presents a data-driven temperature baseline reconstruction approach that is applicable for various structures made from the same material. The influence of temperature on the amplitude and phase of guided wave measurements are experimentally quantified as dimensionless compensation factors. The derived compensation factors are used to reconstruct baselines at various temperatures for guided wave measurements in a simple flat plate and a stiffened panel. With a single baseline measurement at 20°C and the reconstructed baseline using the predetermined temperature compensation factors, impact damage was successfully detected and located when current measurements were up to 25°C and 20°C higher than the baseline temperature, respectively.