Kalman-based estimation of loading conditions from ultrasonic guided wave measurements

Abstract Ultrasonic guided wave-based structural health monitoring (SHM) of structures can be perturbed by environmental and operations conditions (EOCs) that alter wave propagation. In this work, we present an estimation procedure to reconstruct an EOC-free baseline of the structure from the only available Ultrasonic guided wave measurements. This procedure could typically be used as a prior step to increase the robustness of a more general ultrasonic imaging algorithm or SHM process dedicated to flaw detection. Our approach is model-based, i.e. we use a precise modeling of the wave propagation altered by structure loading conditions. This model is coupled with the acquired data through a data assimilation procedure to estimate the deformation caused by the unknown loading conditions. From a methodological point of view, our approach is original since we have proposed an iterated reduced-order unscented Kalman strategy, which we justify as an alternative to a Levenberg–Marquardt strategy for minimizing the non quadratic least-squares estimation criteria. Therefore, from a data assimilation perspective, we provide a quasi-sequential strategy that can valuably replace more classical variational approaches. Indeed, our resulting algorithm proves to be computationally very effective, allowing us to successfully apply our strategy to realistic 3D industrial SHM configurations.