Fiber Bragg gratings are known being immune to electromagnetic interference and emerging as Lamb wave sensors for structural health monitoring of plate-like structures. However, their application for damage localization in large areas has been limited by their direction-dependent sensor factor. This article addresses such a challenge and presents a robust damage localization method for fiber Bragg grating Lamb wave sensing through the implementation of adaptive phased array algorithms. A compact linear fiber Bragg grating phased array is configured by uniformly distributing the fiber Bragg grating sensors along a straight line and axially in parallel to each other. The Lamb wave imaging is then performed by phased array algorithms without weighting factors (conventional delay-and-sum) and with adaptive weighting factors (minimum variance). The properties of both imaging algorithms, as well as the effects of fiber Bragg grating’s direction-dependent sensor factor, are characterized, analyzed, and compared in details. The results show that this compact fiber Bragg grating array can precisely locate damage in plates, while the comparisons show that the minimum variance method has a better imaging resolution than that of the delay-and-sum method and is barely affected by fiber Bragg grating’s direction-dependent sensor factor. Laboratory tests are also performed with a four–fiber Bragg grating array to detect simulated defects at different directions. Both delay-and-sum and minimum variance methods can successfully locate defects at different positions, and their results are consistent with analytical predictions.
Modified minimum variance imaging of Lamb waves for damage localization in aluminum plates and composite laminates