Abstract
This paper presents a likelihood-based time-of-flight method for localizing sequential acoustic sources in composite structures within a single structural health monitoring (SHM) acquisition. The proposed approach exploits signal arrival time information measured by a sensor network to construct a global likelihood map obtained by aggregating the individual contributions associated with successive emission events. Source locations are estimated by identifying the maxima of this global likelihood map, which correspond to the most probable source positions in a relative sense. To enhance localization accuracy and robustness, a nonlinear weighting operation is applied to the likelihood map to sharpen the spatial distribution, followed by morphological filtering to remove spurious peaks and a quadratic regression step to refine the estimation of the maximum positions. The method is experimentally validated on a carbon–epoxy composite plate using pencil lead break tests to simulate acoustic emission (AE) sources. Experimental results demonstrate that the proposed approach accurately localizes successive-AE events while maintaining a simple and computationally efficient formulation suitable for practical SHM applications. A key contribution of this work lies in its ability to localize multiple sequential acoustic events within a single SHM acquisition without requiring independent processing of each event.
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