Evaluation of the sparse reconstruction and the delay-and-sum damage imaging methods for structural health monitoring under different environmental and operational conditions. (February 2021) - Nokhbatolfoghahai, A.; Navazi, H.M; Groves, R.M.
Highlights: The performance of Delay-And-Sum and Sparse Reconstruction are investigated in SHM. Taguchi and Analysis of Variance methods are used for the performance study. The robustness of the DAS is better than the SR for uncontrolled factors. The SR method is more robust to poor baseline subtraction than the DAS method. The DAS method was more robust to factors that lead to a model mismatch. Abstract: In this paper, the performance of the sparse reconstruction (SR) and the delay-and-sun (DAS) methods for damage localization, were evaluated for various environmental and operational conditions, both numerically and experimentally. To assess these damage localization methods, a methodology based on the Taguchi method was used to make the experimental design, and a modified performance-index was defined to represent the quality of reconstructed images. Then, the robustness and the accuracy of each method, in a well-defined performance region relevant to in-service aerospace structures, were investigated using the Taguchi and analysis of variance methods. It was concluded that for the defined conditions, the robustness of the delay and sum method is better than the sparse reconstruction method for uncontrolled factors. However, the sparse reconstruction method is more robust to poor baseline subtraction than the delay and sum method, while the delay and sum method was more robust to factors that lead to a model mismatch. These results provide additional insight into the design of reliable accurate structural health monitoring systems. The outcomes of this work can be used in future reaserch into SHM imaging techniques.