Smooth Nonnegative Matrix Factorization for Defect Detection Using Microwave Nondestructive Testing and Evaluation

This paper addresses the interpolation issue of current spectral estimation methods in microwave-based nondestructive testing and evaluation. We developed a spatial-frequency feature extraction algorithm for defect detection with an open-ended waveguide system using smooth Itakura-Saito nonnegative matrix factorization. In addition, the mathematical models of spatial-frequency characteristics for both defects and nondefects areas are derived. The newly developed algorithm has two prominent characteristics, which benefit the detection system. First, it is scale-invariant in the sense that spatial-frequency features that are characterized by large dynamic range of energy can be extracted more efficiently. Second, it imposes smoothness constraint on the solution to enhance the spatial resolution of defect detection. To evaluate the proposed technique, we demonstrate the efficacy of the proposed method by performing extensive experiments on four samples: four defects in an aluminum plate with different depths, a steel plate with 15-mm coating thickness, one tiny defect on steel and one natural defect. Experimental results have unanimously demonstrated the capabilities of the proposed technique in accurately detecting defects, especially for shallow and coated samples with high resolution.