Radio frequency non-destructive testing and evaluation of defects under insulation

PhD ThesisThe use of insulation such as paint coatings has grown rapidly over the past decades. However, defects and corrosion under insulation (CUI) still present challenges for current non-destructive testing and evaluation (NDT&E) techniques. One of such challenges is the large lift-off introduced by thick insulation layer. Inaccessibility due to insulation leads corrosion and defects to be undetected, which can lead to catastrophic failure. Furthermore, lift-off effects due to the insulation layers reduce the sensitivities. The limitations of existing NDT&E techniques heighten the need for novel approaches to the characterisation of corrosion and defects under insulation. This research project is conducted in collaboration with International Paint®, and a radio frequency non-destructive evaluation for monitoring structural condition is proposed. High frequency (HF) passive RFID in conjunction with microwave NDT is proposed for monitoring and imaging under insulation. The small-size, battery-free and cost-efficient nature of RFID makes it attractive for long-term condition monitoring. To overcome the limitations of RFID-based sensing system such as effective monitoring area and lift-off tolerance, microwave NDT is proposed for the imaging of larger areas under thick insulation layers. Experimental studies are carried out in conjunction with specially designed mild steel sample sets to demonstrate the detection capabilities of the proposed systems. The contributions of this research can be summarised as follows. Corrosion detection using HF passive RFID-based sensing and microwave NDT is demonstrated in experimental feasibility studies considering variance in surface roughness, conductivity and permeability. The lift-off effects introduced by insulation layers are reduced by applying feature extraction with principal component analysis and non-negative matrix factorisation. The problem of thick insulation layers is overcome by employing a linear sweep frequency with PCA to improve the sensitivity and resolution of microwave NDT-based imaging. Finally, the merits of microwave NDT are identified for imaging defects under thick insulation in a realistic test scenario. In conclusion, HF passive RFID can be adapted for long term corrosion monitoring of steel under insulation, but sensing area and lift-off tolerance are limited. In contrast, the microwave NDT&E has shown greater potential and capability for monitoring corrosion and defects under insulation

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