Shanglei Li

Ultrasonic Defect Mapping Using Signal Correlation for Nondestructive Evaluation (NDE)

This article presents the application of a signal correlation technique to automatically classify ultrasonic A-scan signals for defect and defect-free regions in isotropic and anisotropic materials. First, feature extraction was implemented by generating a reference A-scan signal of a defect-free area using an autocorrelation function and statistics. Then, a cross-correlation function, utilized as a feature detector, was applied to the reference signal and a signal of interest (SOI) to detect defect-free features in an SOI. The correlation result was considered as a pattern containing both defect and defect-free features. Next, the pattern was classified by measuring the similarity between features of the reference signal and an SOI based on their Euclidean distance. Each A-scan signal classification result was then plotted on a 2D map based on its position on the specimen. The present work uses multiple correlation functions and statistics to classify defect signals rather than relying on an inspector’s prior knowledge to interpret C-scan data, and has particular value in automated ultrasonic signal classification and characterization.

Polynomial Fitting Techniques for IRT Inspection

This paper discusses the use of polynomial surface fitting techniques for the infrared thermography (IRT) evaluation of the graphite epoxy composite laminate. The composite laminate had 12 inserted Teflon films in different layers so as to simulate delamination defects. Based on the initial IRT inspection, it was determined that the raw IR images were not able to detect all 12 defects. In order to improve the detection capability and remove the heating pattern, a fitted heating pattern was generated by using the polynomial surface fitting method. Then, this pattern was deleted by applying the subtract function. It was demonstrated that this applied method not only removed the non-uniform heating effect, but also preserved all defect information and enhanced the thermal contrast of the raw IR images.

Super-Resolution in Ultrasonic NDE

This paper discusses the use of an iterative back projection (IBP) super-resolution (SR) image reconstruction technique on the carbon epoxy laminates with simulated porosity defects. In order to first validate and evaluate the application of the proposed method, three artificially simulated delamination defects in carbon epoxy laminates were considered. Based on the preliminary results, it was verified that the contrast signal-to-noise ratio (CNR) of the SR image was higher than the bi-cubic interpolation image. Further, the peak signal-to-noise ratio (PSNR) value of SR result had an average increase of 5.7088 dB compared to the bi-cubic interpolation method. This validates the proposed approach used to generate the reconstructed SR images with image quality similar to the original simulated UT images. After the validation, the UT image reconstruction algorithm was applied to the ultrasonic C-scan amplitude images of a porosity sample. Based on the results, it was demonstrated that the SR image achieved better visual quality with an improved image resolution. It was also demonstrated that this method was capable of detecting the defects with more confidence by recovering the defect outline compared to the LR C-scan image. The defect outline in SR images is more distinct to recognize, allowing post-processing work such as measurement of defect size, shape, and location to be much easier.