Composite materials are susceptible to barely visible impact damages (BVID) due to low-velocity impact. Therefore, an automated damage detection and quantification technique is highly desirable for quick inspection of large number of composite structures. Among various different non-destructive techniques (NDTs), active thermography NDT can be used for detecting damage on aircraft structures, using an infrared camera to capture the temperature distribution on the structure after it is exposed to heat using a flash lamp. In this paper, an image analysis algorithm that analyzes the infrared image, acquired using NDTherm NT, by determining the changes in the colormap values to automate the detection and quantification of the damage size was proposed. An area of the second derivative pre-processed grayscale image acquired using NDTherm NT is scanned in the x-direction and y-direction, and for each scan region the histogram of colormap values is extracted and stored. Irregularities in the structure result in non-uniform temperature distributions, which cause the infrared image to have a wide-range of grayscale colormap values in the damaged area. Therefore, the damage region is identified by monitoring the changes in the number of detected grayscale colormap values. The proposed image analysis technique was implemented for automated damage detection on Boeing 787 skin's curved CFRP panel, with dimensions of 1.3 × 1.3 m. The proposed method detected the damage and determined the maximum damage length in the x-direction and y-direction to be 70.1 mm and 57.8 mm, respectively. Moreover, the proposed technique is suitable for feature identification applications.

In this study, silicon carbide fiber was proposed as a sensor for detection and localization of low-velocity impacts on composite structures. Semi-conductive silicon carbide fibers have excellent piezoresistivity and good mechanical properties, so their potential as a sensor for low-velocity impact detection and localization was investigated by attaching it on the surface of a composite panel. By measuring the resistance change of the silicon carbide fiber sensor due to low-velocity impacts on the composite material, impacts signals were obtained, and the resistance changes of the silicon carbide fiber sensor were acquired by conversion to voltage using a Wheatstone bridge circuit. The impact signals acquired using the silicon carbide fiber sensors were investigated to analyze the repeatability for impacts at the same location point and impact distinguishability at different points. Finally, impact localization based on a reference database using the silicon carbide fiber sensors attached to the composite panel was performed, and a total of 20 impacts were localized with an average error of 16.2 mm and a maximum error of 39.5 mm for a test section with planar dimensions of 200 mm × 200 mm.