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.

Composite materials are being widely used for manufacturing aircraft components due to their superior material properties such as high strength, light weight, corrosion resistance, etc. However, compared to isotropic materials, composite materials exhibit complex damage characteristics. Moreover, when the composite material is impacted by a foreign object they are prone to barely visible impact damages such as delamination, matrix cracking, etc. Since composite materials are being increasingly used in aircraft component production the likelihood of composite damage occurrence during aircraft operation increases as well. Therefore, it is crucial to address the challenges associated with detecting composite damage and performing composite repairs. The focus of this research is the development of automated depot repair technology for composite structures, which combines; non-destructive testing (NDT) for damage size determination, damage removal by milling, repair by adhesive bonding of a repair patch and NDT for post repair assessment. In this study, a damaged curved CFRP panel with dimensions of 1.3 × 1.3 m was used for the development of algorithms for automated composite repair process. NDT using a laser line scanner was performed to acquire the composite panel’s surface data, to assess features of the panel such as its shape, visible damage, etc., and the thermographic inspection was done to assess the extent and location of internal damage. Algorithms were developed to perform data fusion of the sensor data; a) to detect, localize, quantify and visualize the damage on the composite panel, through analysis of gradient changes between defined local sections of the panel, b) to generate a 3D model of the repair region based on the surface geometry and with design considerations that ensures the optimal structural integrity of the repaired panel, and c) to output suitable computer-aided design (CAD) files which can be imported to the milling tool, to perform the damage removal, and the CAD tool, to fabricate the repair patch. Finally, after the composite panel undergoes the milling and repair process, NDT inspections will be performed to ensure its safety and integrity.