Search

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.

This work proposes a novel technique for the localization of low-velocity impacts in composites without a-priori knowledge of the mechanical properties nor the speed of propagating waves, thus overcoming current limitations of existing impact localization methods. The proposed algorithm is based on the estimation of the power of acoustic emissions generated by impacts on a composite plate instrumented with embedded piezo-transducers. The signal power values calculated at sparse sensor locations are interpolated over the sample by using radial basis function networks. The impact coordinates on the specimen surface are estimated by a center-of-gravity method based on the interpolated power values. Experimental tests were performed by using both an instrumented impact hammer and a drop tower. The results obtained showed the validity of the presented approach, which was able to identify the impact locations with high level of accuracy.

Nowadays, smart composites based on different nano-scale carbon fillers, such as carbon nanotubes (CNTs), are increasingly being thought of as a more possible alternative solution to conventional smart materials, mainly for their improved electrical properties. Great attention is being given by the research community in designing highly sensitive strain sensors for more and more ambitious challenges: in such context, interest fields related to carbon nanotubes have seen extraordinary development in recent years. The authors aim to provide the most contemporary overview possible of carbon nanotube-based strain sensors for aeronautical application. A smart structure as a morphing wing needs an embedded sensing system in order to measure the actual deformation state as well as to “monitor” the structural conditions. Looking at more innovative health monitoring tools for the next generation of composite structures, a resin strain sensor has been realized. The epoxy resin was first analysed by means of a micro-tension test, estimating the electrical resistance variations as function of the load, in order to demonstrate the feasibility of the sensor. The epoxy dogbone specimen has been equipped with a standard strain gauge to quantify its strain sensitivity. The voltamperometric tests highlight a good linearity of the electrical resistance value as the load increases at least in the region of elastic deformation of the material. Such intrinsic piezoresistive performance is essentially attributable to the re-arrangement of conductive percolating network formed by MWCNT, induced by the deformation of the material due to the applied loads. The specimen has been prepared within this investigation, to demonstrate its performance for a future composite laminate typical of aerospace structures. The future carbon-fiber sensor can replace conventional metal foil strain gauges in aerospace applications. Furthermore, dynamic tests will be carried out to detect any non-reversible changes to the sensing response.