Alisson Figueiredo

Carbon fiber composites inspection and defect characterization using active infrared thermography: numerical simulations and experimental results

Composite materials are widely used in the aeronautic industry. One of the reasons is because they have strength and stiffness comparable to metals, with the added advantage of significant weight reduction. Infrared thermography (IT) is a safe nondestructive testing technique that has a fast inspection rate. In active IT, an external heat source is used to stimulate the material being inspected in order to generate a thermal contrast between the feature of interest and the background. In this paper, carbon-fiber-reinforced polymers are inspected using IT. More specifically, carbon/PEEK (polyether ether ketone) laminates with square Kapton inserts of different sizes and at different depths are tested with three different IT techniques: pulsed thermography, vibrothermography, and line scan thermography. The finite element method is used to simulate the pulsed thermography experiment. Numerical results displayed a very good agreement with experimental results.

Machine Learning and Infrared Thermography for Fiber Orientation Assessment on Randomly-Oriented Strands Parts

The use of fiber reinforced materials such as randomly-oriented strands has grown in recent years, especially for manufacturing of aerospace composite structures. This growth is mainly due to their advantageous properties: they are lighter and more resistant to corrosion when compared to metals and are more easily shaped than continuous fiber composites. The resistance and stiffness of these materials are directly related to their fiber orientation. Thus, efficient approaches to assess their fiber orientation are in demand. In this paper, a non-destructive evaluation method is applied to assess the fiber orientation on laminates reinforced with randomly-oriented strands. More specifically, a method called pulsed thermal ellipsometry combined with an artificial neural network, a machine learning technique, is used in order to estimate the fiber orientation on the surface of inspected parts. Results showed that the method can be potentially used to inspect large areas with good accuracy and speed.

Thermographic Computational Analyses of a 3D Model of a Scanned Breast

Breast cancer is the most common type of cancer among women. Cancer cells are characterized by having a higher metabolic activity and superior vascularization when compared to healthy cells. The internal heat generated by tumors travels to the skin surface where an infrared camera is capable of detecting small temperatures variations on the dermal surface. Breast cancer diagnosis using only thermal images is still not accepted by the medical community which makes necessary another exam to confirm the disease. This work presents a methodology which allows identification of breast cancer using only simulated thermal images. Experiments are performed in a three-dimensional breast geometry obtained with a 3D digital scanning. The procedure starts with the 3D scanning of a model of a real female breast using a “Picza LPX-600RE 3D Laser Scanner” to generate the breast virtual geometry. This virtual 3D model is then used to simulate the heat transfer phenomena using Finite Element Model (FEM). The simulated thermal images of the breast surface are obtained via the FEM model. Based on the temperature difference of a healthy breast and a breast with cancer it is possible to identify the presence of a tumor by analyzing the biggest thermal amplitudes. Results obtained with the FEM model indicate that it is possible to identify breast cancer using only infrared images.