Optimization of the Inspection of Large Composite Materials Using Robotized Line Scan Thermography

The emergence of composite materials has started a revolution in the aerospace industry. When using composite materials, it is possible to design larger and lighter components. However, due to their anisotropy, composite materials are usually difficult to inspect and detecting internal defects is a challenge. Line scan thermography (LST) is a dynamic thermography technique, which is used to inspect large components of metallic surfaces and composites, commonly used in the aerospace industry. In this paper, the robotized LST technique has been investigated on a large composite component which contains different types of internal defects located at a variety of depths. For theoretical analysis, the LST inspection was simulated using a mathematical formulation based on the 3D heat conduction equation in the transient regime in order to determine the optimum parameters. The solution of the model was performed using the finite element method. The LST parameters were adjusted to detect the deepest defects in the specimen. In order to validate the numerical results with experimental data, a robotized system in which the infrared camera and the heating source move in tandem, has been employed. From the experimental tests, it was noted that there are three sources of noise (non-uniform heating, unsynchronized frame rate with scanning speed and robot arm vibration) which affect the performance of the test. In this work, image processing techniques that were initially developed to be applied on pulse thermography have been successfully implemented. Finally, the performance of each technique was evaluated using the probability of detection approach.