According to the problem of substrate recognition for coating materials, this paper proposes a technical approach to identify the under-coating materials based on the infrared time variation characteristics. Five specimens with the same coating and different kinds of substrates are designed; pulsed stimulation is applied on the surface of the specimens, and the infrared radiation variation is captured by an infrared camera. The thermal images sequences and temperature vs. time curve are processed, and the logarithmic temperature vs. time curve is analyzed; the deviation degree of the logarithmic curves from the -1/2 slope line (the theoretical logarithmic curve of single-layer material) is defined as the characteristic value of the logarithmic curves of different substrate materials. Therefore, different types of the substrate materials can be recognized. For practical application, a characteristic value database is needed, and this method can effectively identify subsurface materials with different thermodynamic parameters by comparing with the database.
Honeycomb sandwich Composite has wide applications in manufacture, such as aircraft, automobile, rail transit, and so on, due to its special advantages. However, defects always exist in the honeycomb composite during manufacturing and in-service period, liquid ingress and debondings are the most typical defects. In this paper, according to the NDT problem for this kind of material, Pulsed thermography is applied, theoretical model of heat conduction for the defect detection under an instantaneous heat source is analyzed; Several kinds of honeycomb composite specimen is designed for the two typical defects detection; Pulsed thermography is applied on the specimens and the defects are revealed by the thermal images sequence processing. Furthermore, by analyzing the logarithmic temperature decreasing curves can distinguish different types of liquids under the skin. Results show that Pulsed thermography has advantages for the NDT of honeycomb composite.
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