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The active thermal nondestructive testing and evaluation method is a rapidly growing testing procedure for a quick and remote inspection procedure for fibre-reinforced plastics. Conventional modulated lockin thermography significantly contributed to this field by allowing usage of low peak power controlled stimulations followed by phase based detail extraction procedures. But demand of repetitive experimentation required for depth scanning of the test object limits its applicability for realistic critical applications and demands multi-frequency low power stimulations for better resolution and sensitivity for subsurface defect detection. Frequency modulated thermal wave imaging and coded excitation thermal wave imaging methods permitting multi-frequency stimulations cater for these needs and facilitate depth scanning of the test object in a single experimentation cycle. Recently introduced three-dimensional pulse compression is an alternative to phase based analysis for these stimulations by providing enhanced defect detection even in noisy environmental and experimental conditions. Defect detection capability and sizing by these nonstationary thermal wave imaging methods are highlighted using the pulse compression approach. The present experimental study has been carried out on a carbon fibre reinforced plastic specimen with flat bottom holes.

Infrared thermography (IRT) is one of the promising remote and whole field inspection techniques for nondestructive characterization of various solids. This technique relies on the mapping of surface temperature response to detect the presence of surface and subsurface anomalies within the material. Due to its fast and quantitative testing capabilities, the IRT has gained significant importance in the testing of fiber reinforced polymers (FRP). A carbon FRP sample with flat bottom holes is considered for inspection using nonstationary digitized frequency modulated thermal wave imaging technique. Furthermore, depth scanning performance using frequency domain-based phase approach has been compared with recently proposed time domain phase approach.

This paper proposes a novel signal processing approach to thermal non-destructive testing by incorporating Gaussian window function onto the linear frequency modulated incident heat flux to achieve better pulse compression properties. The present work highlights a finite element analysis based modeling and simulation technique in order to test the capabilities of the proposed windowing scheme over the conventional frequency modulated thermal wave imaging method. It is shown that by using Gaussian weighted chirp thermal stimulus, high depth resolution can be achieved.

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Modelling of the frequency modulated thermal wave imaging process through the finite element method for non-destructive testing of a mild steel sample Frequency modulated thermal wave imaging involves mapping of the thermal response over the test sample for a given incident frequency modulated heat flux within a suitable band of frequencies that are launched into the sample from its surface. This contribution describes finite element analysis-based modelling for the characterisation of a mild steel sample with defects of different shapes using frequency modulated thermal wave imaging. The present work highlights the comparative results obtained from frequency and time domain phase analysis schemes adopted on the mean-removed generated temporal thermal data.

Among various widely used InfraRed Thermal NonDestructive Testing (IRTNDT) modalities, Non-Stationary Thermal Wave Imaging (NSTWI) techniques have proved to be an indispensable approach for the inspection and evaluation of various materials. Growing concern for the development of surface and subsurface defect detection techniques with moderate peak power heat sources (than the widely used conventional pulse based thermographic methods) and in a reasonably less testing time (compared to sinusoidal modulated lock-in thermography), makes these NSTWI techniques invaluable for this field. The present work highlights a comparative study on various NSTWI techniques, further experimental results are presented to find their defect detection capabilities by taking signal to noise ratio (SNR) into consideration.

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