Quadrature Frequency Modulated Thermal Wave Imaging with Compressive Sensing Technology

Abstract

This chapter highlights the compressive Sensing in Quadrature Frequency Modulated Thermal Wave Imaging. Active infrared thermography is a widely used technique in the field of non-destructive.

testing. The subsurface defects produce non-uniform heat dissipation and this phenomenon is captured by an infrared camera. At a frequency much higher than the necessary nyquist rate, an IR camera records the thermal response from test material. This is a waste of resources like power, memory, and sensors. In this study, the thermal response from test samples of aluminium and bone is captured using compressed sensing (CS) at a lower frame rate, and the full response is then recovered using the CS recovery algorithms Basis Pursuit (BP) and Orthogonal Matching Pursuit (OMP).   The capturing rate is much larger than the nyquist rate as suggested by the thermal stimulus. This leads to wastage of resources and produces a sparse data. Compressive sensing (CS) is a new signal acquisition procedure in which a sparse signal is acquired with far fewer measurements than the dimension of the signal. Utilising a correlation-based pulse compression approach, the recovered thermal response is processed to carry out subsurface analysis and find any defects.  To verify the effectiveness of the recovery algorithms comparison is done between original and recovered data and the results are promising. It can be concluded that by applying CS in thermography there is huge scope for conserving sensors, power and memory.