High-order spectra-based deconvolution of ultrasonic NDT signals for defect identification

In ultrasonic nondestructive testing (NDT) of materials, pulse-echo measurements are masked by the characteristics of the measuring instruments, the propagation paths taken by the ultrasonic pulses, and noise. This measured pulse-echo signal is modeled by the convolution of the defect impulse response and the measurement system response, added to noise. The deconvolution operation, therefore, seeks to undo the effect of the convolution and extract the defect impulse response which is essential for defect identification. In this contribution, we show that the defect ultrasonic model can be formulated in the higherorder-spectra (HOS) domain in which the processing is more suitable to unravel the effect of the measurement system and the additive Gaussian noise. In addition, a new technique is developed to faithfully recover the impulse response signal from its HOS. Synthesized ultrasonic signals as well as real signals obtained from artificial defects are used to show that the proposed technique is superior to conventional second-order statistics-based deconvolution techniques commonly used in NDT.