Empirical mode decomposition based techniques for imaging of shallow delamination in concrete using impact echo

Abstract

An impact echo (IE) signal comprises different frequency components as a result of interaction between stress waves and targets. Empirical mode decomposition (and its improved techniques), an adaptive and fully data-driven technique have been used to separate different components of an IE signal into what is known as intrinsic mode functions (IMF). The applications of improved versions of EMD and their advantages over other new adaptive decomposition techniques have also been demonstrated. This separation of modes differentiates constituent signals such as surface wave, echo wave, and flexural wave into corresponding IMFs and thus allows reconstruction of a new signal using only desirable components. An image reconstruction strategy for the selection of appropriate IMFs based on correlation coefficient is found to produce an improved image of the delamination or flaws compared to the raw signal images. The IE signal processed with noise-assisted EMD based techniques profoundly increased the accuracy of flaw features over the raw data. This improvement is validated with a quantification approach using amplitude histogram and binary mapping of flaws in B-scan and C-scan respectively. The study demonstrated that the flexural mode of vibration produced due to shallow delamination can be used for accurate imaging of flaws provided a suitable signal processing technique is used. The technique employed in this study can also be extended for imaging of deep delamination which is exhibited by echo waves in IE signals.