An effective crack-identification approach for impact echo signals using MWT spectrograms and scaled FFT spectra

When performing an impact-echo (IE) test to detect internal cracks in concrete structures, the fast Fourier transform (FFT) of the measured surface responses is used to extract frequency peaks of major periodic events and obtain crack depth information. However, reflections from reinforcing bars located at approximately one-half the crack depth may result in comparable frequencies. It is then difficult to determine whether a certain peak frequency is associated with a crack or a bar based solely on the FFT frequency. Our research group suggested using the Morlet wavelet transform (MWT) to facilitate distinguishing between crack responses and bar responses. It was found that the proposed idea is feasible for identifying relatively large cracks. This paper extends the applicability of the previous study by incorporating two analytical models into the methodology: an attenuation model for describing the decrement trend of the amplitude histograms extracted from the MWT spectrograms; and a method for normalizing and scaling the frequency amplitudes. Thus, an enhanced scheme for identifying cracks and bars has been developed, in which the evaluation procedures consist of a quick diagnosis stage for large cracks and a confirmation stage for bars. Through numerical studies and experimental measurements, this study demonstrates the logic in how to validate the two-stage procedures with appropriate benchmark values. Hence, this paper provides the analysts with an effective scheme to distinguish between bar and crack echoes in IE signals.