Abstract
The detection of flaw echoes in backscattered signals in ultrasonic nondestructive testing can be challenging due to the existence of backscattering noise and electronic noise. In this article, an empirical mode decomposition (EMD) methodology is proposed for flaw echo enhancement. The backscattered signal was first decomposed into several intrinsic mode functions (IMFs) using EMD or ensemble EMD (EEMD). The sample entropies (SampEn) of all IMFs were used to select the relevant modes. Otsu’s method was used for interval thresholding of the first relevant mode, and a window was used to separate the flaw echoes in the relevant modes. The flaw echo was reconstructed by adding the residue and the separated flaw echoes. The established methodology was successfully employed for simulated signal and experimental signal processing. For the simulated signals, an improvement of 9.42 dB in the signal-to-noise ratio (SNR) and an improvement of 0.0099 in the modified correlation coefficient (MCC) were achieved. For experimental signals obtained from two cracks at different depths, the flaw echoes were also significantly enhanced.
Highlights
The ultrasonic technique has been widely used in nondestructive testing
0.0526 modes are determined by the sample entropies (SampEn) of all IMFs0.036 or their 0.0276 differences, and the mixed noise is suppressed by separating the flaw echo from those relevant modes by windowing
The relevant modes are determined by the SampEn of all intrinsic mode functions (IMFs) or their differences, and the mixed noise is suppressed by separating the flaw echo from those relevant modes by windowing
Summary
The ultrasonic technique has been widely used in nondestructive testing. Usually, the backscattered signal is complex due to the existence of electronic noise and backscattering noise.flaw echo detection may be challenging. Numerous methods have been proposed to enhance flaw echoes, such as split spectrum processing [1,2,3,4], wavelet transforms [5,6,7,8,9,10], the Stockwell transform [11,12,13,14], and empirical mode decomposition (EMD) [15,16,17,18,19,20,21,22] Split spectrum processing has significant advantages in processing ultrasonic signals with scattered noise. Split-spectrum analysis separates the spectrum of the signals to obtain several sub-bands, and uses some nonlinear de-noising criteria (such as thresholding method, etc.) to process the signals in each sub-band to achieve the purpose of de-noising. The difficulty of split spectrum processing is how to determine the filter type, central frequency, bandwidth and other parameters
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