Variational Wavelet Ensemble Empirical (VWEE) Denoising Method for Electromagnetic Ultrasonic Signal in High-Temperature Environment with Low-Voltage Excitation

Abstract

Low excitation voltage for an electromagnetic acoustic transducer (EMAT) is necessary for the petrochemical equipment and facilities inspection, which work at high-temperatures, to avoid potential explosion. However, low excitation voltage causes low signal-to-noise ratio (SNR) signals that are difficult to extract features, especially in a high-temperature environment, which causes high noise. In this study, a denoising method called the variational wavelet ensemble empirical (VWEE) method was proposed by combining the advantages of the variational modal decomposition (VMD), wavelet threshold (WT) denoising, and ensemble empirical mode decomposition (EEMD) methods. To validate the VWEE method, EMAT signals obtained in the temperature range of 25 to 700 °C were analyzed. The results show that, compared with VMD, WT and empirical mode decomposition denoising methods, the SNR of proposed method is improved more than two times. The VWEE method dramatically improved the SNR of a high-temperature EMAT signal and enhanced the accuracy of defect echos extraction.