Application of Wavelet and EEMD Joint Denoising in Nonlinear Ultrasonic Testing of Concrete

Abstract

e health state of concrete is deteriorating during its service. Nonlinear ultrasonic detection based on the amplitude of the fundamental and the second harmonic is considered to be a powerful tool for the discovery of the microcrack in concrete. However, the research on processing the nonlinear ultrasonic signal is still insufficient. In order to highlight the real frequency domain components in the nonlinear ultrasonic signal, wavelet and ensemble empirical mode decomposition (EEMD) were joined to denoise the numerical and measured signal. e optimal wavelet base and the decomposition level were determined by the signal-to-noise ratios (SNRs). en, the wavelet threshold denoising signal was decomposed by EEMD, omitting the highfrequency components and ultimately achieving the desired denoising effect. e denoising result of the test signals demonstrates that this method is effective in denoising the details of the ultrasonic signal and improving the reliability and adaptability of the nonlinear ultrasonic testing. In this experiment, the concrete with the microcrack was tested by linear and nonlinear ultrasonic methods. Based on the variation regularity of the nonlinear ultrasonic coefficient β and velocity v, we can conclude that the nonlinear ultrasonic parameter β is more sensitive to the microcrack in concrete than the traditional wave velocity v. e nonlinear ultrasonic testing can be an important supplement to the current nondestructive testing technique of the concrete.

Reconstructing echoes completely submerged in background noise by a stacked denoising autoencoder method for low-power EMAT testing

“…The settings of main factors, including the sequence length, code element length, and pair number of magnets would affect the interval and SNR of echoes. Some popular signal processing methods were used to process ultrasonic signals, such as the integration of ensemble empirical mode decomposition and wavelet transform (WT) [11], fractal denoising [12], fractional differential method [13]. Dragomiretskiy and Zosso [14] proposed the variational mode decomposition (VMD) to decompose the raw signal as some band-limited intrinsic mode functions.…”

Water quality prediction in sea cucumber farming based on a GRU neural network optimized by an improved whale optimization algorithm

“…VMD has advantages in processing nonstationary signals and suppressing noise.The above decomposition and denoising methods have good denoising effects, but they also have some shortcomings. In recent years, an increasing number of studies have shown that hybrid denoising methods have better performance than single denoising algorithms ( Cao et al, 2021 ; Nie, Wang & Zhao, 2018 ; Fu et al, 2020 ). To effectively decompose and denoise sea cucumber aquaculture water quality data, this article applied a hybrid algorithm combining variational mode decomposition (VMD) and wavelet threshold denoising (WTD) to realize the denoising processing of water quality data.…”

Characterization of Contact‐Type Defects in Mortar Using a Nonlinear Ultrasonic Method

“…us, it is difficult to distinguish the material nonlinearity from the obtained nonlinearity in experiment. In general, the numerical method can be considered as an effective method for the nonlinear ultrasonic study [35][36][37][38][39]. By finite element simulations, the motion of interface obeys the contact laws, and the nonlinear effects of ultrasonic waves can be obtained.…”