Study on the orientation detection of surface cracks by electromagnetic acoustic emission

Abstract

Crack orientation plays a vital role in structural integrity analysis, which provides quantitative crack growth and structural failure information. Even though many structural health monitoring systems can detect crack location and length, only few methods are capable of detecting crack orientation. Recently, we have shown that an electromagnetically induced acoustic emission method can detect active defect with elastic waves. In this article, the ability of the electromagnetically induced acoustic emission method for finding the orientation of cracks is studied. Based on the freeelectron theory and electroplastic flow concept, the mechanism of electromagnetically induced acoustic emission effect will be explored at the microscopic level. By studying the energy exchange between the free electrons and the metallic dislocations, the total energy and the trajectory of drift electrons radiated during the electromagnetic loading can be evaluated theoretically. The Hilbert-Huang transform method is applied for extracting properties of the experimental electromagnetically induced acoustic emission signals. The results showed that the correlation coefficients between the original signals and the intrinsic mode function components, as well as the instantaneous frequency of the intrinsic mode function, depended on the crack orientations. Hence, experimental results and analysis confirm that the crack orientation can be monitored by the crack-induced intrinsic mode function extracted from the electromagnetically induced acoustic emission signals.

Defect detection of ferromagnetic rail using EMAE-based peak-to-peak method and confidence probability indicator

“…Meanwhile, the [10] and [16] discussed the effect of the maximum amplitude of excitation current on simulation results, and the range of maximum amplitude was set to [10 A, 110 A] and [10 A, 90 A], respectively. Similarly, it was set to [10 A, 110 A] in this paper.…”

“…Jin et al introduced the effect of an external magnetic field generated by an Nd-Fe-B magnet on the EMAE, and analyzed the deformation of specimen when the exciting coil was located at different positions in 2010 [15]. According to the free-electron theory and electroplastic effect concept, Cai in 2019 studied the ability of the EMAE method to determine the orientation of defects and explored the mechanism of the EMAE effect at the microscopic level [16]. Furthermore, fast Fourier transform and wavelet packet transform were utilized by Zhang et al to process EMAE signals to complete defect detection in aluminum specimens [17].…”

Influence of the PZT Sensor Array Configuration on Lamb Wave Tomography Imaging with the RAPID Algorithm for Hole and Crack Detection

“…Fortunately, the predicted location can be used to determine the crack orientation, as discussed in the following. The angular scattering patterns of the Lamb wave mode of cracks under different incident wave directions are well detailed in [23][24][25][26][27][28], which mostly focus on the transmission and reflection coefficients. This paper focuses on the SDC for tomography images.…”

“…Holes are the simplest type of scattering features in engineering structures, and their effects on Lamb waves have been extensively studied [22]. Cracks are another common type of scattering feature, but the angular scattering behavior of the Lamb wave manifests significant directionality depending on the angle of the incident wave relative to the crack orientation, which is more complicated than the scattering behavior of a hole [23][24][25][26][27][28]. Such a directionally scattered field poses great difficulty for crack orientation identification, especially for the asymmetric distribution under oblique wave incidence.…”

Research on finite element analysis and signal denoising based on electromagnetic acoustic emission

“…Currently, the feasibility of electromagnetic acoustic emission was demonstrated by finite element analysis [6] . The signal processing methods of electromagnetic acoustic emission based on fast Fourier transform (FFT), wavelet packet transform [7] and Hilbert-Yellow transform [8] was used. The denoising method based on wavelet packet threshold method [9] had obvious denoising effect.…”