scholarly journals Wavenumber Imaging of Near-Surface Defects in Rails using Green’s Function Reconstruction of Ultrasonic Diffuse Fields

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3744 ◽  
Author(s):  
Hui Zhang ◽  
Haiyan Zhang ◽  
Jiayan Zhang ◽  
Jianquan Liu ◽  
Wenfa Zhu ◽  
...  

Wavenumber imaging with Green’s function reconstruction of ultrasonic diffuse fields is used to realize fast imaging of near-surface defects in rails. Ultrasonic phased array has been widely used in industries because of its high sensitivity and strong flexibility. However, the directly measured signal is always complicated by noise caused by physical limitations of the acquisition system. To overcome this problem, the cross-correlations of the diffuse field signals captured by the probe are performed to reconstruct the Green’s function. These reconstructed signals can restore the early time information from the noise. Experiments were conducted on rails with near-surface defects. The results confirm the effectiveness of the cross-correlation method to reconstruct the Green’s function for the detection of near-surface defects. Different kinds of ultrasonic phased array probes were applied to collect experimental data on the surface of the rails. The Green’s function recovery is related to the number of phased array elements and the excitation frequency. In addition, the duration and starting time of the time-windowed diffuse signals were explored in order to achieve high-quality defect images.

2020 ◽  
Vol 62 (4) ◽  
pp. 216-221
Author(s):  
Haiyan Zhang ◽  
Mintao Shao ◽  
Guopeng Fan ◽  
Hui Zhang ◽  
Wenfa Zhu

A method combining Green's function retrieval theory and sign coherence factor (SCF) imaging is presented to detect near-surface defects in rails. The defects are close to the ultrasonic phased array and near-surface acoustic information of defects is obscured by the non-linear effects of the initial wave signal in directly acquired responses. To overcome this problem, cross-correlations of the diffuse field signals captured by the array transducer are performed to reconstruct the Green's function. SCF imaging is used to further improve the spatial resolution and signal-to-noise ratio (SNR) of near-surface defects in rails. Experiments are conducted on two rails containing two and four defects, respectively. The results show that these defects can be clearly identified when using the reconstructed Green's function. However, the images of near-surface defects are masked and cannot be distinguished when using directly captured signals and total focus imaging. The proposed method reduces the background noise and allows for effective imaging of near-surface defects in rails.


Metals ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 868
Author(s):  
Haiyan Zhang ◽  
Mintao Shao ◽  
Guopeng Fan ◽  
Hui Zhang ◽  
Wenfa Zhu ◽  
...  

In this paper, phase coherence imaging is proposed to improve spatial resolution and signal-to-noise ratio (SNR) of near-surface defects in rails using cross-correlation of ultrasonic diffuse fields. The direct signals acquired by the phased array are often obscured by nonlinear effects. Thus, the output image processed by conventional post-processing algorithms, like total focus method (TFM), has a blind zone close to the array. To overcome this problem, the diffuse fields, which contain spatial phase correlations, are applied to recover Green’s function. In addition, with the purpose of improving image quality, the Green’s function is further weighted by a special coherent factor, sign coherence factor (SCF), for grating and side lobes suppression. Experiments are conducted on two rails and data acquisition is completed by a commercial 32-element phased array. The quantitative performance comparison of TFM and SCF images is implemented in terms of the array performance indicator (API) and SNR. The results show that the API of SCF is significantly lower than that of TFM. As for SNR, SCF achieved a better SNR than that of TFM. The study in this paper provides an experimental reference for detecting near-surface defects in the rails.


Naturally generated ambient noise in the ocean is created by breaking waves, spray and precipitation. Each of these mechanisms produces a pulse of sound that propagates down into the depths of the ocean, and the superposition of all such pulses from across the whole sea surface constitutes the ambient noise field. Since the noise is a stochastic phenomenon, its properties are described in terms of statistical quantities, the most useful being the power spectral density at a point and the cross-spectral density between two points in the field. If these second-order statistical measures are independent of absolute position, the noise field is said to be spatially homogeneous. In the rare case of an isovelocity, deep ocean, the noise field at depths greater than a wavelength or so beneath the surface is spatially homogeneous, consisting of a random superposition of plane waves. A non-uniform sound speed profile, however, introduces wave-front curvature which modifies the situation significantly. the noise exhibits strong spatial homogeneity over length scales that are comparable with the apertures of typical acoustic arrays. Apart from the implications with regard to array performance, this is important in connection with certain aspects of acoustical oceanography, whereby information on the oceanographic environment is extracted from the noise field (Buckingham et al. 1992). Such information is accessible only if the structure of the noise field is well understood. The problem lies in determining the spatial and spectral properties of the noise in a profile. Fundamental to the noise analysis is the Green’s function for the channel, which characterizes the propagation conditions; and yet for most non-uniform sound speed profiles the analysis of the Green's function is intractable. However, there is one profile, designated the inverse-square profile, for which a complete, exact solution for the field has been developed (Buckingham 1991). The inverse-square profile is monotonic increasing with depth, giving rise to upward refractive propagation. Such a profile is found in several ocean environments: the polar oceans, where the temperature and hence the sound speed show a minimum at the surface; the mixed surface layer, extending to a depth of order 100 m in the open ocean; and the ocean-surface bubble layer, occupying the first ten metres or so beneath the surface. An analysis of the noise field in the presence of an inverse square profile, based on the solution for the Green’s function, shows that the cross-spectral density of the noise in the vertical consists of three components: a normal mode sum, representing noise originating largely in distant sources; a direct path contribution, from sources that are more or less overhead; and a near-surface term that is negligible at depths greater than a wavelength. In the theoretical noise spectrum , the normal mode and direct path components are prominent, dominating, respectively, at low and high frequencies. The cross-over frequency depends on the parameters of the profile and attenuation in the medium, but for polar oceans is in the region of several hundred hertz. At a much lower frequency, around 10 Hz, where the polar profile ceases to support normal mode propagation, a minimum appears in the theoretical spectrum . This is the result of a very rapid fall off in the normal mode component of the noise and a slow rise of the direct path component with decreasing frequency. Each of the three components of the vertical cross-spectral density exhibits strong spatial inhomogeneity. This is exemplified by the dramatic dependence of the cross-spectrum on both the mean depth of the sensors and frequency. Although such behaviour adds complexity to the structure of the noise field, this could be advantageous since it allows the possibility of performing inversions on noise cross-spectral data to determine properties of the medium. Recent measurements of low-frequency (50-2000 Hz) and very low-frequency (5-200 Hz) ambient noise spectra in the marginal ice zone of the Greenland Sea, where the sound speed profile is of the inverse-square form, have been compared with the predictions of the new noise theory. There is evidence in the measured spectra that both the normal mode and direct path components of the noise are present with the predicted relative levels. A minimum around 10 Hz is a ubiquitous feature of the VLF spectra, and the LF spectra show a change of slope close to 400 Hz, both of which are in accord with the theory. Along the ice edge a highly non-uniform (spatial) distribution of energetic sources is known to be present, whose effects in the observed spectra are consistent with arguments developed from the inverse-square noise analysis.


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