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.calculating the cross-correlation of noise recorded at two locations on the surface. In 2001, Weaver et al. [4] validated that the impulse response of the structure between two receiving points can be extracted by using the cross-correlation of noise recorded at two receiving points in random noise fields. The retrieved signals were only different in magnitude from Green's function. From then on, due to the ability of retrieving deterministic signals (Green's function) from random signals, this method has been applied in many fields, such as electromagnetics [5], seismology [6,7], ocean acoustics [8], civil engineering [9], medicine [10], and ultrasonics [11]. In 2004, under the isotropic scattering assumption, Snieder et al. [12] deduced the feasibility of recovering Green's function of the ballistic wave from the coda. The global requirement of the equipartitioning of normal modes was held if the scattered waves propagated quasi-isotropically near the receivers. Subsequently, after considering the limitation of time-reversal invariance in correlating noise, he found that it was possible to obtain Green's function of diffusion by correlating the solutions of the diffusion equation that were excited randomly [13]. This property was used to retrieve Green's function for diffusive systems from ambient fluctuations. In 2011, Moulin et al. [14] tested ambient vibrations for passive real-time monitoring of structures by low-frequency random vibration data, which was collected on an all-aluminum naval vessel operating at high speed. In 2014, Roux et al. [15] evaluated the relative contributions of source distribution and medium complexity in the two-point cross-correlations, showing that the fit between the cross-correlation and the 2D Green's function strongly depended on the nature of th...
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.
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