Quantification and mitigation of the effect of resynchronization errors in ultrasound sensor network for passive imaging in elastic plates.

The problem of signal desynchronization in passive imaging based on noise correlation for defect detection in elastic plates is investigated. Although a post-processing resynchronization process relying on the symmetry of noise correlation functions can be applied prior to the imaging algorithm, perfect synchronization might not be achieved experimentally. Effect of such residual synchronization errors on the defect detection performance is quantified as a function of their probability density function. A mathematical regularization process is then proposed to reduce the standard deviation of the resynchronization errors by a factor of N-1/N (N is the number of sensors), which results in a significant improvement in the detection performance. Finally, these theoretical results are validated through a simple flexural-wave propagation simulation.

Monitoring saltwater corrosion of steel using ultrasonic coda wave interferometry with temperature control.

Assessing corrosion is crucial in the petrochemical and marine industries. Usual ultrasonic methods based on pulse-echo and guided waves to detect corrosion lack of precision and struggle in structures with a complex shape. In this paper, a complementary and sensitive ultrasonic method based on coda wave interferometry is presented to detect and quantify thickness loss caused by saltwater corrosion of a steel sample. The method consists in exciting the sample and measuring periodically the scattered coda signal. Correlation of the coda signal with a reference taken for the sample initial state permits the monitoring of corrosion spread with a high accuracy. A laboratory experiment is conducted with two steel samples immersed in saltwater with coda and temperature measured simultaneously. One of the samples is protected from corrosion and is used as a control sample to determine the influence of temperature on the coda signals. It is shown that the coda signals on the corroded sample can be temperature-corrected using the temperature measurement only. A control sample is not needed. A good correlation is found between a parameter quantifying the stretching of the coda over time and the corrosion surface, which is monitored with a camera. Finally, a simple theoretical model of coda signal is proposed to quantify the real-time average corrosion rate during the experiment with a sub-micrometric precision. The estimated final average corrosion depth is validated by independent depth profile measurements. The uncertainties and sensitivity of the presented method are investigated.

Accuracy of Green's function estimation from correlation of diffuse elastic waves on thin plates.

In a reverberant cavity, when a noise field is sufficiently diffuse, the correlation of the signal measured by two sensors provides an estimation of the Green's function (GF) between them. Here, the convergence of this passive estimation in the case of elastic waves on thin plates is studied. A statistical approach is proposed, which relates the similarity between the cross correlation and the GF to the structural properties of the plate and the number of uncorrelated sources. The analysis is sustained by experimental results obtained on an aluminum plate. This study allows us to evaluate the efficiency of passive structural health monitoring of plate-like structures based on noise correlation. Finally, a most interesting finding shows an absolute upper bound of the signal-to-noise ratio for GF quality reconstruction: 4Ns/5, independently of the plate properties.

Reverberation of flexural waves scattered by a local heterogeneity in a plate.

A statistical model is proposed to relate the scattering properties of a local heterogeneity in a plate to the statistical properties of scattered and reverberated flexural waves. The contribution of the heterogeneity is isolated through the computation of differential signals consisting of a subtraction of the signals recorded after and before introduction of the heterogeneity. The theoretical expression of the average reverberation envelope of these differential signals is obtained as a function of the scattering cross-section of the heterogeneity. Successful numerical and experimental validations in various cases of canonical heterogeneities with known scattering cross-sections are shown. These satisfying results offer a way to estimate the scattering cross-section of an unknown scatterer from the reverberated differential signals.

Experimental study of passive defect localization in plates using ambient noise.

Passive listening methodology has been shown to be a practical and effective method for passive structural health monitoring. In this work, this approach is applied experimentally to monitor the occurrence of defects in thin aluminum plates. A correlation matrix is estimated from noise vibrations recorded on a transducer array. A defect is localized by applying a beamforming algorithm to the difference between the correlation matrices obtained with and without the defect. We successfully detect defects for different kinds of noise sources. Moreover, we show that this technique is robust to detect massive inclusions, holes, and cracks. With a vibrometer, we observe that the fidelity of the estimated transient responses strongly depends on the number of uncorrelated noise sources. Finally, we show that the defect is successfully localized even if the noise source distribution is not uniform, provided that it remains spatially stationary between the states with and without defect. A simple theoretical framework is proposed to interpret these results.