Alain Le Duff

Study of stress-induced velocity variation in concrete under direct tensile force and monitoring of the damage level by using thermally-compensated Coda Wave Interferometry

In this paper, we describe an experimental study of concrete behavior under a uniaxial tensile load by use of the thermally-compensated Coda Wave Interferometry (CWI) analysis. Under laboratory conditions, uniaxial tensile load cycles are imposed on a cylindrical concrete specimen, with continuous ultrasonic measurements being recorded within the scope of bias control protocols. A thermally-compensated CWI analysis of multiple scattering waves is performed in order to evaluate the stress-induced velocity variation. Concrete behavior under a tensile load can then be studied, along with CWI results from both its elastic performance (acoustoelasticity) and plastic performance (microcracking corresponding to the Kaiser effect). This work program includes a creep test with a sustained, high tensile load; the acoustoelastic coefficients are estimated before and after conducting the creep test and then used to demonstrate the effect of creep load.

Validation of a thermal bias control technique for Coda Wave Interferometry (CWI)

The Coda Wave Interferometry (CWI) analysis serves to monitor the variation of propagation velocity in a heterogeneous medium with high precision (10(-3)% in relative terms). In combination with acoustoelastic theory, this type of analysis offers an NDT method for stress evaluation and/or damage detection. Since the CWI method is intended to evaluate extreme levels of accuracy, the presence of bias under certain circumstances can undermine evaluation results and/or test repeatability. In this paper, we offer a bias control technique involving the use of a second (reference) specimen for CWI analysis that is designed to compensate: (1) the thermally-induced velocity variation due to environmental temperature fluctuations; and (2) bias originating from experimental procedures. The presentation of this technique contains both a theoretical analysis and experimental protocol for the purpose of implementation. Furthermore, comparisons of experimental results have been included in order to demonstrate the utility of this bias control technique under laboratory conditions.

Nonlinear coda wave interferometry for the global evaluation of damage levels in complex solids

HIGHLIGHTSNonlinear modulation method is combined with CWI for global damage assessment.Propagation mediums elastic nonlinear level is evaluated effectively and globally.Damage degree of Pyrex samples are related to their effective nonlinear level.Influences from temperature change to the method are discussed. ABSTRACT A nonlinear acoustic method to assess the damage level of a complex medium is discussed herein. Thanks to the highly nonlinear elastic signatures of cracks or, more generally, internal solid contacts, this method is able to distinguish between contributions from linear wave scattering by a heterogeneity and contributions from nonlinear scattering by a crack or unbounded interface. The coda wave interferometry (CWI) technique is applied to reverberated and scattered waves in glass plate samples featuring various levels of damage. The ultrasonic coda signals are recorded in both the absence and presence of an independent and lower‐frequency elastic “pump” wave, before being analyzed by CWI. The monitored CWI parameters quantifying changes in these coda signals, which therefore quantify the nonlinear wave‐mixing effects between the coda and pump waves, are found to be dependent on the damage level in the sample. A parametric study is also performed to analyze the influence of sensor positions and average temperature on the methods output. The reported results could be applied to the non‐destructive testing and evaluation of complex‐shape materials and multiple scattering samples, for which conventional ultrasonic methods show strong limitations.

A model-based approach for statistical assessment of detection and localization performance of guided wave–based imaging techniques:

This article aims at providing a framework for assessing the detection and localization performance of guided wave–based structural health monitoring imaging systems. The assessment exploits a damage identification metric providing a diagnostic of the structure from an image of the scatterers generated by the system, allowing detection, localization, and size estimation of the damage. Statistical probability of detection and probability of localization curves are produced based on values of the damage identification metric for several damage sizes and positions. Instead of relying on arduous measurements on a significant number of structures instrumented in the same way, a model-based approach is considered in this article for estimating probability of detection and probability of localization curves numerically. This approach is first illustrated in a simplistic model, which allows characterizing the robustness of the structural health monitoring system for various levels of noise in test signals. An experimental test case using a more realistic case with an artificial damage is then considered for validating the approach. A good agreement between experimental and numerical values of the damage identification metric and derived probability of detection and probability of localization curves is observed.

In situ characterization technique to increase robustness of imaging approaches in structural health monitoring using guided waves

The performance of guided wave imaging strategies used in Structural Health Monitoring relies on the accurate knowledge of mechanical properties for proper damage detection and localization. In order to increase the performance and robustness of such algorithms, it is desirable to implement autonomous approaches that can characterize the mechanical properties of the structure whatsoever the environmental and operational conditions. This article presents an innovative in situ and integrated characterization procedure based on guided waves that evaluates the thermo-mechanical properties of a structure when subjected to thermal variations prior to imaging using the same set of piezoceramic transducers used for imaging. These properties are then exploited in the damage imaging using a correlation-based algorithm (Excitelet) combined with the optimal baseline subtraction. The characterization strategy uses a genetic algorithm to identify the optimal set of mechanical properties leading to the best correlation between an analytical formulation of dispersed guided waves propagation and experimental measurements. The strategy is assessed experimentally on an aluminum plate with three sparse bonded piezoceramic transducers used for both characterization and imaging at various temperatures, representative of operational conditions of an aircraft. An artificial damage is subsequently introduced in the plate, and the effect of the accuracy of the mechanical properties estimation on imaging is assessed through the detection capability, positioning, accuracy, and correlation amplitude. The approach is then compared to three imaging methods, namely, baseline-free imaging, imaging without considering thermo-mechanical effects, and imaging using stretching methods traditionally used to compensate for temperature effects.

Time delay estimation for acoustic source location by means of short-time cross-correlation

This article presents a method which can be used for online Acoustic Emission (AE) source location in a composite plate by means of time delay estimations. A short-time cross-correlation function from the envelope of the two signals, has been developed. This method allows to estimate the time delay in the early coherent part of the signals, which is especially suitable in a very dispersive medium such as composite material. Experimental results, obtained with a glass-fiber/epoxy plate equipped with piezoelectric transducers, show that a balance of simplicity, accuracy and robustness can be achieved by using this method.

Model-assisted Assessment of Damage Detection and Localization using Guided Wave-based Imaging Techniques

In this paper, a model-assisted approach is proposed for assessing the ability of guided wave (GW)-based Structural Health Monitoring (SHM) imaging techniques to detect and localize a damage on a structure. A damage identification metric (DIM) is determined from the damage index (DI) image produced by the SHM system when a damage is present on the structure. Several damage sizes and positions are considered, thus producing various values of the DIM. The probability of detection (POD) curve is then calculated using the â vs. a approach well established in the nondestructive testing (NDT) community. For assessing the localization performance of the system, the probability of localization (POL) curve is derived from the ratio of defects correctly localized to the total number of defects, based on the calculation of the absolute error of localization (AEL). The approach is applied for assessing the performance of an actual SHM system composed of three piezoelectric actuators bonded on an aluminum plate. A good agreement is observed between POD and POL curves obtained experimentally and using a finite element model (FEM) of the system. The model-assisted approach is finally used to predict the performance of the system assuming a variation of temperature between the baseline acquisition and the detection test.