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The detection and quantification of defects in pipes by non-destructive testing techniques plays a crucial role in several industries (petrochemical and nuclear in particular). Once a defect is detected, assessing its severity enables to schedule maintenance appropriately, hence reducing maintenance cost and rupture or leakage risks. Structural Health Monitoring (SHM) is an approach that consists in instrumenting a structure with permanent sensors to monitor its health status throughout its life. Guided elastic waves are particularly suitable for SHM applications on thin structures (such as pipes) thanks to their ability to propagate over long distances and their high sensitivity. An SHM approach called "passive guided waves tomography" has emerged in recent years to detect and quantify corrosion in pipes (or plate-like structures). This technology is based on the combination of guided elastic wave tomography algorithms and a passive method such as the so-called ambient noise cross-correlation. It allows to obtain absolute and precise maps of the thickness of an area surrounded by a distribution of sensors without emitting waves, simply by analyzing the elastic noise that exists naturally in the pipe (due to vibrations, fluid-structure interactions with a moving fluid, etc.). In this paper passive guided waves tomography is tested in representative conditions thanks to an erosion loop that circulates air and sand. By impacting the tube wall, sand grains erode the structure, creating thickness losses that we monitor with passive tomography.

L’utilisation d’un état de référence, c’est-à-dire d’une baseline, pour l’analyse des données dans le cadre du contrôle santé des intégré (Structural Health Monitoring, SHM) par ondes guidées limite le champ d’application de ces approches. Cela a largement été démontré dans la littérature en présence de changement de température, mais c’est également vrai en présence de variations d’autres conditions environnementales et opérationnelles, ainsi que des effets du vieillissement. Cet article présente une nouvelle méthodologie auto-référencée, conçue pour être intrinsèquement robuste à l’influence des effets externes, y compris ceux qui n’ont pas été identifiés lors de la conception du système. La méthode repose sur le concept de baseline instantanée, c’est-à-dire la comparaison de plusieurs mesures acquises sur des mesures présentant un degré élevé de similitude du point de vue des ondes guidées. La subtilité de l'approche réside dans la détection de défauts ayant une faible influence sur les mesures en présence de variabilités extrinsèques et intrinsèques ayant une influence comparativement plus importante sur plusieurs échantillons similaires. La méthode comprend également une réduction de la dimension par l'extraction de quantités d'intérêt à partir des signaux acquis, permettant potentiellement l'analyse de plusieurs échantillons avec un volume de données limitées. La méthode proposée est validée avec succès sur 12 plaques d'aluminium, chacune présentant une fissure traversante de 1 à 30mm de longueur, dans un environnement de laboratoire avec des paramètres externes limités. Ensuite, l'approche est testée sur 2 échantillons composites tissés de forme complexe avec jusqu'à 7 trajectoires similaires du point de vue des ondes guidées. La détection d'une masse ajoutée est réussie sur toute la plage de températures considérée (-30◦C à 30◦C) pour toutes les fréquences d'interrogation étudiées (50, 100 et 150 kHz). La méthodologie proposée est nettement plus performante qu'un algorithme d'imagerie de l’état de l’art avec compensation de température appliqué aux mêmes données.

Optical fiber transducers such as Fiber Bragg Gratings (FBG) are promising solutions for guided waves Structural Health Monitoring (SHM) due to their low intrusivity and their ability to cope with harsh environments (extreme temperatures, radiations, explosive atmospheres…). We present here a solution enabling measurements under varying environmental and operational conditions, which is mandatory for many applications in SHM, the low complexity of the solution ensuring good integration capacities. The effect of the length of the FBG was also studied to enable the optimization of the system sensitivity.

The use of guided waves enables to monitor wide areas of structures with a limited number of sensors and/or a limited acquisition time. In particular, guided wave tomography algorithms give a quantitative image of the residual thickness of the monitored structured, for example a corroded pipe. The idea is to use the dispersion curves to link a change in phase or group velocity to a change in thickness. The method developed at CEA-List includes an auto-calibration phase, eliminating the need of a baseline to work, therefore enabling its use in presence of varying environmental and operational conditions. One drawback of tomography techniques is that they need many sensors compared to more conventional algorithms such as RAPID or Delay and Sum. We propose here a passive version of tomography to limit its intrusiveness by using data obtained by post-processing the ambient elastic noise in the structure. This enables the use of Fiber Bragg Gratings (FBG) on optical fibers as ultrasonic sensors. The use of FBGs drastically reduces the burden of the system, as several gratings can be multiplexed on a single optical fiber. Furthermore, these sensors are suited for many applications because of their resistance to harsh conditions (extreme temperatures, explosive atmosphere, radiations…).

This paper presents a study of guided wave tomography for corrosion monitoring under varying environmental conditions. Guided wave tomography can be computed in an ‘absolute’ mode thanks to an automatic calibration using solely the data of the current acquisition. This is interesting because no baseline is needed. In particular, this paper studies the capacity of absolute tomography algorithms to be robust to temperature fluctuations. Experimental validations of the method are presented and results on the method’s robustness to temperature variations are shown through acquisitions carried out in a climate chamber over a wide range of temperatures.