Automated uncertainty-based extraction of modal parameters from stabilization diagrams

International audienceThe interpretation of stabilization diagrams is a classical task in operational modal analysis, and has the goal to obtain the set of physical modal parameters from estimates at the different model orders of the diagram. The diagrams are contaminated by spurious modes that appear due to the unknown (non-white) ambient excitation and sensor noise, as well as possible over-modelling. Under the premise that spurious modes will vary and physical modes will remain quite constant at different model orders, the focus is to retrieve the physical modes that constitute the identified model, while rejecting the non-physical, spurious modes. Over the last decade, extensive research has been devoted for developing automated strategies facilitating their interpretation. To this end, the interpretation is in principle disconnected from the identification method and boils down to three stages i.e., clearing the diagram from the spurious mode estimates, aggregating the modal parameter estimates in modal alignments and the final parameter choice. Besides the point estimates of the modal parameters, also their confidence bounds are available with some identification methods, such as subspace identification. These uncertainties provide useful information for an automated interpretation of the stabilization diagrams. First, modes with high uncertainty are most likely non-physical modes. Second, the confidence bounds provide a natural threshold for the automated extraction of modal alignments, avoiding the requirement of a deterministic threshold regarding the allowable variation within an alignment. In this paper, a strategy is presented for the automated mode extraction considering their uncertainties, based on clustering a statistical distance measures between the modes. The relevance of the uncertainty consideration in the automated extraction will be demonstrated on vibration data from two bridges

Identification of resistivity parameter by meta-model methods

La tomographie électrique est une méthode permettant d'identifier la résistivité d'un milieu grâce à la résolution d'un problème inverse. Le milieu sondé est modélisé par la méthode des éléments finis puis la paramétrisation se fait en sous-domaines de résistivité constante dont on cherche à identifier les valeurs. Numériquement cela revient à minimiser l'écart entre un jeu de données mesurées et un jeu de données calculées en faisant varier les paramètres du modèle. Dans le cas de la résistivité, ces jeux de données sont des mesures de potentiels. Ce problème est résolu en géophysique par la méthode de Newton grâce aux hyptothèses permettant de calculer analytiquement les directions de descente de l'algorithme de minimisation. Dans le cas de milieux finis, l'impossibilité d'évaluer analytiquement les directions de descente de l'algorithme de minimisation entraîne une augmentation substantielle du temps de calcul. Dans le but d'effectuer un suivi des structures en milieu maritime, cette méthode est adaptée au domaine du génie civil. Il est ainsi proposé de substituer au modèle éléments finis direct de propagation du courant électrique, un modèle approché de faible rang. La méthode d'identification adaptée ainsi proposée est une méthode à gradient basée sur des évaluations du modèle approché. Ses performances sont évaluées à travers des tests numériques par comparaison avec une méthode d'identification classique. Les avantages de l'utilisation de ces modèles approximés sont mis en avant, notamment la possibilité d'obtenir un gradient explicite non disponible sur le modèle direct. Enfin, le suivi du port est détaillé via une application au quai de Saint-Nazaire mettant en avant les corrélations entre la température et la résistivité. Puis une méthode de suivi de résistivité pour une structure in situ est proposée dans une dernière partie.Electrical tomography is a method for identifying the resistivity of a medium by solving an inverse problem. The probed medium is modelled by the finite element method and then the parameterisation is done in sub-domains of constant resistivity whose values are to be identified. Numerically, this amounts to minimising the difference between a set of measured data and a set of computed data by varying the model parameters. In the case of resistivity, these data sets are potential measurements. This problem is solved in geophysics by Newton's method thanks to the hypotheses allowing to compute analytically the directions of descent of the minimisation algorithm. In the case of finite medium, the impossibility of analytically evaluating the directions of descent of the minimisation algorithm leads to a substantial increase in computation time. In order to monitor structures in a maritime environment, this method is adapted to the civil engineering domain. It is thus proposed to substitute the direct finite element model of electric current propagation with an approximate model of low rank. The proposed adapted identification method is a gradient method based on evaluations of the approximated model. Its performance is evaluated through numerical tests by comparison with a classical identification method. The advantages of using these approximate models are highlighted, in particular the possibility of obtaining an explicit gradient not available on the direct model. Finally, the monitoring of the harbor is detailed, with an application to the Saint-Nazaire wharf highlighting the correlations between temperature and resistivity. Then a resistivity monitoring method for an in situ structure is proposed in the last part

Monitoring of a Reinforced Concrete Wharf Using Structural Health Monitoring System and Material Testing

This paper presents the Structural Health Monitoring (SHM) system developed for a port wharf of a freight terminal, in Saint-Nazaire, France. This concrete structure has been equipped with a multi-sensor system for the monitoring of concrete ageing. The measurement chain is designed to detect the penetration of chloride ions in order to quantify the risk of reinforcement bars corrosion. Modifications of the mechanical behavior of the structural elements of the wharf are also monitored. At first, the sensors embedded within the structure and the acquisition devices are described. The data from the monitoring performed during the first months of the structure service life are then presented. The concrete monitoring at early age providing data like temperature history, strain and resistivity is useful both for the wharf owner and the construction company since it indicates where concrete shrinkage is likely to cause cracking and gives an indicator of material hardening. These data were compared to the results of material tests carried out on concrete. The study shows that a measurement chain dedicated to the SHM could be a useful tool for validating the quality of the construction of a reinforced concrete structure before being used in the framework of long-term monitoring