Potentiel de la robotique pour l'inspection thermographique par chauffage inductif

La thermographie par courants de Foucault (ECT) est une méthode de thermographie active. L’excitation inductive génère des courants de Foucault dans les spécimens conducteurs. En présence de défauts, la circulation des courants est affectée par ces discontinuités produisant un changement dans la distribution de la température autour des défauts. Ces changements sont observés avec une caméra infrarouge. Dans ce travail, on présente une application robotique de la thermographie par courants de Foucault. Une interface robotique a été développée et tous les capteurs utilisés ont été intégrés à la plateforme. Des simulations ont été achevées avec COMSOL Multiphysics en variant différents paramètres. Des expériences ont été menées sur plusieurs spécimens (de différents matériaux) avec des défauts de différents types et tailles. La linescan thermographie est principalement étudiée et d’autres modes d’inspections ont été explorés. Les images résultantes sont reconstruites avec un algorithme dédié. Finalement, les résultats de la méthode sont comparés à ceux de la thermographie optique (par halogène) pour montrer les capacités de la méthode.Eddy current thermography (ECT) is an active thermography method. The inductive excitation generates Eddy currents in electrically-conductive specimen. In a presence of defects, the eddy current flow is affected by these discontinuities leading to changes in the temperature distribution in the specimen around the defects. These changes are observed by an infrared camera. In this work, we present a robotic application of the method. A robotic interface is developed and all the sensors needed are integrated to the platform. Simulations are performed using COMSOL Multiphysics by varying different parameters. Experiments are realised on different specimens (made of different materials) with defects of different sizes. The linescan Eddy current thermography is studied and other modes are explored. The resulting images are reconstructed with a dedicated algorithm. Finally, the method’s results are compared to optical thermography to show the capability of the method

Comparative study of Line Scan and Flying Line Active IR Thermography operated with a 6-axis robot

International audienceIn this paper, two Non Destructive Testing approaches by active infrared thermography mounted on a 6-axis robot are presented and studied. Data acquisition and thermal excitation is carried out dynamically over various CFRP specimens with increasing geometry complexity, from planar, to convex and concave shapes. An automated procedure is proposed to reconstruct thermal image sequences issued from the two scanning procedure studied: Line Scan and Flying Line procedures. Defective area detection is performed by image processing and an inverse technique based on thermal quadrupole method is used to map the depth of flaws. Results obtained are discussed and perspectives are addressed

Impact modelling and a posteriori non-destructive evaluation of homogeneous particleboards of sugarcane bagasse

With a view to gaining an in-depth assessment of the response of particleboards (PBs) to different in-service loading conditions, samples of high-density homogeneous PBs of sugarcane bagasse and castor oil polyurethane resin were manufactured and subjected to low velocity impacts using an instrumented drop weight impact tower and four different energy levels, namely 5, 10, 20 and 30 J. The prediction of the damage modes was assessed using Comsol Multiphysics ® . ®. In particular, the random distribution of the fibres and their lengths were reproduced through a robust model. The experimentally obtained dent depths due to the impactor were compared with the ones numerically simulated showing good agreement. The post-impact damage was evaluated by a simultaneous system of image acquisitions coming from two different sensors. In particular, thermograms were recorded during the heating up and cooling down phases, while the specklegrams were gathered one at room temperature (as reference) and the remaining during the cooling down phase. On one hand, the specklegrams were processed via a new software package named Ncorr v.1.2, which is an open-source subset-based 2D digital image correlation (DIC) package that combines modern DIC algorithms proposed in the literature with additional enhancements. On the other hand, the thermographic results linked to a square pulse were compared with those coming from the laser line thermography technique that heats a line-region on the surface of the sample instead of a spot. Surprisingly, both the vibrothermography and the line scanning thermography methods coupled with a robotized system show substantial advantages in the defect detection around the impacted zone

An Evidential Fusion Approach for Activity Recognition in Ambient Intelligence Environments

International audienceWith the growing emergence of ambient intelligence, ubiquitous computing, sensor networks and wireless networking technologies, "ubiquitous networked robotics" is becoming an active research domain of intelligent autonomous systems. It targets new innovative applications in which robotic systems will become part of these networks of artifacts to provide novel capabilities and various assistive services anywhere and anytime, such as healthcare and monitoring services for elderly in Ambient Assisted Living (AAL) environments. Situation recognition, in general, and activity recognition, in particular, provide an added value on the contextual information that can help the ubiquitous networked robot to autonomously provide the best service that meet the needs of the elderly. Dempster-Shafer theory of evidence and its derivatives are an efficient tool to handle uncertainty and incompleteness in smart homes and ubiquitous computing environments. However, their combination rules yield counter-intuitive results in high conflicting activities. In this paper, we propose a new approach to support conflict resolution in activity recognition in AAL environments. This approach is based on a new mapping for conflict evidential fusion to increase the efficiency and accuracy of activity recognition. It gives intuitive interpretation for combining multiple sources in all conflicting situations. The proposed approach, evaluated on a real world smart home dataset, achieves 78% of accuracy in activity recognition. The obtained results outperform those obtained with the existing combination rules

An evidential fusion approach for activity recognition under uncertainty in ambient intelligence environments

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Evidence Combination Based on CSP Modeling

International audienceThe evidence theory and its variants are mathematical formalisms used to represent uncertain as well as ambiguous data. The evidence combination rules proposed in these formalisms agree with Bayesian probability calculus in special cases but not in general. To get more reconcilement between the belief functions theory with the Bayesian probability calculus, this work proposes a new way of combining beliefs to estimate combined evidence. This approach is based on the Constraint Satisfaction Problem modeling. Thereafter, we combine all solutions of these constraint problems using Dempster's rule. This mathematical formalism is tested using information system security risk simulations. The results show that our model produces intuitive results and agrees with the Bayesian probability calculus

New Evidence Combination Rules for Activity Recognition in Smart Home

International audienceThe evidence theory and its propositional conflict redistribution variant rules are mathematical formalisms used to represent uncertain as well as ambiguous data. The evidence combination rules proposed in these formalisms do not satisfy the idempotence property. However, in a variety of applications, it is desirable that the evidence combination rules satisfy this property. In response to this challenge, the present work proposes a new formalism for reasoning under uncertainty based on new consensus and conflicting of evidence concepts. This mathematical formalism is evaluated using a real world activity recognition problem in smart home environment. The results show that one rule of our formalism respects the idempotence property and improves the accuracy of activity recognition

Automated dynamic inspection using active infrared thermography

Active thermography is a proven technology used in a wide variety of applications. In the most common approach using a static configuration, the elements involved in the inspection do not move. This presents serious drawbacks when it is applied to the inspection of large products and machines. An alternative approach is the dynamic inspection, which enables the inspection of large and complex products with better resolution, but it is also extremely challenging as data reconstruction is necessary. This work analyzes two methods for dynamic inspection using active infrared thermography: the thermal photocopier and the line scan. Automatic robust methods are proposed to calculate the temperature-time history, producing a pseudostatic sequence that can be further processed using advanced data processing algorithms to improve defect detection. Results demonstrate the robustness of the proposed methods and the ability to inspect large products with excellent results.Peer reviewed: YesNRC publication: Ye