Scientific direction Development of key enabling technologies
Transfer of knowledge to industry

PhD : selection by topics

Technological challenges >> Factory of the future incl. robotics and non destructive testing
5 proposition(s).

Hybrid modeling for the simulation of ultrasonic inspection of laminate composite for the detection of inter-plies damages or weaknesses

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Simulation et Modélisation en Acoustique

01-10-2020

SL-DRT-20-0671

nicolas.leymarie@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

In the framework of the simulation of ultrasonic non-destructive techniques (UT), we consider to design specific simulation tools dedicated to laminate composites. These materials are nowadays widely used in the aeronautical field but show fragility under dynamic stresses such as impacts. Even for low-energy impacts, composite components can be weakened by localized damage, mainly by transverse cracking and delamination. Due to their anisotropic, heterogeneous and multi-layered properties, the development of UT methods for the inspection of such structures is very challenging. Numerical simulation is therefore useful, both for analysis and for the design and optimization of new UT techniques. Based on innovative numerical works, the aim of this study is to propose numerical methods dedicated to the simulation of new UT methods and in particular to the analysis of oblique incidence controls of realistic damage defects. For this, we will rely on existing developments recently done at CEA LIST based on the transient spectral element method, especially by using effective interface conditions to model a realistic delamination or local porosities in inter-plies matrix.

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Task oriented gripper design methodology for robotic manipulation ? application to pluridigital grippers with flexible joints

Département Intelligence Ambiante et Systèmes Interactifs (LIST)

Laboratoire d'Architecture des Systèmes Robotiques

01-09-2020

SL-DRT-20-0852

florian.gosselin@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

Robots are increasingly visible in our environment, with applications in e.g. fruits and vegetables picking, food packaging and human-robot interactions. All these applications require an efficient solution for grasping and manipulating many different objects. Several approaches have been proposed so far to solve this issue, ranging from double jaw pliers which are very efficient for the grasping of specific tools but cannot deal with other objects nor manipulate them finely, to pluridigital grippers which offer a higher grasping stability and can be reconfigured to grasp various objects. The latter's mechanical complexity and control difficulty however still limit their use in practice to grasping tasks and slow their spread in industry and service robotics. This thesis aims to solve these limitations by combining innovative technological solutions based on the latest advances in flexible structures and 3D printing, distributed sensors and actuators, with task oriented mechanisms synthesis methods, to develop a task oriented design methodology for versatile grasping and dexterous manipulation mechanisms. This methodology will be used for the design and control of novel grippers making use of innovative and adaptive structures that conform automatically to the objects' geometry and can generate sufficiently large in-hand movements. These developments will be validated experimentally on one or several demonstrators.

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Detection and location of faults in a multiconductor transmission line

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Fiabilité et Intégration Capteur

01-09-2019

SL-DRT-20-0890

moussa.kafal@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

The proper functioning of a distribution network depends on the ability to quickly detect the occurrence of faults, such as discharges, short circuits or the penetration of moisture in the cables. If the nature of these defects depends on the application context, the techniques used to detect them depend essentially on the ability to request a cable with test signals, and to monitor the appearance of response signals that would testify to the existence of a modification in the cables. While this approach is clear in the case of standard cables consisting of two conductors, the case of Multiconductor cables remains more complex to deal with. Indeed, applying test signals to a pair of conductors typically causes parasitic excitation of nearby conductors, because of the electromagnetic coupling that connects them. This phenomenon can considerably complicate the interpretation of the results of a test, by creating an ambiguity in the identification of the faulty driver, because several drivers can couple with those actually under test. In this thesis, the coupling will be considered as an opportunity, because it allows to probe a larger number of drivers at the same time. The intrinsic ambiguity of such a proposition can be removed by repeating the tests on several pairs of conductors. It then seems interesting to define optimum choice strategies of drivers to test to cover the largest number of neighboring drivers, without testing all possible combinations. In this sense, this proposal is parsimonious, introducing the concept of effective test surface covered from a pair of conductors. A promising decision strategy for identifying a failing driver is provided by Bayesian tree and graph-based approaches. These tools make it possible to cross the information obtained in order to identify an explanatory model, here the faulty driver. Among the advantages of this approach we can count on their ability to integrate qualitative information, such as the typology of the defect, and to provide a result formulated in terms of probabilities associated with each possible scenario, thus qualifying the interpretation of results and to assess their reliability, unlike purely numerical methods. It will then be necessary to carry out a preparatory work, making it possible to evaluate the probability a priori of observing parasitic signals from a fault on a neighboring conductor. This work will be based on the study of line theory and will provide the link between the physical aspects of Multiconductor propagation and the observables considered during the tests.

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Study of embedded prognostic strategies in wired networks based on temporal neural networks

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Fiabilité et Intégration Capteur

01-09-2020

SL-DRT-20-0891

wafa.benhassen@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

Whatever their fields of application, cables are very often victims of their operating environment. They often face aggressive conditions such as mechanical vibration, heat stress, moisture penetration, etc. These conditions favor the appearance of more or less serious defects ranging from a simple crack in the sheath to a cable break thus causing a malfunction of the system. In this context, the CEA LIST studies methods of diagnosis and prognosis of defects in cable networks based on the reflectometry method. The idea is to inject a test signal into the cable. Whenever it encounters an impedance discontinuity (i.e. a fault), some of its energy is returned to the injection point. The processing of the reflected signal subsequently makes it possible to detect and locate this defect. Despite the maturity of the reflectometry to detect a defect in a cable, it does not allow to determine the causes of the appearance of an incipient defect (ie damage of the shielding, radius of curvature, pinching, etc.) nor to predict its evolution in the future. The work of this thesis aims at developing new prognostic strategies for defects in wired networks. For this, the application of Machine Learning methods such as Artificial Neural Networks (ANN) on data from reflectometry sensors is a promising solution to solve this problem. It is in this context that the works of this thesis are inscribed.

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Assessing the variability of operators' morphology for assembly tasks using virtual reality

Département Intelligence Ambiante et Systèmes Interactifs (LIST)

Laboratoire de Simulation Interactive

01-10-2020

SL-DRT-20-0920

vincent.weistroffer@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

The aim of the thesis is to develop a tool for the evaluation of the feasability and the ergonomics of a task with operators having a different morphology than an operator performing the task in virtual reality. Two scientific questions will be addressed. The first problem consists in automatically identifying the characteristics of the task to perform (i.e. the important steps, the trajectories and/or the associated efforts), based on a limited number of demonstrations from operators using virtual reality. The second problem consists in transferring the task performance formerly identified to avatars (virtual humans) having different morphologies.

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