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July 25, 2019 | Listening to the flows inside pipes to monitor structural health

List canalisations cndA passive non-destructive testing (NDT) method was developed for the inspection of pipes. The sound of the flows inside of the pipes is processed by a purpose-developed tomography algorithm that reconstructs the pipes’ thickness profile.

The active methods used in structural health monitoring (SHM) consist of emitting a wave, and then studying the modifications to the wave when it encounters a defect. Passive methods are different in that they do not require the emission of a wave prior to taking measurements. Researchers at List, a CEA Tech institute, recently developed a method to measure and analyze the waves generated by the flow of a fluid inside a pipe to detect any defects in the pipe.

The solution developed is based on pairs of fiber Bragg grating rings that serve as elastic wave receivers, and offer the advantage of being more robust under extreme conditions (high temperature, radiation, etc.) than the piezoelectric sensors conventionally employed in active SHM methods. The information from the pairs of sensors is processed by a purpose-developed tomography algorithm to reconstruct the pipe-wall thickness profile. The resulting profile can be used to detect, identify, locate, and measure any defects present.

The method was tested and validated on artificial defects and its performance was compared to that of a traditional active method. It was a success! List, that earned the Carnot seal in 2006, is now partnering with French electric utility EDF to investigate how the method can be used in industrial environments. Other applications, such as in aeronautics, are also possible.

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July 9, 2019 | Artificial intelligence successfully implemented in low-power demonstrator

SamurAI 250SamurAI is the first-ever demonstrator system to bring together two previously-incompatible worlds: artificial intelligence and low-power communicating devices.

Reducing the energy consumption of communicating devices is a top priority for manufacturing companies. And yet, energy efficiency can be difficult to deliver when integrating certain complex functions—especially those powered by artificial intelligence. CEA Tech institutes Leti and List* have built the first-ever demonstrator system that combines a very-low-power platform with a neural network accelerator. Even better, the demonstrator can support end-use scenarios representative of what the market is currently looking for.

The system is built on a L-IoT (low-power IoT) circuit developed by Leti and an architecture that features a low-power wake-up and processing platform, plus an on-demand processing platform that is activated only when complex processing is required. List's PNeuro neural network accelerator is integrated into the on-demand platform to provide the system with parallel processing optimized for artificial intelligence.

The demonstrator, called SamurAI, was used to complete local neural processing to detect, via an infrared camera, human presence and count the number of people at the scale of a room. The goal was to illustrate the system's low energy consumption in sleep mode and its capacity to perform complex processing on demand and to activate this processing very rapidly and with a high degree of flexibility.

*List earned the prestigious Institut Carnot seal in 2006 (Institut Carnot TN@UPSaclay).

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June 25, 2019 | Two CEA Tech demonstrators in Novares’ Nova Car 2

cea list novacar 2Novares unveiled its Nova Car 2 demo car to manufacturers on June 25. The car incorporates around fifteen patented innovations, two of which were developed by CEA Tech institutes.

Novares, an automotive supplier that specializes in plastic parts, recently unveiled its latest demo car, Nova Car 2. Designed for automotive-industry stakeholders, the car showcases the latest innovations to make cars more interactive and user-friendly. This most recent incarnation of the demo car packs in fifteen patented innovations, two of which were developed by CEA Tech institutes.



CEAList bouton rotatif novacar 2
The rotating piezoelectric button with haptic feedback developed by CEA List

The first, developed by List, is a rotating piezoelectric button with haptic feedback integrated into the center console. The reprogrammable button can be used to move from one system to another (radio, air conditioning, etc.), giving the driver relevant and personalized haptic feedback on the system being controlled.

The second, developed by Leti, is found at the core of a door locking and unlocking system on the door handle and rear panel. Based on thin-layer piezoelectric sensors with a purpose-built design, the system is much more sensitive and reliable than what is currently available on the market. This innovation resulted in a CEA spinoff, WORMS, that will be founded by September and that will have exclusive rights to commercialize the technology.

Novares will kick off its Nova Car 2 world tour in July and also plans to pursue its partnership with all three CEA Tech institutes. Leti, Liten, and List are already working on new and innovative proof-of-concept prototypes for Nova Car 3.






19 juin 2019 | Le programme Accompagnement Smart Industrie pour les PMI

smart industrie 250Dans le cadre de sa stratégie « Smart Industrie », la Région Île-de-France accompagne 300 PMI franciliennes dans leurs projets de transformation. 

Le programme Accompagnement Smart Industrie est l’opportunité pour les PMI d’améliorer leur performance industrielle globale et leur compétitivité en jouant sur les facteurs humains, technologiques, organisationnels et sur les ruptures marché.

Les experts du CEA List, labellisé institut Carnot, accompagnent les PMI dans une démarche pragmatique, adaptée à leurs enjeux, pour agir sur les leviers de compétitivité du référentiel Industrie du Futur. De cette façon, les PMI ont accès à l’ensemble des opportunités d’innovation proposées par le Digital Innovation Hub de DIGIHALL.

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June 17, 2019 | Electromagnetism used to study the mechanical properties of steel

List acier cnd 250Researchers at List, a CEA Tech institute, have developed simulation models and tools that leverage electromagnetism to characterize steel. These models and tools will be integrated into the CIVA platform so that they can be used to develop industrial non-destructive testing processes.

The mechanical properties of steel are closely related to the steel’s microstructure. The same is true of steel’s magnetic behavior. Modifications to the microstructure can affect the material’s mechanical and magnetic properties.

So, studying steel’s electromagnetic behavior can provide indirect insights into its mechanical properties—but only if other factors that cause variations in the magnetic properties of the metals that make up the steel are taken into account.

List, that earned the Carnot seal in 2006, developed a simulation model of an industrial non-destructive testing process that uses macroscopic measurements of steel’s electromagnetic signature. The idea is to take into account the related sources of variability and, especially, the types of probes used and the material’s heterogeneity. The method leverages an original semi-analytical formulation of the problem and non-linear models to rapidly arrive at a robust solution.

These tools will ultimately be integrated into the CIVA platform so that they can be transferred to industrial users. Whether it is to monitor structural health or control quality during manufacturing, inspecting the microstructure of steel is a major challenge in the nuclear, automotive, and other industries.

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