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The National Engineering School of Tarbes (ENIT) is a French engineering school with a curriculum from undergraduate to graduate studies for general engineers. Curriculum ends by an equivalent Master degree in sciences. ENIT students are particularly involved into mechanical, civil, industrial engineering, material science and design of integrated systems. From the first year of study, students tackle theoretical tools for engineers. Moreover, in a curriculum composed of several different disciplines, connections between scientific subjects may be difficult to weave. As a consequence, student activities for solving engineering problems were developed. The basic concept is to clearly illustrate how theoretical tools can be used in an activity linked to engineering and more generally to student life. In addition, future engineers must be acquainted and trained to ethic values, especially those used in team work. During team working, honesty and benevolence are important core values to be encouraged as a basis of trust that has been identified as one of the cornerstones for performing teams. Consequently, the principle of team working for students was adopted and humanities are associated into the project to manage ethical and professional standards. Thus, the chosen teaching activity is a project-based learning team work that addresses on the one hand application of integration and derivation to expression of needs of consumable supplies and notions around professional ethics on the other hands.

International audience; Validation and verification are the most important issues in railway applications due to cost and security reasons. Therefore, having a model of the system would be necessary in this case. Due to non-ideal test conditions in industrial applications, an accurate parameter identification process has to be defined. In this paper, bond graph method is used to model energy exchanges within components of a traction chain. More precisely, the non-linear transformer model and its parameter identification is studied. In the case of non-ideal test conditions, the usual Jiles-Atherton parameter identification procedure can not be performed. Regarding state of the art, the Jiles-Atherton parameter identification is discussed. It is highlighted that an uncomplete hysteresis cycle, including extremum point and coercive field are mandatory for an accurate parameter identification. The proposed identification process is applied to a real application case. The obtained parameters are then inserted into the overall system model. The consecutive simulations are compared to experimental data obtained through traction chain test bench.

International audience; With the emergence of new semi-conductor technologies, an increasing number of high integrated power electronic modules are designed. The increase of reliability of power modules induces the precise knowledge of the local temperature, even if it cannot be measured at any location. In this paper, the design of a soft sensor, more precisely a linear functional observer, is proposed. It enables the estimation of the temperature at any location using measurements provided from thermal sensors located at a number of precise points. The aim is to design a reduced size observer that could be implemented on a real-time embedded target such as Digital Signal Processor. Consequently, it is necessary to obtain a minimal order observer to limit the computation complexity.

International audience; Testing of proton exchange membrane fuel cell system is one of the most important issues due to the cost and security reasons in railway applications. To reduce the cost, it would be necessary to have a representative simulation model for this case. Having an accurate model of proton exchange membrane fuel cell system requires considering several auxiliary circuits. However, in industrial application, the accurate model of proton exchange membrane fuel cell system and corresponding information are not often provided by the designer. Moreover, the simplicity and representativity of model is required to be compatible with overall traction chain model. The model has to be suitable for system simulation and not design purpose. In this paper, a simplified model of PEMFC system is proposed using the experimental profile mission. The impact of all the environment system of proton exchange membrane fuel cell stack is estimated using the average of polarization curve on several operational points. The parameter identification process is applied, and the obtained parameters are then inserted on the overall system of fuel cell stack. The experimental data obtained through train is compared with the consecutive simulation results.

International audience; This paper focuses on multi-physics modeling of encapsulating gels in power electronic modules for transient and steady-state simulation. With the emergence of wide-bandgap semiconductors such as SiC or GaN, operating at a higher temperature than conventional Si power chips, this passive element of the packaging appears as a few studied element sensitive to thermal and mechanical stresses. A thermo-mechanical coupled modeling of the material, based on bond graph representation, is presented. This approach allows to establish, under the same formalism, an analogy between the different physical domains. From this analogy, a multi-physical nonlinear state space representation is built, allowing transient simulation of the thermo-mechanical behavior of the material. This way of modeling and simulating is particularly adapted for a preliminary study during the upstream phases of design of the power electronic modules. It quickly establishes the maximum temperature and mechanical strains experienced by the gel.

International audience; The aim of the present study was to evaluate the effects of mental fatigue (MF) induced by a 90-min continuous demanding cognitive task on balance control. Twenty healthy young participants were recruited. They had to perform three postural tasks (on a stable support with eyes open, with eyes closed and on a wobble board) while standing on a force platform before and after watching a documentary in a control condition or carrying out a prolonged continuous demanding cognitive task (AX-continuous performance test—AX-CPT) in a MF condition. Results showed that performing the AX-CPT generated. MF since participants felt a higher subjective workload from the NASA Task Load Index after the AX-CPT than after viewing the documentary. Both the AX-CPT and the viewing of the documentary impaired balance control, mainly by affecting postural regulatory mechanisms which evolved towards a less automatic and less complex regulation mode with an increased participation of cognitive resources. MF generated by the AX-CPT affected balance control by compromising the attentional processing, while the deleterious influence of watching a documentary on postural control could stem from an adverse effect of prolonged sitting on balance control during subsequent standing.

This paper considers an iterative procedure to design a minimum possible order unknown input functional observer for linear time-invariant (LTI) systems. Necessary and sufficient conditions for the existence of the observer are given. The proposed procedure is simple and is based neither on the solution of a generalized Sylvester equation nor canonical forms. This procedure can be easily implemented due to its incremental form. The main feature of our procedure is then the simplicity of the design. Moreover, in the case of a single functional to be observed, a minimum order stable linear unknown input functional observer is obtained.

International audience; This paper deals with the estimation of heat sources from infrared thermographic measures on anisotropic CFRP(Carbon-Fibre Reinforced Composites). Such procedure combines the data processing of the thermal signal, especially as spatial and temporal derivation quantities involved in the heat equation are notably affected by the measurement noise, and the determination of thermo-physical properties of the material, especially to account for the anisotropic conductivity behavior of the material. A comparative analysis of different filtering techniques is done to define a filtering method able to decrease the noise while keeping the useful features of the signal. Then, we use a homogenization scheme based on single-inhomogeneity solutions of Eshelby to derive the transversely isotropic thermal conductivity tensor.

International audience; The present paper is devoted to the determination of heat source dissipation from infrared thermographic measurements. Such procedure is mainly based on the heat diffusion equation provided by thermodynamics principles. Especially, this requires time and spatial derivation of temperature fields and the knowledge of the material thermal conductivity. This work intends to extend such classical procedure for isotropic materials to the anisotropic context. At first, we propose a comparative study of several filtering methods required for the data processing of noisy and discrete thermal acquisitions. In a second part, a transversely isotropic effective thermal conductivity tensor is estimated by means of ahomogenization-based method. From these both results, a heat source application is presented in order to analyze damage phenomena in transversely isotropic CFRP submitted to tensile tests.

This study deals with new integrated systems for power electronic applications including wide-band gap semiconductors. The integration of Silicon carbide (SiC) components provides new perspectives such as higher temperature operating points than conventional Silicon (Si) semiconductors. The present work intends to study the electro-thermal behaviour of an integrated buck converter composed of a Silicon IGBT (Insulated-Gate Bipolar Transistor) and a Silicon carbide diode. An analysis of local heat sources due to Joule effect and compact thermal model of the assembly are proposed to predict local temperature of power electronic components.

This study deals with new integrated systems for power electronics applications including wide-gap semiconductors. Integration of Silicon carbide (SiC) components provides for instance new perspectives with higher temperature operating points than conventional Silicon (Si) semiconductors. The present work intends to study an integrated buck converter composed of a Silicon IGBT (Insulated-Gate Bipolar Transistor) and a Silicon carbide diode. By means of infrared thermography, an analysis of the thermal disparities induced within such a hybrid assembly under various electrical loads is proposed, regarding especially the consequences of the electrical power transfer and the spatial distribution of the thermal field.

International audience; This paper deals with mechanical fault diagnosis in three-phase induction machines from stator current measurements. According to machine models, mechanical faults lead to amplitude and/or phase modulations of the measured stator current with possibly time varying carrier frequency. The modulation diagnosis requires a univocal de¯nition of the instantaneous phase and amplitude. This is performed by associating a complex signal to the real measured one. For a convenient separate modulation diagnosis, the complex signal instantaneous phase and amplitude are expected to carry respectively information about the phase and amplitude modulations. The complex signal is classically obtained through the Hilbert transform. Under Bedrosian conditions, the so-called analytic signal allows a separate modulation diagnosis. However, mechanical faults may also produce fast modulations violating the Bedrosian conditions. This study proposes an alternative complex signal representation which takes advantage of the three stator current measurements available in a three phase machine. From two stator current measurements, the Concordia transform builds a complex vector, the so-called space vector, which unconditionally allows separate modulation diagnosis. This paper applies and compares the Hilbert and Concordia transforms, theoretically and in case of simulated and experimental signals with various modulation frequency ranges.

International audience; This paper deals with mechanical fault monitoring in induction machines from stator current measurements. The considered faults lead to amplitude and/or phase modulations of the measured stator current. The different faults can be characterized by their time-frequency signatures via the Wigner distribution. The time-frequency representations apply to complex signals that may be obtained through the Hilbert transform of the real measured signal. In case of high frequency modulations, it can not be taken advantage of the time frequency signatures. This study proposes an alternative complex signal representation for modulated stator currents. The so-called space vector is obtained through the Concordia transform. From three stator current measurements, the Concordia transform builds a complex vector which conveniently carries the information about phase and amplitude modulations. This paper applies and compares the Wigner distribution computed with the Hilbert and Concordia transforms in case of simulated and experimental signals with various modulation frequency ranges.

International audience; This paper deals with mechanical fault diagnosis in induction machines from stator current measurements. Mechanical faults lead to amplitude or phase modulations on stator currents that induce different time-frequency signatures. However, the time-frequency representations apply on complex signals for a univocal phase and modulus definition. When modulation frequencies are lower than the carrier frequency, this complex signal is the analytic signal obtained through the Hilbert transform of the real measured signal. However, bearing faults, for instance, may produce high frequency modulations. An alternative is to obtain the complex signal through the Concordia transform that takes advantage of the additional information available using two of the three phases of an electrical machine. However, Concordia Transform requires the previous validation of a particular stator current model in three phase machine in case of mechanical faults. This paper uses the argument of the Fourier Transform for the validation of the model. Using the Hilbert and Concordia transforms of the proposed model, the Wigner-Ville distribution of narrow-band and wide-band frequency modulated signal is expressed. Finally, this paper applies the two transforms on simulated and experimental signals and provides a diagnosis of amplitude or phase modulation in various conditions.

International audience; This paper deals with mechanical fault monitoring in induction machines from stator current measurements. At variable speed, the different faults can be characterized by their time-frequency signatures. However, the time-frequency representations apply to complex signals for a univocal phase and modulus definition. Under usual modulation conditions, this complex signal is the analytic signal obtained through the Hilbert Transform of the real measured signal. Indeed, classical mechanical faults result in modulation frequencies which are lower than the carrier frequency. The analytic signal complex envelope and instantaneous frequency thus provide the amplitude and phase modulations respectively. However, bearing faults, for instance, may produce high frequency modulations. Then, the analytic signal phase and modulus each carry information on both phase and amplitude modulations. This study proposes an alternative complex signal representation in this case. The proposed representation, namely the Concordia Transform, takes advantage of the additional information available in the case of a three phase machine. By using two stator currents, the Concordia Transform builds a complex vector which conveniently carries the information about phase and amplitude modulations. This paper applies the Hilbert and Concordia Transforms to simulated and experimental signals and provides a diagnosis of amplitude or phase modulation in various conditions.

International audience; This paper deals with the application of motor current spectral analysis for the detection of rolling bearings damage in asynchronous machines. Vibration measurement is widely used to detect faulty operations. However, this approach is expensive and cannot always be performed. An alternative is to base the monitoring on electrical quantities such as the machine stator current which is often already measured for control and detection purposes. Firstly, to define an automatic detector for bearing faults based on mechanical quantities, vibration spectra are analyzed. Afterwards, it is shown that bearing faults induce mechanical load torque oscillations. Then, a theoretical stator current model in case of load torque oscillations demonstrates the presence of phase modulation. Related sideband components on current spectrum can be used for detection. Experimental measurements show that a transfer function including resonance links amplitudes of sideband components to the torque oscillation frequency. This singularity will be used to improve the detection efficiency. A fault detector using the energy of stator current in specific frequency ranges is then proposed. The efficiency of the detector is studied for different operating conditions. The supply frequency values are particulary investigated to demonstrate that using the resonance previously described could improve detection performances.

International audience; This paper deals with the application of motor current spectral analysis for the detection of artificially damaged rolling bearings in asynchronous machine. Vibration monitoring of mechanical characteristic frequencies related to the bearings is widely used to detect faulty operations. However, vibration measurement is expensive and can not always be performed. An alternative is to base the monitoring on the available electrical quantities e.g. the machine stator current which is often already measured for control and protection purposes. The bearing faults reveal the presence of mechanical load torque oscillations. A theoretical stator current model in case of load torque oscillations demonstrates the presence of phase modulation. Related sideband components appear in the current spectrum and can be used for detection. Experimental measurements show that their amplitudes are linked to the fault frequency by a transfer function including resonance. This singularity will be used to improve the detection efficiency. Fault detectors using the energy of stator current in specific frequency ranges are then proposed. The efficiency of indicators is studied on long and short data records of experimental current for different bearing faults. The most significant of the investigated indicators is finally improved to guarantee a higher reliability of the detection.

International audience; This paper deals with the application of Luenberger speed observer for the detection of damaged rolling bearings in asynchronous machines. Vibration monitoring of mechanical characteristic frequencies related to the bearings is widely used to detect faulty operations. However, vibration measurement is expensive and can not always be performed. An alternative is to base the monitoring on the available electrical quantities e.g. the machine stator current which is often already measured for control and protection purposes. This work investigates another detection approach using estimated variables such as mechanical rotating speed. Considering that bearing faults induce load torque oscillations, a theoretical stator current model in case of load torque oscillations demonstrates the presence of phase modulations. Then, a theoretical estimated rotor flux and speed model in case of load torque oscillations demonstrates the presence of harmonics related to load torque oscillations. These components appear in the estimated speed spectrum and can be used for detection purposes. Measurements show that speed spectral energy is modified in specific frequency ranges corresponding to bearing faults. A fault detector is then proposed. The efficiency of the indicator is studied on long data records of measurements for different operating conditions. The investigated indicator proves that the detection of bearing faults is ensured by using estimated mechanical speed.

International audience; This study deals with the application of vibration and motor current spectral analysis for the monitoring of rolling bearings damage in asynchronous drives. Vibration measurement is widely used to detect faulty bearings operations. However, this approach is expensive and cannot always be performed, while electrical quantities such as the machine stator current are often already measured for control and detection purposes. Signal processing methods and global indicators associated with bearing fault detection of vibration measurements are recalled. Compared to these methods, an automatic detector based on vibration spectral energy extraction is then proposed and its performances are discussed. Moreover, load torque measurements underlines that bearing faults also induce mechanical load torque oscillations. Therefore a theoretical stator current model in case of load torque oscillations is used to demonstrate the presence of phase modulation (PM) on stator currents. Frequency behaviour of the related sideband components is strongly investigated for monitoring purposes. Thus, a fault detector using the extraction of spectral energy of stator current is proposed to detect damaged bearings. This detector is then compared to the one defined on vibration signals.

International audience; This paper focuses on induction motor monitoring based on stator current measurements. The diagnosis aims at identifying the mechanical faults related to either airgap eccentricity or load torque oscillation. The airgap eccentricity (respectively load torque oscillation) essentially results in an amplitude (respectively phase) modulation of the stator current. Classical spectral analysis allows for the detection but not for the discrimination of these modulations. Time-frequency representations, such as the spectrogram or the Wigner distribution, provide appropriate signatures for fault discrimination. This paper proposes to perform the decision task from the time-frequency representation using the surrogate data technique. In a deterministic context, the phase and amplitude modulations can be considered as non-stationarities since they correspond to time-variations of the signal spectral content. The detection of a modulation is expressed as a binary hypothesis test. The null hypothesis corresponds to a signal without modulation. Stationarized/unmodulated replicas of the observed (possibly modulated) signal are obtained by phase randomization of its Fourier transform. These so-called surrogates provide a reference for the null hypothesis. The observed signal is then compared to these surrogates using appropriate distances in the time-frequency domain. A one-class classifier may be used considering the surrogates as a learning set. This classifier detects outliers corresponding to the modulation and thus to the failures. Moreover, this technique provides the information concerning the predominant type of modulation. This diagnosis method will be tested on simulated and experimental signals.