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International audience; Single-chamber microbial fuel cells (MFCs) with air-cathodes and new anodes made of stainless steel entangled wires are developed. Increasing the cathode surface area significantly increases performances (doubling the cathode surface area increases the maximum power by +23,3 % and tripling it by +59,8 %). By contrast, increasing the anode surface area rapidly leads to performance saturation (doubling the anode surface area increases the maximum power by +37.8 % but tripling it by only +39.3 %). In addition, decreasing the electrode spacing from 6 cm to 4 cm improves the maximum power by +21.3 % and from 4 cm to 2 cm by +27.9 %. This results permit to optimally dimension the architecture of the MFC in order to maximize energy production while minimizing the amount of materials used to minimize costs. This in turn is likely to enable the development of effective solutions for energy harvesting.

International audience; A disposable ovulation test is operated using a flow stack of 5 in series connected glucose biofuel cells giving an open circuit voltage (OCV) of 3.5 V. Such tests consume at total around 60 μWh of energy and in average 1.7 mW of power during one run of around 12 min which are supplied by a CR1220 3 V lithium button battery in the commercialized device. We replaced this battery by the glucose biofuel cell stack and observed during the measurements and display steps peak currents up to 1.4 mA inducing a voltage drop down to 2.8 V during few seconds (4 mW of power consumption). Even such power peaks are supported by the presented biofuel cell stack assuring the necessary operational cell voltage and current. After the measurements towards Luteinizing Hormone (LH) detection the display remains turned on for 8 min and consumes just 2 μW which allows to reestablish the initial OCV and to run a further test. The presented results demonstrate as proof of concept the suitability of eco-friendly enzymatic glucose biofuel cells as alternative power source for disposable devices.

International audience; Bioelectrocatalytic carbon nanotube pellets comprising glucose oxidase (GOx) at the anode and horseradish peroxidase (HRP) at the cathode were integrated in a glucose/H2O2 flow-through fuel cell setup. The porous bioelectrodes, separated with a cellulose membrane, were assembled in a design allowing the fuel/electrolyte flow through the entire fuel cell with controlled direction. An air saturated 5 mmol L−1 glucose solution was directed through the anode where glucose is used for power conversion and for the enzymatic generation of hydrogen peroxide supplying the HRP biocathode with its substrate. This configuration showed an open circuit voltage (OCV) of 0.6 V and provided 0.7 ± 0.035 mW at 0.41 V. Furthermore, different charge/discharge cycles at 500 Ω and 3 kΩ were applied to show the long term stability of this setup producing 290 μW h (1.04 J) of energy after 48 h. The biofuel cell design further allows a convenient assembly of several glucose biofuel cells in reduced volumes and its connection in parallel or in series.

Cover letter An autonomous flyback converter was designed for energy harvesting from Microbial Fuel Cells (MFCs). The circuit was optimized to minimize the losses and maximize the efficiency. A Maximum Power Point Tracking (MPPT) algorithm was implanted in the converter to extract the maximum power available from MFC. Discontinuous conduction mode operation of the flyback allows controlling the MPP operation by impedance matching. The flyback can start-up at low voltage, around 300 mV. The output open circuit voltage is about 20 V and the voltage at MPP is 6.4 V with a maximum efficiency of 71.2%. Abstract: Microbial fuel cells (MFCs) use bacteria as the catalysts to oxidize organic matter and generate electricity. This energy can be used to supply low power electronic systems. A power management unit between the MFCs and the load is required to adapt the voltage and control the operation. The low voltage and low power characteristics of MFCs prohibit the use of standard converter topologies since the threshold voltage of standard CMOS transistors in CMOS technology is higher than the output voltage of MFCs. A low-voltage start-up sub-circuit is required to charge a primary capacitor to supply the driver. A specific sub-circuit is also required to control the operation of MFCs for Maximum Power Point Tracking (MPPT) issues. An optimized Discontinuous Conduction Mode (DCM) autonomous flyback converter for energy harvesting is presented for ambient sources, like MFCs. The converter is designed, fabricated, and tested. An MPPT algorithm is integrated in the system to control the operation and to extract the maximum available power from the MFC. The converter is able of start and step-up MFC output voltage to a value higher than 3 V under load. The peak efficiency of the converter is 71.2%.

International audience; Sedimentary microbial fuel cells are promising harvesting systems generating powers as low as 10 μW, which is sufficient for powering underwater environmental sensors. This paper proposes a methodology and modeling to design a flyback converter in discontinuous conduction mode harvesting powers as low as 10th of μWs to maximize the harvested energy and boost its voltage to a minimum value required by sensors. Using a model validated experimentally, we figure out the converter loss contributors and balance them to maximize the power efficiency. We achieved 28% and 75%, efficiency with an input power of 10 μW and 30 μW respectively.

International audience; Bioelectrocatalytic carbon nanotube based pellets comprising redox enzymes were directly integrated in a newly conceived flow-through fuel cell. Porous electrodes and a separating cellulose membrane were housed in a glucose/oxygen biofuel cell design with inlets and outlets allowing the flow of electrolyte through the entire fuel cell. Different flow setups were tested and the optimized single cell setup, exploiting only 5 mmol L-1 glucose, showed an open circuit voltage (OCV) of 0.663 V and provided 1.03 ± 0.05 mW at 0.34 V. Furthermore, different charge/discharge cycles at 500 Ω and 3 kΩ were applied to optimize long-term stability leading to 3.6 J (1 mW h) of produced electrical energy after 48 h. Under continuous discharge at 6 kΩ, about 0.7 mW h could be produced after a 24 h period. The biofuel cell design further allows a convenient assembly of several glucose biofuel cells in reduced volumes and their connection in parallel or in series. The configuration of two biofuel cells connected in series showed an OCV of 1.35 V and provided 1.82 ± 0.09 mW at 0.675 V, and when connected in parallel, showed an OCV of 0.669 V and provided 1.75 ± 0.09 mW at 0.381 V. The presented design is conceived to stack an unlimited amount of biofuel cells to reach the necessary voltage and power for portable electronic devices without the need for step-up converters or energy managing systems.

International audience; — Les piles microbiennes sédimentaires (SMFCs) sont des systèmes récupérant l'énergie directement de la biomasse, ce qui en fait des candidates prometteuses pour l'alimentation autonome de capteurs marins. Au regard des puissances et des tensions générées par les SMFCs (100 µW à 0,3 V pour des électrodes de quelques cm²), une interface de récupération reste indispensable pour à la fois travailler au point de puissance maximum (MPP) de la pile et élever la tension à celle requise par le capteur à alimenter. Dans ce papier nous cherchons à optimiser un convertisseur flyback en mode de conduction discontinue pour une SMFC délivrant une puissance de 90 µW sous 0,3 V. En prenant appui sur d'anciens travaux dans lesquels un modèle du convertisseur avait été validé expérimentalement, nous proposons d'étudier l'influence du rapport cyclique sur les pertes du flyback. Le rendement maximal obtenu est de 68% pour un rapport cyclique de 0,5 en considérant une tension de sortie de 2 V.

Benthic microbial fuel cells (BMFCs) are continuous electricity generators using electroactive microorganisms and organic matter from aquatic environment, respectively, as catalysts and substrate. In this paper, first a low-cost PVC-made structure is constructed to harvest electricity from mangrove environment located in French Guiana. An in situ BMFC has given power density of 30 mW/m2 of the anodic surface area. This performance has been confirmed by experience in laboratory where inter-electrode distance and electrode surface area appeared to be power increasing factors. However, the output power of one BMFC is not used to supply real devices such as autonomous sensors. Second, to meet this expectation, in parallel and in series associations were considered. These associations were made in order to increase the output voltage and consequently the power, to reach levels that can supply small sensors (about 3 V). Finally, to improve the performance of the series association and to avoid the voltage reversal phenomenon, a voltage balancing circuit was simulated and added to the series connections. With balancing method, the cell voltage of BMFCs can be equalized, and the performances can be improved. This allows an optimal energy harvesting and a better global efficiency of the set.

International audience; This energy harvesting solution permits the autonomous supply of low power sensor nodes, without a chemical battery, allowing their extensive use in various environments. The electrical interface between the harvester and the sensor is crucial in order to maximize the harvested energy and boost the voltage to a minimum value required by the sensor. To achieve input impedance and voltage gain independently, this paper presents a flyback converter in discontinuous mode. Using the proposed flyback model validated experimentally, we have studied the impact of each loss source in order to give some trade-off for designing an efficient sub-mW harvesting interface. We underline the effect of the transformer losses due to the magnetic hysteresis as well as the driving loss impact. Following this method, the flyback prototype achieves 71% power efficiency when harvesting from a microbial fuel cell delivering 90µW. Keywords— flyback design method; energy harvesting; DC-DC converter; maximum power point tracking; microbial fuel cell

International audience; Microbial Fuel Cells (MFCs) have been receiving increased interest in the last three decades. MFC can produce electrical energy from a wide variety of organic wastes in wastewater treatment plant concurrently with the treatment process. MFCs are considered as low power, low voltage generator. Scaled-up systems are needed to allow for efficient treatment of large volume of wastewater, but also to be able to produce sufficient electricity. Non-uniformities and hydraulic couplings between stacked MFCs are two problems that can negatively affect the performances. A power management unit is required to step-up the output voltage of the association of few MFCs for suitable supply of low power applications. In this paper, the operation of a serial stack, hydraulically coupled, non-uniform MFCs is studied and optimized to supply low power applications in a wastewater treatment scheme.

International audience; Microbial fuel cells (MFCs) show great promise as a concomitant process for water treatment and as renewable energy sources for environmental sensors. The small energy produced by MFCs and the low output voltage limit the applications of MFCs. Specific converter topologies are required to step-up the output voltage of a MFC. A Power Management Unit (PMU) is proposed for operation at low input voltage and at very low power in a completely autonomous way to capture energy from MFCs with the highest possible efficiency. The application of sensors for monitoring systems in remote locations is an important approach. MFCs could be an alternative energy source in this case. Powering a sensor with MFCs may prove the fact that wastewater may be partly turned into renewable energy for realistic applications. The Power Management Unit is demonstrated for 3.6 V output voltage at 1 mW continuous power, based on a low-cost 0.7-L MFC. A temperature sensor may operate continuously on 2-MFCs in continuous flow mode. A flyback converter under discontinuous conduction mode is also tested to power the sensor. One continuously fed MFC was able to efficiently and continuously power the sensor.

Papier complet disponible sur : http://www.sciencedirect.com/science/journal/09521976; International audience; A pattern recognition technique associated with a new state estimator is developed in order to supervise electrical process. For this purpose, diagnostic features are extracted from current and voltage measurements for monitoring different operating modes. Then, a feature selection method is applied in order to select the most relevant features which define the feature space. In this frame, the classification is realized by a non-parametric method (“k-nearest neighbors” rule) with reject options. However, this method does not take into account the evolution of the operating modes. Thus, it is necessary to enhance the initial knowledge database. For that, a polynomial approach allows characterizing the intermediate states of each operating modes and an original use of Kalman algorithm allows predicting the evolution of the partially known modes. A simple behavioral model is used to describe the evolution of the pattern vector. An estimation step provides the parameter of such model and a prediction step determines the future evolution of the pattern vector.This approach is illustrated on an asynchronous motor of 5.5 kW, in order to detect broken bars under any load level. The experimental results prove the efficiency of pattern recognition methods in condition monitoring of electrical machines.

International audience; This study reports a mixed operational/storage stability of a MWCNT-based glucose biofuel cell (GBFC) over one year. The latter was examined by performing a one hour discharge every day during one month followed by several discharges over a period of 11 months. Under continuous discharge in physiological conditions (5 mM glucose, 37°, pH 7), the GBFC exhibits a 25% power decrease after 1 h of operation. This decrease is mainly due to the deactivation of laccase biocathodes at neutral pH. Nevertheless, the biocathodes can be reversibly reactivated via storage in phosphate buffer (pH 5). Under these conditions, the GBFC finally exhibits 22% of its initial maximum power density after one year at intermittent reactivation/discharge cycles. Although both GBFC electrodes can exhibit one year stability, short-term experiments show that biocathodes are limited by hydroxide inhibition while long-term experiments indicate that bioanodes are likely limited by the stability of the GOx itself. While most of the GBFCs in the literature present stability in the range of several weeks, these results demonstrate the viability of a GBFC for industrial applications in a long period of time.

International audience; Microbial fuel cell (MFC) converts electrochemical energy from organic matter into electricity by means of chemotrophic bacteria metabolisms. The MFC power output is limited in voltage and in current in the range of microwatts or milliwatts per liter. The output power may be improved by association of MFCs either in series or in parallel. The serial association of a large number of MFCs presents a benefit in effective output voltage but may suffer from several limitations. The most important is that the possible dispersion between the microgenerators leads to a nonoptimal stack efficiency. A power management unit is also necessary to harvest energy from a single MFC or a group of connected MFCs. The converter functions are to step up the voltage and to control the operating point of the MFC(s). The aim of this paper is to build an appropriate architecture for energy harvesting from series-connected MFCs, which feature disparate behaviors. A system to meet low-power sensor consumption specifications is composed of a stack of nonuniform serially connected MFCs, a voltage balancing circuit, and a maximum power point converter. The system is designed, fabricated, and tested. A percent of maximum power achieved of 86% is demonstrated for 1.5 mW of harvested power from four MFCs with large dispersion in characteristics.

Cet article présente l'utilisation d'une méthode de reconnaissance des formes pour assurer le suivi et le diagnostic d'un système. Pour l'illustrer, nous avons utilisé comme application, un moteur asynchrone 5,5 kW à cage d'écureuil, notamment pour la détection de barres cassées, en fonction du niveau de charge. A partir de mesures réalisées sur le système, des paramètres sont calculés. Ces paramètres sont utilisés pour construire un vecteur forme qui sera considéré comme la signature du système. Pour déterminer ce vecteur forme, deux méthodes sont appliquées, l'une, assez connue, Sequential Backward Selection (SBS) et l'autre, que nous avons développé, basée sur une approche génétique, présentant l'avantage de choisir la meilleure dimension de l'espace de représentation. L'algorithme de décision est basé sur la règle des k-plus proches voisins, enrichi d'un suivi de l'évolution du système à l'aide de trajectoire permettant alors un diagnostic non seulement des états définis dans l'ensemble d'apprentissage, mais aussi des états intermédiaires. In this paper, a pattern recognition method is used to provide the tracking and the diagnosis of a system. To illustrate it, we used as application, a 5.5 kW squirrel-cage asynchronous motor, in particular for the detection of broken bars, under any level of load. From measurements carried out on the system, parameters are calculated. These parameters are used to build up a pattern vector which is considered as the system signature. To determine this pattern vector, two methods are applied. One, well-known, Sequential Backward Selection (SBS) and the other, which we developed, based on a genetic approach, with the advantage to determine the optimal dimension of the representation space. The decision phase is based on the "k-nearest neighbors" rule, associated with an evolution tracking of system using trajectory allowing a diagnosis not only of states defined in the training set, but also of the intermediate states.

L'invention concerne un dispositif de mesure de courants (3) dans les conducteurs d'un câble gainé d'un réseau polyphasé, comprenant : -au moins trois capteurs magnétiques (300) disposés autour d'un orifice central (312) ; -un dispositif de calcul (330) configuré pour : -accéder à une bibliothèque de matrices [K] et [K] , avec [K] une matrice pseudo-inverse de la matrice [K] ; -former un vecteur [B] incluant une mesure de champ magnétique de chacun desdits capteurs ; -pour différentes configurations de câbles et différentes positions angulaires desdits capteurs par rapport à ces câbles, calculer un vecteur résiduel [R] = [K].[K] .[B] - [B] ; -sélectionner la matrice [K] pour laquelle la norme du vecteur [R] est minimale ; -calculer [I] = [K] .[B] avec [K] ladite matrice sélectionnée.

International audience; The ability to measure, monitor and control energy consumption at several key locations in a manufacturing plant is a major prerequisite for any efficient energy management program. To identify and evaluate energy savings, one must get a clear view of how the energy is used. Furthermore, measuring energy flows is one of the necessary conditions for long lasting energyefficient solutions. Most of the time energy managers are reluctant to put in place power and flow rate measuring devices either because of their cost or because this implies stopping production. To find acceptable and economical solutions for long lasting energy measurements in Industry, EDF R&D launched a 3-year collaborative research project called CHIC. This project is funded by the French National Research Agency (ANR) and involves 7 partners. Its total budget amounts to 2.55 M€. This project serves two purposes: to build a clamp-on power meter that could be installed around multi-conductors power cables without interrupting power supply, and to build power and flow meters that derive the sought-for variable from mathematical models and from simple and easy to collect other physical measurements (e.g. command signals, etc...).

International audience; Microbial Fuel Cells (MFCs) harness the metabolism of micro-organisms to generate electrical energy from organic matter. MFCs offer great promise for simultaneous wastewater treatment and green energy production. The association of a large number of individual MFCs offers very interesting perspectives for electrical energy generation. It can scale-up the low output voltage of an individual cell to enable output voltages to levels acceptable by commercially-available DC/DC converters and it permits to mutualize the electrical powers of each cell. The serial association of a large number of MFCs is a challenge itself for many reasons. Firstly the hydraulic couplings (when MFCs share the same substrate) witch cause leakage of electrical-charge careers between the connected reactors. Secondly the non-uniformities between generators which lead to a non-optimal energy recovery because the associated cells do not able to operate at Maximum Power Point (MPP). Non-uniformities can be compensated with electronic circuits to prevent voltage reversal or enable voltage equalizing. In this paper a balancing method is studied and adapted for energy harvesting from a stack of serially connected MFCs. The balancing circuit was simulated, realized and tested for energy harvesting. With balancing method the cell voltage of MFCs in a stack can be equalized and the performance of MFCs can be improved and it leads to an optimal energy recovery of the stack.

The invention relates to a device for measuring currents (3) in the conductors of a sheathed cable of a polyphase network, comprising at least three magnetic sensors (300) arranged around a central hole (312) through which the cable to be measured is intended to pass, the number of conductors in said cable being less than the number of sensors, and a calculation device (330) configured to: access a library of matrices [K] and [K]+, where [K]+ is a pseudo-inverse matrix of matrix [K]; form a vector [B] including a magnetic field measurement for each of the sensors; for various cable configurations and various angular positions of the sensors relative to the cables, calculate a residual vector [R] = [K].[K]+.[B] - [B]; select the matrix [K]+ for which the norm of the vector [R] is minimal; and calculate [1] = [K]+.[B], where [K]+ is the selected matrix.

International audience; Biofuel cells use catalysts (chemical, enzymatic or microbial) to convert chemical energy from organic substrates into electrical energy. This paper investigates energy harvesting from several low-power biofuel cells to power a load under several volts. As biofuel cells can share the same fuel source, an isolation is required to aggregate energy towards high voltages (compared to a cell voltage). The proposed converter is based on the well known flyback topology. The efficiency of the flyback converter is about 60% for an input power of 10mW. The PCB area is 29 cm2 compared to around 74 cm2 for a previously built boost converter. The topology of the flyback converter includes a control circuit which allows a regulation of the input voltage to keep it around the maximum power point (MPP at around 0.3 V). This control circuit is powered internally through an auxiliary sub-circuit.

International audience; This paper deals with a diagnosis tool based on a pattern recognition approach associated with Kalman interpolator/extrapolator. The first aim is to decrease the number of measurements to realize while increasing the learning database contents using a Kalman state estimator. The second one is to estimate, from the initial set of measured data, future states of the studied process. A 5.5-kW induction motor bench is used as an application to validate this approach. First, a signature is determined in order to monitor the different operating modes evolution. Diagnostic features are extracted only from current and voltage sensors. Then, a feature selection method is applied in order to select the most relevant features for diagnosis. Finally, a Kalman filter algorithm is developed in order to interpolate the known states and to predict evolution toward new ones. A new diagnosis tool is then designed handling continuous evolution (severity, load) inside the different operating modes (healthy, stator fault, ...).

Electric drives condition monitoring is essential to optimize maintenance operations and to increase reliability levels. This paper presents a diagnosis method for electrical faults detection. Firstly some signatures representing induction motor thermal heating are developed. Indeed a motor provides normal losses (mechanical, electrical, magnetic, etc.) as well as additional losses due to some faults. Losses involve an operating temperature increase, which can be particularly damaging for insulation. Eventually this can bring partial or total destruction of this insulation and create a short circuit between turns. From a thermal modelling of induction motor, with a simplified model, the heating can be computed and used as faults signatures. Secondly in order to realize automatic diagnosis, theses signatures are associated with a pattern recognition approach. The aim is to detect faults appearing on the system and to define their severity level by reference to an initial data base. In order to prove reliability and efficiency, experimental results will be presented using an induction motor 5.5kW.

International audience; Cet article présente le principe de fonctionnement d'un capteur virtuel permettant la mesure de courants dans un système polyphasé. Une méthode numérique est utilisée pour la réjection des perturbations extérieures pouvant être émises par d'autres conducteurs à proximité de l'environnement de mesure.

International audience; Presently, condition monitoring and fault diagnostics in electric drives are essential to optimize maintenance operations and increase reliability levels. This paper presents a diagnosis method for electrical and mechanical faults detection. This method combines a detection method based on expertise with a pattern recognition approach so as to detect different faults appearing on the system but also to classify their origins and their severity by reference to an initial data base. In order to prove reliability and efficiency of this method, experimental results are presented using a permanent magnet synchronous motor (PMSM) drive.

International audience; In the last decade, the field of diagnosis has attracted the attention of many researchers, especially for the diagnosis of induction motors. This type of machine is widely used in industry because of its robustness and its specific power. Therefore, the monitoring and diagnosis of these motors become very important. This paper deals with the diagnosis of induction motor faults. The method is based on ant-clustering and it is improved by K-means pattern recognition and Principal Components Analysis (PCA). This approach is applied to the diagnosis of a squirrel-cage induction motor of 5.5kW with broken bars and bearing faults in order to check the detection capability. The obtained results prove the efficiency of this approach

Nos remerciements à IEEE pour l'autorisation de mise à disposition du papier complet. © IEEE Copyright Notice : Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.; International audience; Nowadays, electrical drives generally associate inverter and induction machine. Thus, these two elements must be taken into account in order to provide a relevant diagnosis of these electrical systems. In this context, the paper presents a diagnosis method based on a multidimensional function and pattern recognition (PR). Traditional formalism of the PR method has been extended with some improvements such as the automatic choice of the feature space dimension or a "nonexclusive" decision rule based on the k-nearest neighbors. Thus, we introduce a new membership function, which takes into account the number of nearest neighbors as well as the distance from these neighbors with the sample to be classified. This approach is illustrated on a 5.5 kW inverter-fed asynchronous motor, in order to detect supply and motor faults. In this application, diagnostic features are only extracted from electrical measurements. Experimental results prove the efficiency of our diagnosis method.

International audience; This paper deals with the use of pattern recognition method in order to provide thetracking and the diagnosis of an electrical system. From the measurements carried out onthe system, some parameters are calculated. These ones are used to build up the systemsignature. As the set of parameters is not necessarily relevant, a selection method based on acompacity/separability criterion is used. The determination of the decision space is carriedout by using an automatic classification method named clustering. Two decision methodsare used and compared: the “k-nearest neighbors” rule (k-ppv), easy to implement butpenalizing in term of computing time. The other method that we developed is based on aprogressive grid of the representation space. The appearance of a new operating mode istaken into account in order to enrich the initial knowledge base and thus to improve thediagnosis. To illustrate this method, we used as an application, an asynchronous motor 5.5kW with squirrel-cage supplied with a voltage converter for the detection of rotor and statorfaults.; Cet article présente le suivi et le diagnostic d’un système réalisé à partir d’uneméthode de reconnaissance des formes. A partir des mesures effectuées sur le système, desparamètres sont calculés. Ces derniers sont utilisés pour construire la signature du système.L’ensemble des paramètres n’étant pas nécessairement pertinent, une méthode de sélectionbasée sur un critère de compacité/séparabilité est utilisée. La détermination de l’espace dedécision est réalisée de manière automatique à l’aide d’une méthode appelée« coalescence ». Deux méthodes de décision sont utilisées et comparées : la règle des casplus proches voisins (k-ppv), facile à mettre en œuvre mais pénalisante en terme de temps decalcul, l’autre que nous avons développé et qui s’appuie sur un maillage progressif del’espace de représentation. L’apparition d’un nouveau mode de fonctionnement est pris encompte afin d’enrichir la base de connaissance initiale et d’améliorer ainsi le diagnostic.Pour illustrer cette méthode, nous avons utilisé comme application, un moteur asynchrone5.5 kW à cage d’écureuil alimenté par un onduleur de tension pour la détection des défautsaussi bien au rotor qu’au stator.

International audience; ntensive research efforts have been focused on the signature analysis (SA) to detect electrical and mechanical fault condition of induction machines. Different signals can be used: voltage, current and flux. The characteristic frequency research by a current spectral analysis is a well-known method widely used. This method is valid when the motor is supplied by the three-phase main network. However nowadays, in industrials applications, the asynchronous motors are more and more supplied by converters, in particular for variable speed. The current spectral analysis is almost not exploitable because of appearance of multiple harmonics of the commutation frequency. This paper presents a diagnosis method applied to a set "converter-machine-load". This method is based on pattern recognition approach. The use of the data standardization makes it possible to free from the level of load and thus to represent an operating mode by only one class. This fact allows decreasing the number of initial data necessary to the training phase and improving the final diagnosis

International audience; In this paper, a pattern recognition (PR) method is used to provide the tracking and the diagnosis of a system. First of all, from measurements carried out on the system, features are extracted from current and voltage measurements without any other sensors. These features are used to build up a pattern vector, which is considered as the system signature. Then, a feature selection method is applied in order to select the most relevant features, which define the representation space. The decision phase is based on the "k-nearest neighbors" (knn) rule, associated with an evolution tracking of system using trajectory allowing a diagnosis not only of states defined in the training set, but also of the intermediate states. The appearance of a new operating mode is taken into account in order to enrich the initial knowledge base and thus to improve the diagnosis. This approach is illustrated on asynchronous motor of 5.5 kW with squirrel cage, in order to detect broken bars under any load level. The experimental results prove the efficiency of PR methods in condition monitoring of electrical machines.

International audience; This paper deals with pattern recognition (PR) method associated with a tracking and a prediction of evolution for various operating modes of a process. The aim is to improve diagnosis of a process by enhancing its knowledge database. Indeed, PR needs an initial database named training set. It is composed of different operating modes and obtained during the first step of PR. It is commonly named training phase. It is a laborious step and moreover the whole of operating modes is never available (generally poor experimental feedback). Thatpsilas why, using knowledge in training set, it is interesting to predict evolution of operating modes in unknown fields of representation space. PR steps are first presented and followed by a polynomial approach of tracking evolution. Next, a Kalman algorithm is used to predict evolution and finally two different asynchronous machines (5.5 kW and 18.5 kW) are used to illustrate our purpose.

International audience; In this paper, a pattern recognition method is used to provide the tracking and the diagnosis of a system. To illustrate it, we used as application, an asynchronous motor 5.5 kW with squirrel-cage, in particular for the detection of broken bars, under any level of load. From measurements carried out on the system, parameters are calculated. These parameters are used to build up a pattern vector which is considered as the system signature. To determine this pattern vector, two methods are applied. One, well-known, sequential backward selection (SBS) and the other, which we developed, based on a genetic approach, with the advantage to determine the optimal dimension of the representation space and to give better results (value of criterion) than SBS. The determination of the decision space is carried out using a method of automatic classification called clustering. The decision phase is based on the ldquok-nearest neighborsrdquo rule, associated with an evolution tracking of system using trajectory allowing a diagnosis not only of states defined in the training set, but also of the intermediate states. The appearance of a new operating mode is taken into account in order to enrich the initial knowledge base and thus to improve the diagnosis

Electrolytic filter capacitors are frequently responsible for static converters breakdowns. The rise of temperature within capacitor is the most significant factor upon ageing and so lifespan. To predict the ageing of the capacitor, a method of predictive maintenance has been developed. It consists in monitoring the voltage ripple of the capacitor. This ripple is the best indicator of its worn state. It is function of parameters such as input voltage, output current and ambient temperature. A reference system taking into account all these parameters is determined for sound capacitors. We deducted that the dispersion of input voltage had a weak influence upon voltage ripple compared to other parameters such as output current and ambient temperature. And precisely the temperature is being an influent parameter in the diagnosis, measurement must be very relevant. That is why we measured the internal temperature of capacitor which takes into account the ambient temperature but also the internal heating of capacitor. This measurement is done in an environment not confined for not which is distorted. We then checked the relevance of our modifications by comparing our results with the actual values of the state of capacitors deduced using a bridge RLC.

International audience; Intensive research efforts have been focused on the signature analysis (SA) to detect electrical and mechanical fault condition of induction machines. Different signals can be used: voltage, current, flux and power. This paper is a comparative analysis of two different diagnosis methods that are used to detect and localize failures in induction motors. The first one is based on leakage flux measurement and the second one is a diagnosis method based on current, electrical power measurement and pattern recognition. A synthesis of two methods will be developed. It mainly concerns rotor faults.

URL = http://www.epjap.org/article_S1286004213304364; International audience; Accurate monitoring of energy consumption is key for electrical energy management in industry This implies the use of low-cost and easy-to-install measuring chains that can be placed directly around three-phase cables without interrupting power delivery. This paper describes an innovative current measurement method using a magnetic sensor array dispatched around three-conductor cables. Analytical solution is given for the measurement problem and results from simulations.

This thesis presents the study and realization of an innovative currents sensor prototype for multi-Core cables. The two main advantages of this sensor compared to existing devices on the electrical equipment market are: firstly, it is no longer necessary to interrupt the system's electrical power supply to install the sensor. This is due to contactless measure (non-Intrusive sensor). Another feature of our device is its capability to measure the currents in a multi-Core system with unknown positions of conductors. This currents sensor operates in a way to find firstly the conductor positions, and then reconstructing the currents using the retrieved positions. In order to meet specifications, simulation results, test bench measurements and experimental results are presented with a ferromagnetic shielding, Cette thèse porte sur l'étude et la réalisation d’un prototype de capteur de courants innovant pour câbles multiconducteurs. Outre le caractère non-Intrusif de ce capteur (i.e. mesure sans contact), il permet de réaliser une mesure sur un système polyphasé dont la position des conducteurs est inconnue. L’approche adoptée est basée sur la résolution d’un problème inverse. En effet, à partir d’une mesure de la signature des champs magnétiques autour du câble, des algorithmes de reconstruction appropriés permettent de remonter aux courants circulant dans le câble. En plus des résultats de simulation, un banc de tests a été conçu et une validation expérimentale de ce concept est présentée pour répondre à un cahier des charges, notamment pour une structure comportant un blindage en matériau ferromagnétique pour atténuer les perturbations extérieures