PRE ETUDE D'UN GENERATEUR PENDULAIRE IN VIVO POUR IMPLANTS ORTHOPEDIQUES

Cet article présente le principe et le potentiel énergétique d'un générateur électromagnétique, in vivo, non invasif, utilisant les mouvements naturels du corps humain lors de la marche, dans le but de créer une source autonome qui pourra servir à terme de prothèse intelligente. Dans un premier temps, nous décrivons le principe du système. Ensuite, les couplages entre les phénomènes humains, mécaniques et électriques étant très importants, une étude mécanique et électrique est conduite pour déterminer un ordre de grandeur de la puissance récupérable

Preliminary Study of a Pendulum in Vivo Electromechanical Generator for Orthopedic Implants

This paper presents the principle and the energy potential of an original electromechanical generator that uses human body natural motions during walking, in order to create an autonomous generator. This in vivo and noninvasive system is intended to be used in intelligent knee prosthesis. As the combined human, mechanical, and electrical phenomena are very significant, a mechanical and an electrical study are then carried to evaluate the recoverable power

Génération d'électricité dans les implants orthopédiques à partir des mouvements naturels du corps humain - Capacité d'un générateur pendulaire

International audienceCet article présente le principe et le potentiel énergétique d'un générateur électromagnétique, in-vivo, non invasif, utilisant les mouvements naturels du corps humain lors de la marche, dans le but de créer une source autonome qui pourra servir à terme pour des prothèses intelligentes. Dans un premier temps, nous décrivons le principe du système. Ensuite, les couplages entre les phénomènes humains, mécaniques et électriques étant très importants, une étude mécanique et électrique est conduite pour déterminer un ordre de grandeur de la puissance récupérable

Study of a Pendulum in Vivo Electromechanical Generator to be Used in a Knee Prosthesis

International audienceThis paper presents the principle and the energy potential of an original electromechanical generator that uses human body natural motions during walking, in order to create an autonomous generator. This in vivo and noninvasive system is intended to be used in intelligent knee prosthesis. As the combined human, mechanical, and electrical phenomena are very significant, a mechanical and an electrical study are then carried to evaluate the recoverable power

Diagnosis of Three-Phase Electrical Machines Using Multidimensional Demodulation Techniques

International audienceThis paper deals with the diagnosis of three-phase electrical machines and focuses on failures that lead to stator- current modulation. To detect a failure, we propose a new method based on stator-current demodulation. By exploiting the configuration of three-phase machines, we demonstrate that the demodulation can be efficiently performed with low-complexity multidimensional transforms such as the Concordia transform (CT) or the principal component analysis (PCA). From a practical point of view, we also prove that PCA-based demodulation is more attractive than CT. After demodulation, we propose two statistical criteria aiming at measuring the failure severity from the demodulated signals. Simulations and experimental results highlight the good performance of the proposed approach for condition monitoring

Performance Analysis of an EEMD-based Hilbert Huang Transform as a Bearing Failure Detector in Wind Turbines

International audienceSustainability and viability of wind farms are highly dependent on the reduction of the operational and maintenance costs. The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the degeneration of the generator health, facilitating a proactive response, minimizing downtime, and maximizing productivity. This paper deals then with the assessment of a demodulation technique for bearing failure detection through wind turbines generator stator current. The proposed technique is based on a modified version of the Hilbert Huang transform. In this version, the use of the EEMD algorithm allows overcoming the well-known mixed mode

An Ensemble Empirical Mode Decomposition Approach for Voltage Sag Detection in a Smart Grid Context

International audienceSmart grids have become a focal point in renewable energy source researches. Sustainability and viability of distributed grids are highly dependent on the reduction of the operational and maintenance costs. The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the power quality degeneration, and facilitating a proactive response, prevent a fault ride-through the renewable energy conversion system, minimizing downtime, and maximizing productivity. This paper provides then the assessments of an advanced signal processing technique, namely the ensemble empirical mode decomposition, using the instantaneous power for voltage sags detection in smart grids

Smart Grid Voltage Sag Detection using Instantaneous Features Extraction

International audienceSmart grids have initiated a radical reappraisal of distribution networks function where the integration of renewable energy sources, load demand control, and effective use of the network are indexed as the most important keys for smart grid expansion and deployment regardless each country policies. One of the most efficient ways of effective use of these grids would be to continuously monitor their conditions. This allows for early detection of power quality degeneration facilitating therefore a proactive response, prevent a fault ride-through the renewable power sources, minimizing downtime, and maximizing productivity. In this smart grid context, this paper proposes the evaluation and comparison of advanced signal processing tools, namely the Hilbert transform and the ensemble empirical mode decomposition method for the detection of voltage sags as they are the most commonly encountered power quality disturbances

Hilbert Transform-Based Bearing Failure Detection in DFIG-Based Wind Turbines

International audienceCost-effective, predictive and proactive maintenance of wind turbines assumes more importance with the increasing number of installed wind farms in more remote location (offshore). A well-known method for assessing impeding problems is to use current sensors installed within the wind turbine generator. This paper describes then an approach based on the generator stator current data collection and attempts to highlight the use of the Hilbert transform for failure detection in a doubly-fed induction generator-based. Indeed, this generator is commonly used in modern variable-speed wind turbines. The proposed failure detection technique has been validated experimentally regarding bearing failures. Indeed, a large fraction of wind turbine downtime is due to bearing failures, particularly in the generator and gearbox

Design of an electro-mechanical portable system using natural human body movements for electricity generation

International audienceIn this article, the authors present the energy potential associated with an electromechanical resonant generator that uses natural movements of the human body during walking motion, as a means of increasing the autonomy of portable electronic systems. The article begins by characterizing the human walk in terms of frequency and hip displacement amplitude. A combined mechanical and electrical study is then conducted in order to determine an order of magnitude for recoverable power