Le système d’entraînement rotatif comporte : - une source de tension continue (102) ; - un moteur électrique (104) présentant un axe de rotation (A), et comportant des phases indépendantes (a, b, c) présentant des directions autour de
5 l’axe de rotation (A) ;
- un onduleur (106) destiné à connecter chaque phase (a, b, c) à la source de tension continue (102) ; et
- un dispositif de commande (110) destiné à fournir une commande à l’onduleur (106).
Le dispositif de commande (110) comporte :
- des moyens (118) de sélection de 10 formule, destinés à sélectionner une formule parmi des formules prédéterminées, chaque formule prédéterminée étant destinée à calculer soit une consigne de tension homopolaire, soit une consigne de courant homopolaire ;
- des moyens (124) de détermination de consigne, destinés à appliquer la formule sélectionnée pour déterminer, suivant la formule sélectionnée, soit une consigne de tension homopolaire,
15 soit une consigne de courant homopolaire, et - des moyens (126) de détermination de
commande, destinés à déterminer la commande de l’onduleur (106) à partir de la consigne déterminée.; Projet SOFRACI/FUI
L’amélioration de la disponibilité et de la fiabilité des éoliennes offshores et des systèmes de récupération de l’énergie des courants marins implique la nécessité de minimiser et de prévoir les opérations de maintenance. En fonctionnement à vitesse
variable ou en régime transitoire, des techniques de traitement du signal avancées sont requises pour réaliser la détection et le diagnostic des défaillances à partir des courants statoriques. Dans ce contexte, plusieurs études récentes ont proposées l’utilisation de techniques temps-fréquence et temps-échelle pour le diagnostic. Les techniques les plus utilisées sont : Le spectrogramme, la transformée en ondelettes, la représentation de Wigner-Ville et la transformée de Hilbert-Huang. Cet article propose alors une étude comparative et une analyse de ces techniques pour la détection des défauts qui surviennent dans une génératrice asynchrone connectée à un réseau triphasé fonctionnant en régime nominal.; Ce travail est soutenu par Brest Métropole Océan (BMO).
Nous tenons à remercier le Groupe d’Etudes Sous-Marine de l’Atlantique (GESMA) pour sa collaboration lors de la campagne de mesures et son expertise.; Dans un contexte de protection portuaire, l’un des enjeux consiste à détecter des cibles potentielles au-dessus ou sous la surface (plongeurs, AUV…). Parmi les dispositifs de détection existants, l’approche acoustique passive présente l’avantage d’être discrète pour un faible coût de mise en œuvre. Le signal recherché se trouve souvent noyé dans un environnement bruité et il convient alors d’avoir des connaissances a priori de la signature acoustique de la cible pour être capable de la détecter. L’objet de cette étude est d’adapter la méthode DEMON sur des signaux obtenus en mer en conditions réelles. Cette technique est basée sur la détection d’enveloppe après filtrage du signal dans une bande de fréquences caractéristiques de l’objet d’intérêt. Le rapport signal sur bruit s’en trouve alors amélioré, ce qui facilite l’extraction de paramètres caractéristiques de la cible. La méthode a été appliquée sur deux types de signaux : des enregistrements issus de plongeurs d’une part et de bruits de navire d’autre part. Dans le cas des plongeurs...
In this paper a signal analysis framework for estimating time-varying amplitude and frequency functions of multicomponent amplitude and frequency modulated (AM–FM) signals is introduced. This framework is based on local and non-linear approaches, namely Energy Separation Algorithm (ESA) and Empirical Mode Decomposition (EMD). Conjunction of Discrete ESA (DESA) and EMD is called EMD–DESA. A new modified version of EMD where smoothing instead of an interpolation to construct the upper and lower envelopes of the signal is introduced. Since extracted IMFs are represented in terms of B-spline (BS) expansions, a closed formula of ESA robust against noise is used. Instantaneous Frequency (IF) and Instantaneous Amplitude (IA) estimates of a multi- component AM–FM signal, corrupted with additive white Gaussian noise of varying SNRs, are analyzed and results compared to ESA, DESA and Hilbert transform-based algorithms. SNR and MSE are used as figures of merit. Regularized BS version of EMD– ESA performs reasonably better in separating IA and IF components compared to the other methods from low to high SNR. Overall, obtained results illustrate the effective- ness of the proposed approach in terms of accuracy and robustness against noise to track IF and IA features of a multicomponent AM–FM signal.
In this paper we consider the hermitian extension of the cross-Psi_B-energy operator that we will denote by Psi_H. In addition, cross energy terms are formalized through multivariate signals representation. We investigate the connection between the interaction energy function of Psi_H and the cross-power spectral density (CPSD)of two complex valued signals. In particular, this link permits to use this operator for estimating the CPSD. We illustrate the interest of Psi_H as a similarity between a pair of signals in frequency domain on synthetic and real data.
This work aims at introducing some energy operators linked to Teager-Kaiser energy operator and its associated higher order versions and expand them to multidimensional signals. These operators are very useful for analyzing oscillatory signals with time-varying amplitude and frequency (AM-FM). We prove that gradient tensors combined with Kronecker powers allow to express these operators by directional derivatives along any n-D vector. In particular, we show that the construction of a large class of non linear operators for AM-FM multidimensional signal demodulation is possible. Also, a new scalar function using the directional derivative along a vector giving the ”sign” of the frequency components is introduced. An application of this model to local n-D AM-FM signal is presented and related demodulation error rates estimates. To show the effectiveness and the robustness of our method in term of envelope and frequency components extraction, results obtained on synthetic and real data are compared to multi-dimensional energy separation algorithm and to our recently introduced n-D operator.
In this letter a new signals coding framework based on the Empirical Mode Decomposition (EMD) is introduced. The EMD breaks down any signal into a reduced number of oscillating components called Intrinsic Modes Decomposition (IMFs). Based on IMF properties, different coding strategies are presented. No assumptions concerning the linearity or the stationarity are made about the signal to be coded. Results obtained on ECG signals are presented and compared to those of wavelets coding.
This paper explains the effect of a motion platform for driving simulators on postural instability and head vibration exposure. The sensed head level-vehicle (visual cues) level longitudinal and lateral accelerations (ax,sensed = ax_head and ay,sensed = ay_head, ayv = ay_veh and ayv = ay_veh) were saved by using a motion tracking sensor and a simulation software respectively. Then, associated vibration dose values (VDVs) were computed at head level during the driving sessions. Furthermore, the postural instabilities of the participants were measured as longitudinal and lateral subject body centre of pressure (XCP and YCP, respectively) displacements just after each driving session via a balance platform. The results revealed that the optic-head inertial level longitudinal accelerations indicated a negative non-significant correlation (r = −.203, p = .154 > .05) for the static case, whereas the optic-head inertial longitudinal accelerations depicted a so small negative non-significant correlation (r = −.066, p = .643 > .05) that can be negligible for the dynamic condition. The XCP for the dynamic case indicated a significant higher value than the static situation (t(47), p < .0001). The VDVx for the dynamic case yielded a significant higher value than the static situation (U(47)...
Structural damages can result in nonlinear dynamical signatures that can significantly enhance their detection. An original nonlinear damage detection approach is proposed that is based on a cascade of Hammerstein models representation of the structure. This model is estimated by means of the Exponential Sine Sweep Method from only one measurement. On the basis of this estimated model, the linear and nonlinear parts of the output are estimated, and two damage indexes (DIs) are proposed. The first DI is built as the ratio of the energy contained in the nonlinear part of an output versus the energy contained in its linear part. The second DI is the angle between the subspaces obtained from the nonlinear parts of two set of outputs after a principal component analysis. The sensitivity of the proposed DIs to the presence of damages as well as their robustness to noise are assessed numerically on spring-mass-damper structures and experimentally on actual composite plates with surface-mounted PZT-elements. Results demonstrate the effectiveness of the proposed method to detect a damage in nonlinear structures and in the presence of noise.
This paper proposes an accurate sensor fusion scheme for navigation inside a real-scale 3D model by combining audio and video signals. Audio signal of a microphone-array is merged by Minimum Variance Distortion-less Response (MVDR) algorithm and processed instantaneously via Hidden Markov Model (HMM) to generate translation commands by word-to-action module of speech processing system. Then, the output of optical head tracker (four IR cameras) is analyzed by non-linear/non-Gaussian Bayesian algorithm to provide information about the orientation of the user's head. The orientation is used to redirect the user toward a new direction by applying quaternion rotation. The output of these two sensors (video and audio) is combined under the sensor fusion scheme to perform continuous travelling inside the model. The maximum precision for the traveling task is achieved under sensor fusion scheme. Practical experiment shows promising results for the implementation.
In the course of most wood machining processes, operators are usually able to detect various problems simply by hearing the sound emitted
by the process. This is especially true for wood peeling. Lathe checks formation has been identified as one of the typical situations that an experimented
peeler can detect. Poplar and beech veneer samples have been produced on a laboratory microlathe, using working conditions deliberately favourable
to checking. Forces, sound, and vibration levels were measured during the tests. The lathe check frequencies have been determined on both sound
and vibration signals using a local Root Mean Square (RMS) averaging and a peak detection algorithm. This makes possible the evaluation of lathe
checks distribution along the veneer length. The technique was validated by measuring the real veneer profile using a specific apparatus developed by
IVALSA-CNR in Trento (Italy).; The veneer characterization was realized during a short term scientific mission supported by the COST Action E35.
Experienced peeling operators are able to adjust the settings of their device by hearing the sound coming from the process. Based on this idea, a research program was undertaken to evaluate the possibility of using acoustic or vibration measurements supplying a support decision system to assist untrained operators.
The present paper deals with lathe check phenomenon which is one of the most critical defects of veneer (leading to handling difficulties, excess of glue consumption, poor veneer surface quality, etc.). Several signal processing techniques giving a spectral representation of sensors measurements are compared. Finally, an original procedure based on Power Spectral Density ratio is proposed to measure the average lathe check frequency of the veneer during the process.
In the automotive repairing backdrop, retrieving from previously solved incident the database features that could support and speed up the diagnostic is of great
usefulness. This decision helping process should give a fixed number of the more relevant diagnostic classified in a likelihood sense. It is a probabilistic multi-class classification problem. This paper describes an original classification technique, the Probabilistic Decision Tree (PDT) producing a posteriori probabilities in a multi-class context. It is based on a Binary Decision Tree (BDT) with Probabilistic Support Vector
Machine classifier (PSVM). At each node of the tree, a bi-class SVM along with a sigmoid function are trained to give a probabilistic classification output. For each branch, the outputs of all the nodes composing the branch are combined to lead to a
complete evaluation of the probability when reaching the final leaf (representing the class associated to the branch). To illustrate the effectiveness of PDTs, they are tested on benchmark datasets and results are compared with other existing approaches.; This research has been sponsored by PSA.
This paper aims to propose and evaluate a markerless solution for capturing hand movements in real time to allow 3D interactions in virtual environments (VEs). Tools such as keyboard and mice are not enough for interacting in 3D VE; current motion capture systems are expensive and require wearing equipment. We developed a solution to allow more natural interactions with objects and VE for navigation and manipulation tasks. We conducted an experimental study involving 20 participants. The goal was to realize object manipulation (moving, orientation, scaling) and navigation tasks in VE. We compared our solution (Microsoft Kinect-based) with data gloves and magnetic sensors (3DGloves) regarding two criteria: performance and acceptability. Results demonstrate similar performance (precision, execution time) but a better overall acceptability for our solution. Preferences of participants are mostly in favor of the 3DCam, mainly for the criteria of comfort, freedom of movement, and handiness. Our solution can be considered as a real alternative to conventional systems for object manipulation in virtual reality.
This paper aims to show to what extent the Web3D is an advantage for implementing the Living Lab approach. In order to achieve this objective, we develop a project the context of an Action-Research. A state-of-the-art of Web3D solutions for e-commerce enabled us to select the most suitable functionalities and properties for designing a 3D gates configurator for consumers. A panel of Twenty-seven participants evaluated this tool. Results show that an interactive 3-dimensional visualization of the object is an advantage for the sale, because a single image does not usually allow user to imagine the product in its future environment. The use of Web3D for e-commerce enables consumers to be involved in the design process for co-creating solutions, which is one of the main aspects of the Living Lab approach.
Health Monitoring is the science of system health status evaluation. In the modern industrial world, it is getting more and more importance because it is a powerful tool to increase systems dependability. It is based on the observation of some variables extracted in operation reflecting the condition of a system. The quality of health monitoring strongly depends on the selection of these variables named health indicators. However, the issue in their selection is often underestimated and their validation is, of what is known, an untreated subject. In this paper, the authors introduce a complete methodology for the selection and validation of health indicators in health monitoring systems design. Although it can be applied either downstream on real measured data or upstream on simulated data, the true interest of the method is in the latter application. Indeed, a model-based validation can be integrated in the design phases of the system development process, thereby reducing potential controller retrofit costs and useless data storage. In order to simulate the distribution of health indicators, a well known surrogate model called Kriging is utilized. Eventually, the method is tested on a benchmark system: the high pressure pump of aircraft engines fuel systems. Thanks to the method...
The empirical mode decomposition is a powerful tool for signal processing. Because of its original algorithmic, recent works have contributed to its theoretical framework. Following these works, some mathematical contributions on its comprehension and formalism are provided. In this paper, the so called local mean is computed in such a way that it allows the use of differential calculus on envelopes. This new formulation makes us prove that iterations of the sifting process are well approximated by the resolution of partial differential equations (PDE). Intrinsic mode functions are originally defined in a intuitive way. Herein, a mathematical characterization of modes is given with the proposed PDE based approach.
The mechanical properties of the rib cortical bone are extremely rare on children due to difficulties to obtain specimens to perform conventional tests. Some recent studies used cadaveric bones or bone tissues collected during surgery but are limited by the number of samples that could be collected. A non-invasive technique could be extremely valuable to overcome this limitation. It has been shown that a relationship exists between the mechanical properties (apparent Young’s modulus and ultimate strength) and the bone mineral density (assessed using Quantitative Computed Tomography, QCT), for the femur and recently by our group for the adult ribs ex vivo. Thus the aim of this study was to assess the mechanical properties of the child rib cortical bone using both QCT images in vivo and the previous relationship between bone mineral density and mechanical properties of the rib cortical bone.
Twenty-eight children were included in this study. Seven age-groups have been considered (1, 1.5, 3, 6, 10, 15, 18 years old). The QCT images were prescribed for various thoracic pathologies at the pediatric hospital in Lyon. A calibration phantom was added to the clinical protocol without any modifications for the patient. The protocol was approved by the ethical committee. A 3D reconstruction of each thorax was performed using the QCT images. A custom software was then used to obtain cross-sections to the rib midline. The mean bone mineral density was then computed by averaging the Hounsfield Units in a specific cross-section and by converting the mean value (Hounsfield Units) in bone mineral density using the calibration phantom. This bone mineral density was assessed for the 6th rib of each subject. Our relationship between the bone mineral density and the mechanical properties of the rib cortical bone was used to derive the mechanical properties of the child ribs in vivo.
The results give values for the apparent Young’s modulus and the ultimate strength. The mechanical properties increase along growth. As an example the apparent Young’s modulus in the lateral region ranges from 7 GPa +/-3 at 1 year old up to 13 GPa +/- 2 at 18 years old. These data are in agreement with the few previous values obtained from child tissues.
This methodology opens the way to in vivo measurement of the mechanical properties of the child cortical bone based on calibrated QCT images.
This paper deals with driving simulation and in particular with the important issue of motion sickness. The paper proposes a methodology to evaluate the objective illness rating metrics deduced from the motion sickness dose value and questionnaires for both a static simulator and a dynamic simulator. Accelerations of the vestibular cues (head movements) of the subjects were recorded with and without motion platform activation. In order to compare user experiences in both cases, the head-dynamics-related illness ratings were computed from the obtained accelerations and the motion sickness dose values. For the subjective analysis, the principal component analysis method was used to determine the conflict between the subjective assessment in the static condition and that in the dynamic condition. The principal component analysis method used for the subjective evaluation showed a consistent difference between the answers given in the sickness questionnaire for the static platform case from those for the dynamic platform case. The two-tailed Mann–Whitney U test shows the significance in the differences between the self-reports to the individual questions. According to the two-tailed Mann–Whitney U test, experiencing nausea (p = 0.019 < 0.05) and dizziness (p = 0.018 < 0.05) decreased significantly from the static case to the dynamic case. Also...
This article proposes a method based on wavelet transform and neural networks for relating pupillary behavior to psychological stress. The proposed method was tested by recording pupil diameter and electrodermal activity during a simulated driving task. Self-report measures were also collected. Participants performed a baseline run with the driving task only, followed by three stress runs where they were required to perform the driving task along with sound alerts, the presence of two human evaluators, and both. Self-reports and pupil diameter successfully indexed stress manipulation, and signiﬁcant correlations were found between these measures. However, electrodermal activity did not vary accordingly. After training, the four-way parallel neural network classiﬁer could guess whether a given unknown pupil diameter signal came from one of the four experimental trials with 79.2% precision. The present study shows that pupil diameter signal has good discriminating power for stress detection.