Acoustic Simulation of a Special Switched Reluctance Drive by Means of Field-Circuit Coupling and Multiphysics Simulation

The approach presented in this paper consists of an energy-based field-circuit coupling in combination with multi-physics simulation of the acoustic radiation of electrical machines. The proposed method is applied to a special switched reluctance motor with asymmetric pole geometry to improve the start-up torque. The pole shape has been optimized, subject to low torque ripple, in a previous study. The proposed approach here is used to analyze the impact of the optimization on the overall acoustic behavior. The field-circuit coupling is based on a temporary lumped-parameter model of the magnetic part incorporated into a circuit simulation based on the modified nodal analysis. The harmonic force excitation is calculated by means of stress tensor computation, and it is transformed to a mechanical mesh by mapping techniques. The structural dynamic problem is solved in the frequency domain using a finite-element modal analysis and superposition. The radiation characteristic is obtained from boundary element acoustic simulation. Simulation results of both rotor types are compared, and measurements of the drive are presented.

Mitigation of the torque ripple of a switched reluctance motor through a multiobjective optimization

The purpose of this work is to perform a multiobjective optimization in a 4:2 switched reluctance motor aiming both to maximize the mitigation of the torque ripple and to minimize the degradations of the starting and mean torques. To accomplish this task the Pareto Archived Evolution Strategy was implemented jointly with the Kriging Method, which acts as a surrogate function. The technique was applied on the optimization of some rotor geometrical parameters with the aid of finite element simulations to evaluate the approximation points for the Kriging model. The numerical results were compared to those from tests.

Normal Versus Pathological Voice Signals Using Wavelet Analysis and Least Squares Support-Vector Machines

State of Sao Paulo Research Foundation (FAPESP)

Comparison Between Voltage Control Structures of Synchronous Machines

This paper compares the behaviour of two different control structures of automatic voltage regulators of synchronous machines equipped with static excitation systems. These systems have a fully controlled thyristor bridge that supplies DC current to the rotor winding. The rectifier bridge is fed by the stator terminals through a step-down transformer. The first control structure, named ""Direct Control"", has a single proportional-integral (PI) regulator that compares stator voltage setpoint with measured voltage and acts directly on the thyristor bridge`s firing angle. This control structure is usually employed in commercial excitation systems for hydrogenerators. The second structure, named ""Cascade Control"", was inspired on control loops of commercial DC motor drives. Such drives employ two PIs in a cascade arrangement, the external PI deals with the motor speed while the internal one regulates the armature current. In the adaptation proposed, the external PI compares setpoint with the actual stator voltage and produces the setpoint to the internal PI-loop which controls the field current.

Checking Completeness of Tests for Finite State Machines

In testing from a Finite State Machine (FSM), the generation of test suites which guarantee full fault detection, known as complete test suites, has been a long-standing research topic. In this paper, we present conditions that are sufficient for a test suite to be complete. We demonstrate that the existing conditions are special cases of the proposed ones. An algorithm that checks whether a given test suite is complete is given. The experimental results show that the algorithm can be used for relatively large FSMs and test suites.

Electrical transport in single-crystalline Li(0.9)Mo(6)O(17): A two-band Luttinger liquid exhibiting Bose metal behavior

Temperature-dependent electrical resistance in quasi-one-dimensional Li(0.9)Mo(6)O(17) is described by two Luttinger liquid anomalous exponents alpha, each associated with a distinct one dimensional band. The band with alpha < 1 is argued to crossover to a higher dimension below the temperature T(M'), leading to superconductivity. Disorder and magnetic fields are shown to induce the Bose metal behavior in this bulk compound.

Evolution of magnetic properties and crystallographic texture in electrical steel with large plastic deformation

Deformation leads to a hardening of steel due to an increase in the density of dislocations and a reduction in their mobility, giving rise to a state of elevated residual stresses in the crystal lattice. In the microstructure, one observes an increase in the contribution of crystalline orientations which are unfavorable to the magnetization, as seen, for example, by a decrease in B(50), the magnetic flux density at a field of 50 A/cm. The present study was carried out with longitudinal strips of fully processed non-oriented (NO) electrical steel, with deformations up to 70% resulting from cold rolling in the longitudinal direction. With increasing plastic deformation, the value of B(50) gradually decreases until it reaches a minimum value, where it remains even for larger deformations. On the other hand, the coercive field H(c) continually increases. Magnetometry results and electron backscatter diffraction results are compared and discussed. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3560895]

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Comparison of the Effects of Electrical Field Stimulation and Low-Level Laser Therapy on Bone Loss in Spinal Cord-Injured Rats

Objective: This study investigated the effects of low-level laser therapy (LLLT) and electrical stimulation (ES) on bone loss in spinal cord-injured rats. Materials and Methods: Thirty-seven male Wistar rats were divided into four groups: standard control group (CG); spinal cord-injured control (SC); spinal cord-injured treated with laser (SCL; GaAlAs, 830 nm, CW, 30mW/cm, 250 J/cm(2)); and spinal cord-injured treated with electrical field stimulation (SCE; 1.5 MHz, 1: 4 duty cycles, 30 mW, 20 min). Biomechanical, densitometric, and morphometric analyses were performed. Results: SC rats showed a significant decrease in bone mass, biomechanical properties, and morphometric parameters (versus CG). SCE rats showed significantly higher values of inner diameter and internal and external areas of tibia diaphyses; and the SCL group showed a trend toward the same result (versus SC). No increase was found in either mechanical or densitometric parameters. Conclusion: We conclude that the mentioned treatments were able to initiate a positive bone-tissue response, maybe through stimulation of osteoblasts, which was able to determine the observed morphometric modifications. However, the evoked tissue response could not determine either biomechanical or densitometric modifications.

Logarithmic contribution to the electrical resistivity in (Ru(1-x)Ir(x))Sr(2)GdCu(2)O(8) compounds

A systematic study of magnetoresistance and dc magnetization was conducted in polycrystalline (Ru(1-x)Ir(x))Sr(2)GdCu(2)O(8) [(Ru,Ir)-1212] compounds, for 0 <= x <= 0.15. We found that a deviation from linearity in the normal-state electrical resistivity (rho) curves for temperatures below the magnetic transition temperature T(M) < 130 K can be properly described by a logarithmic term. The prefactor C(x, H) of this anomalous ln T contribution to rho(T) increases linearly with the Ir concentration, and diminishes rapidly with increasing applied magnetic field up to H approximate to 4 T, merging with the C(0,H) curve at higher magnetic fields. Correlation with magnetic susceptibility measurements supports a scenario of local perturbations in the orientation of Ru moments induced in the neighborhood of the Ir ions, therefore acting as scattering centers. The linear dependence of the prefactor C(x,H=0) and the superconducting transition temperature T(SC) on x points to a common source for the resistivity anomaly and the reduction in T(SC), suggesting that the CuO(2) and RuO(2) layers are not decoupled.

Fluoride-modified electrical properties of lead borate glasses and electrochemically induced crystallization in the glassy state

Lead fluoroborate glasses were prepared by the melt-quenching technique and characterized in terms of (micro)structural and electrical properties. The study was conducted on as prepared as well as temperature- and/or electric field-treated glass samples. The results show that, in the as-prepared glassy-state materials, electrical conductivity improved with increasing the PbF(2) glass content. This result involves both an increase of the fluoride charge carrier density and, especially, a decrease of the activation energy from a glass structure expansion improving charge carrier mobility. Moreover, for the electric field-treated glass samples, surface crystallization was observed even below the glass transition temperature. As previously proposed in literature, and shown here, the occurrence of this phenomenon arose from an electrochemically induced redox reaction at the electrodes, followed by crystallite nucleation. Once nucleated, growth of beta-PbF(2) crystallites, with the indication of incorporating reduced lead ions (Pb(+)), was both (micro)structurally and electrically detectable and analyzed. The overall crystallization-associated features observed here adapt well with the floppy-rigid model that has been proposed to further complete the original continuous-random-network model by Zachariasen for closely addressing not only glasses' structure but also crystallization mechanism. Finally, the crystallization-modified kinetic picture of the glasses' electrical properties, through application of polarization/depolarization measurements originally combined with impedance spectroscopy, was extensively explored. (c) 2008 American Institute of Physics.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

THE SUMMATION OF VOLUNTARY AND ELECTRICAL ELICITED STIMULUS INCREASES JOINT TORQUE?

The aim of this study is to analyze the effect of neuromuscular electrical stimulation (NMES) on myoelectrical activity and on joint torque during isometric plantar flexion contraction. Ten healthy young adult subjects participate in this study. The electrodes for NMES are placed along posterior thigh along ciatic nerve trajectory. It is measured the myoelectrical activity and the isometric torque generated by ankle plantar flexion with an isokinetic dynamometer. The conditions of isometric contractions are maximum isometric voluntary contraction (MIVC), NMES, and association of both (MIVC+NMES). The results show lower torque during NMES and larger SOL activity compare to the others. Besides, in order to keep the same objective task (to produce the same level of torque), neuromuscular adaptations are necessary on the common drive.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

Electrical and Magnetic Characterization of BSCCO and YBCO HTS Tapes for Fault Current Limiter Application

Several high temperature superconductor (HTS) tapes have been developed since the late eighties. Due to the new techniques applied for their production, HTS tapes are becoming feasible and practical for many applications. In this work, we present the test results of five commercial HTS tapes from the BSCCO and YBCO families (short samples of 200 mm). We have measured and analyzed their intrinsic and extrinsic properties and compared their behaviors for fault current limiter (FCL) applications. Electrical measurements were performed to determine the critical current and the n value through the V-I relationship under DC and AC magnetic fields. The resistance per unit length was determined as a function of temperature. The magnetic characteristics were analyzed through susceptibility curves as a function of temperature. As transport current generates a magnetic field surrounding the HTS material, the magnetic measurements indicate the magnetic field supported by the tapes under a peak current 1.5 times higher than the critical current, I(c). By pulsed current tests the recovery time and the energy/volume during a current fault were also analyzed. These results are in agreement with the data found in the literature giving the most appropriate performance conductor for a FCL device (I(peak) = 4 kA) to be used in a 220 V-60 Hz grid.