Uma contribuição para a medição de distorções harmônicas e inter-harmônicas em instalações de geração fotovoltaica

Dissertação (mestrado)— Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.

Efficient Image and Video Representations for Retrieval

Image (Video) retrieval is an interesting problem of retrieving images (videos) similar to the query. Images (Videos) are represented in an input (feature) space and similar images (videos) are obtained by finding nearest neighbors in the input representation space. Numerous input representations both in real valued and binary space have been proposed for conducting faster retrieval. In this thesis, we present techniques that obtain improved input representations for retrieval in both supervised and unsupervised settings for images and videos. Supervised retrieval is a well known problem of retrieving same class images of the query. We address the practical aspects of achieving faster retrieval with binary codes as input representations for the supervised setting in the first part, where binary codes are used as addresses into hash tables. In practice, using binary codes as addresses does not guarantee fast retrieval, as similar images are not mapped to the same binary code (address). We address this problem by presenting an efficient supervised hashing (binary encoding) method that aims to explicitly map all the images of the same class ideally to a unique binary code. We refer to the binary codes of the images as `Semantic Binary Codes' and the unique code for all same class images as `Class Binary Code'. We also propose a new class­ based Hamming metric that dramatically reduces the retrieval times for larger databases, where only hamming distance is computed to the class binary codes. We also propose a Deep semantic binary code model, by replacing the output layer of a popular convolutional Neural Network (AlexNet) with the class binary codes and show that the hashing functions learned in this way outperforms the state­ of ­the art, and at the same time provide fast retrieval times. In the second part, we also address the problem of supervised retrieval by taking into account the relationship between classes. For a given query image, we want to retrieve images that preserve the relative order i.e. we want to retrieve all same class images first and then, the related classes images before different class images. We learn such relationship aware binary codes by minimizing the similarity between inner product of the binary codes and the similarity between the classes. We calculate the similarity between classes using output embedding vectors, which are vector representations of classes. Our method deviates from the other supervised binary encoding schemes as it is the first to use output embeddings for learning hashing functions. We also introduce new performance metrics that take into account the related class retrieval results and show significant gains over the state­ of­ the art. High Dimensional descriptors like Fisher Vectors or Vector of Locally Aggregated Descriptors have shown to improve the performance of many computer vision applications including retrieval. In the third part, we will discuss an unsupervised technique for compressing high dimensional vectors into high dimensional binary codes, to reduce storage complexity. In this approach, we deviate from adopting traditional hyperplane hashing functions and instead learn hyperspherical hashing functions. The proposed method overcomes the computational challenges of directly applying the spherical hashing algorithm that is intractable for compressing high dimensional vectors. A practical hierarchical model that utilizes divide and conquer techniques using the Random Select and Adjust (RSA) procedure to compress such high dimensional vectors is presented. We show that our proposed high dimensional binary codes outperform the binary codes obtained using traditional hyperplane methods for higher compression ratios. In the last part of the thesis, we propose a retrieval based solution to the Zero shot event classification problem - a setting where no training videos are available for the event. To do this, we learn a generic set of concept detectors and represent both videos and query events in the concept space. We then compute similarity between the query event and the video in the concept space and videos similar to the query event are classified as the videos belonging to the event. We show that we significantly boost the performance using concept features from other modalities.

Discrete breathers in a two-dimensional hexagonal Fermi-Pasta-Ulam lattice

We consider a two-dimensional Fermi-Pasta-Ulam (FPU) lattice with hexagonal symmetry. Using asymptotic methods based on small amplitude ansatz, at third order we obtain a eduction to a cubic nonlinear Schr{\"o}dinger equation (NLS) for the breather envelope. However, this does not support stable soliton solutions, so we pursue a higher-order analysis yielding a generalised NLS, which includes known stabilising terms. We present numerical results which suggest that long-lived stationary and moving breathers are supported by the lattice. We find breather solutions which move in an arbitrary direction, an ellipticity criterion for the wavenumbers of the carrier wave, symptotic estimates for the breather energy, and a minimum threshold energy below which breathers cannot be found. This energy threshold is maximised for stationary breathers, and becomes vanishingly small near the boundary of the elliptic domain where breathers attain a maximum speed. Several of the results obtained are similar to those obtained for the square FPU lattice (Butt \& Wattis, {\em J Phys A}, {\bf 39}, 4955, (2006)), though we find that the square and hexagonal lattices exhibit different properties in regard to the generation of harmonics, and the isotropy of the generalised NLS equation.

Power Factor Corrector Design applied to an 85-kHz Wireless Charger

Wireless charging technology extends the battery autonomy by allowing more flexible and practical ways of recharging it even when the electric vehicle is on move. The frequency conversion, which is required to generate a kHz-ranged magnetic field, also leads to considerable harmonics. As a result, the power factor and the corresponding efficiency decrement. This paper proposes a Power Factor Corrector which overcomes this drawback. The most relevant feature of the designed Power Factor Corrector is that it does not need any electrical signal from the secondary side to adjust its operation properly. The simulation results show the ability of the proposed scheme to increment the system efficiency for different State-Of-Charge in the Battery.

Avances en el proyecto “Determinación de la forma exacta de la tierra a través de MEMS en un Nano-Satélite”

El presente trabajo muestra el avance que se tiene en el proyecto denominado “Diseño y Construcción de un Nano-Satélite”, que se lleva a cabo en la ESIME U.P.-Ticoman del Instituto Politécnico Nacional. Este proyecto tiene como objetivo principal introducir a los alumnos en el que hacer espacial, se trata de un satélite con un peso de un kilogramo y es un cubo de 10 cm de lado y cuya carga útil tiene MEMS (sistema de micro-electromecánicos) que harán las veces de péndulo electrónico, lo anterior y los armónicos gravitacionales permitirán determinar la forma de la tierra. Se presenta el fundamento matemático, los componentes del satélite, el diseño preliminar de la estructura, la manufactura de la estructura, los resultados de un ensaye estructural destructivo y el análisis estático por elementos finitos.

Flow around a hemisphere-cylinder at high angle of attack and low Reynolds number. Part II: POD and DMD applied to reduced domains

Three-dimensional direct numerical simulations (DNS) have been performed on a finite-size hemispherecylinder model at angle of attack AoA = 20◦ and Reynolds numbers Re = 350 and 1000. Under these conditions, massive separation exists on the nose and lee-side of the cylinder, and at both Reynolds numbers the flow is found to be unsteady. Proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) are employed in order to study the primary instability that triggers unsteadiness at Re = 350. The dominant coherent flow structures identified at the lower Reynolds number are also found to exist at Re = 1000; the question is then posed whether the flow oscillations and structures found at the two Reynolds numbers are related. POD and DMD computations are performed using different subdomains of the DNS computational domain. Besides reducing the computational cost of the analyses, this also permits to isolate spatially localized oscillatory structures from other, more energetic structures present in the flow. It is found that POD and DMD are in general sensitive to domain truncation and noneducated choices of the subdomain may lead to inconsistent results. Analyses at Re = 350 show that the primary instability is related to the counter rotating vortex pair conforming the three-dimensional afterbody wake, and characterized by the frequency St ≈ 0.11, in line with results in the literature. At Re = 1000, vortex-shedding is present in the wake with an associated broadband spectrum centered around the same frequency. The horn/leeward vortices at the cylinder lee-side, upstream of the cylinder base, also present finite amplitude oscillations at the higher Reynolds number. The spatial structure of these oscillations, described by the POD modes, is easily differentiated from that of the wake oscillations. Additionally, the frequency spectra associated with the lee-side vortices presents well defined peaks, corresponding to St ≈ 0.11 and its few harmonics, as opposed to the broadband spectrum found at the wake.

A miniature energy harvesting rectenna for operating a head-mountable deep brain stimulation device

This paper presents design, implementation, and evaluation of a miniature rectenna for energy harvesting applications. The rectenna produces DC power from a distant microwave energy transmitter. The generated DC power is then utilized to operate a head-mountable deep brain stimulation device. The rectenna consists of a miniature three-layer planar inverted-F antenna and a Schottky-diode-based bridge rectifier. The antenna has a volume of π × 6 × 1.584 mm3, a resonance frequency of 915 MHz with a simulated bandwidth of 18 MHz (907-925 MHz), and a measured bandwidth of 18 MHz (910-928 MHz) at the return loss of -10 dB. A dielectric substrate of FR-4 of εr = 4.5 and δ = 0.02 is used for simulation and fabrication of the antenna and the rectifier due to its low cost. An L-section impedance matching circuit is employed between the antenna and the rectifier to reduce the mismatch loss. The impedance matching circuit operates as a low-pass filter eliminating higher order harmonics. A deep brain stimulation device is successfully operated by the rectenna at a distance of 20 cm away from a microwave energy transmitter of power 26.77 dBm. The motivation of this paper includes creation of a deep brain stimulation device that operates indefinitely without a battery. From the application standpoint, the developed energy harvesting rectenna facilitates long-term deep brain stimulation of laboratory animals for preclinical research investigating neurological disorders.

Performance analysis of a grid-connected PV system in LV distribution network

Over the past decade, the growing demand of Grid-connected photo voltaic (GCPV) system has been increasing due to an extensive use of renewable energy technologies for sustainable power generation and distribution. High-penetrated GCPV systems enhance the operation of the network by improving the voltage levels and reducing the active power losses along the length of the feeder. This paper aims to investigate the voltage variations and Total Harmonic Distortion (THD) of a typical GCPV system modelled in Power system simulator, PSS SINCAL with the change of level of PV integrations in a Low Voltage (LV) distribution network. Five different case studies are considered to investigate the impact of PV integrations on LV nodes and the corresponding voltage variations and harmonics. In addition, this paper also explores and benchmarks the voltage improvement techniques by implementing On Load Tap Changer (OLTC) with respective to the main transformer and addition of Shunt Capacitor (SC) at appropriate node points in LV network,

Physics-Based Modeling of Power System Components for the Evaluation of Low-Frequency Radiated Electromagnetic Fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

Online impedance spectroscopy estimation of a battery

Electrochemical impedance spectroscopy (EIS) is a helpful tool to understand how a battery is behaving and how it degrades. One of the disadvantages is that it is typically an 'off-line' process. This paper investigates an alternative method of looking at impedance spectroscopy of a battery system while it is on-line and operational by manipulating the switching pattern of the dc-dc converter to generate low frequency harmonics in conjunction with the normal high frequency switching pattern to determine impedance in real time. However, this adds extra ripple on the inductor which needs to be included in the design calculations. The paper describes the methodology and presents some experimental results in conjunction with EIS results to illustrate the concept.

Numerical solution of an elliptic 3-dimensional Cauchy problem by the alternating method and boundary integral equations

We consider the Cauchy problem for the Laplace equation in 3-dimensional doubly-connected domains, that is the reconstruction of a harmonic function from knowledge of the function values and normal derivative on the outer of two closed boundary surfaces. We employ the alternating iterative method, which is a regularizing procedure for the stable determination of the solution. In each iteration step, mixed boundary value problems are solved. The solution to each mixed problem is represented as a sum of two single-layer potentials giving two unknown densities (one for each of the two boundary surfaces) to determine; matching the given boundary data gives a system of boundary integral equations to be solved for the densities. For the discretisation, Weinert's method [24] is employed, which generates a Galerkin-type procedure for the numerical solution via rewriting the boundary integrals over the unit sphere and expanding the densities in terms of spherical harmonics. Numerical results are included as well.