Using artificial neural networks for identification of electrical losses in transformers during the manufacturing phase

The paper describes a novel neural model to estimate electrical losses in transformer during the manufacturing phase. The network acts as an identifier of structural features on electrical loss process, so that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through experimental data taking into account core losses, copper losses, resistance, current and temperature. The results obtained in the simulations have shown that the developed technique can be used as an alternative tool to make the analysis of electrical losses on distribution transformer more appropriate regarding to manufacturing process. Thus, this research has led to an improvement on the rational use of energy.

Structural health evaluation by optimization techinique and artificial neural network

This paper presents two different approaches to detect, locate, and characterize structural damage. Both techniques utilize electrical impedance in a first stage to locate the damaged area. In the second stage, to quantify the damage severity, one can use neural network, or optimization technique. The electrical impedance-based, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations, this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors, and therefore, it is able to detect the damage in its early stage. Optimization approaches must be used for the case where a good condensed model is known, while neural network can be also used to estimate the nature of damage without prior knowledge of the model of the structure. The paper concludes with an experimental example in a welded cubic aluminum structure, in order to verify the performance of these two proposed methodologies.

Potentiometric determination of saccharin in commercial artificial sweeteners using a silver electrode

A simple, precise, rapid and low-cost potentiometric method for saccharin determination in commercial artificial sweeteners is proposed. Saccharin present in several samples of artificial sweeteners is potentiometrically titrated with silver nitrate solution using a silver wire as the indicator electrode, coupled to a titroprocessor. The best pH range was from 3.0 to 3.5 and the detection limit of sodium saccharin was 2.5 mg/ml. Substances normally found along with saccharin in several commercial artificial sweeteners such as maltodextrin, glucose, sucrose, fructose, aspartame, cyclamate, caffeine, sorbitol, lactose, nitrate, methyl- and n-propyl-p-hydroxybenzoate, benzoic, citric and ascorbic acids do not interfere even in significant amounts (e.g. 20 excess relative to saccharin). Chloride ion interferes when present in concentrations larger than 10 mg l(-1); this interference is eliminated with previous extraction of the sweetener from the aqueous medium with ethyl acetate. The results obtained by applying the proposed method compared very favorably with those given by the HPLC method recommended by the FDA. (C) 2003 Elsevier Ltd. All rights reserved.

Combining artificial intelligence and human problem solving: Proposing a new architecture for ITS's

This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.

Stability analysis of the attitude of artificial satellites subject to gravity gradient torque

Using a canonical formulation, the stability of the rotational motion of artificial satellites is analyzed considering perturbations due to the gravity gradient torque. Here Andoyer's variables are used to describe the rotational motion. One of the approaches that allow the analysis of the stability of Hamiltonian systems needs the reduction of the Hamiltonian to a normal form. Firstly equilibrium points are found. Using generalized coordinates, the Hamiltonian is expanded in the neighborhood of the linearly stable equilibrium points. In a next step a canonical linear transformation is used to diagonalize the matrix associated to the linear part of the system. The quadratic part of the Hamiltonian is normalized. Based in a Lie-Hori algorithm a semi-analytic process for normalization is applied and the Hamiltonian is normalized up to the fourth order. Once the Hamiltonian is normalized up to order four, the analysis of stability of the equilibrium point is performed using the theorem of Kovalev and Savichenko. This semi-analytical approach was applied considering some data sets of hypothetical satellites. For the considered satellites it was observed few cases of stable motion. This work contributes for space missions where the maintenance of spacecraft attitude stability is required.

Artificial neural networks for machining processes surface roughness modeling

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

LH and FSH concentration and follicular development in Nellore heifers submitted to fixed-time artificial insemination protocols with different progesterone concentrations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evaluation of the Possibility of Removing Staining by Repolishing Composite Resins Submitted to Artificial Aging

This in vitro research verified the possibility of eliminating staining caused by coffee and red wine in five composite resins, after being submitted to thermal cycling. Thirty-six specimens were prepared and immersed in water at 37 degrees C for 24 hours. After polishing, specimen color was measured in a spectrophotometer Cintra 10 UV (Visible Spectrometer, GBC, Braeside, VIC, Australia). All specimens were submitted to thermal cycling at temperatures of 5 and 55 degrees C with a dwell time of 1 minute, for 1,000 cycles in a 75% ethanol/water solution. After thermal cycling, the specimens were immersed in water at 37 degrees C until 7 days had elapsed from the time the specimens were prepared. All specimens were then taken to the spectrophotometer for color measurement. The specimens were divided into three groups (N = 12): distilled water (control), coffee, and red wine. For the staining process to occur on only one surface, all the sides, except one, of the surfaces were isolated with white wax. The specimens were immersed in one of the solutions at 37 degrees C for 14 days. The specimens were dried and taken to the spectrophotometer for color measurement. After this, the specimens were submitted to 20 mu m wear three times, and the color was measured after each one of the wear procedures. Calculation of the color difference was made using CIEDE2000 formula. According to the methodology used in this research, it was concluded that the staining caused by coffee and red wine was superficial and one wear of 20 mu m was sufficient to remove the discoloration.