Magnetic Barkhausen Noise in Quenched Carburized Nickel-Steels

Two steel sheets, one with 5% Ni and another with 10% Ni, were submitted to carburization and quenching, obtaining a microstructure with martensite and retained austenite. These steels were characterized with magnetic Barkhausen noise (MBN). The Barkhausen signal is distinctively different for the carburized and quenched samples. The carburized and quenched samples present higher coercive field than the annealed samples. X-ray diffraction data indicated that the carburized and quenched samples have high density of dislocations, a consequence of the martensitic transformation.

Effects of the Compaction Pressure on the Magnetic Properties of a Sintered Fe-Based Alloy

The structural and magnetic properties of a Fe-based alloy before and after sintering have been analyzed. X ray diffraction measurements confirm the deformation of the magnetic particles in the compacted samples. After sintering, hysteresis energy dissipation, remanence and intrinsic coercivity differ by less than 10% as porosity changes from 15 to 7%.

Effect of Plastic Deformation on the Excess Loss of Electrical Steel

The interpretation of the effect of plastic deformation on the calculated excess loss component (anomalous-loss) supports the concept of loss separation. Magnetic losses and Barkhausen noise of nonoriented electrical steel sheets were measured on Epstein strips taken from a single coil of 0.8% Si nonoriented electrical steel. Sheets were extracted in the annealed condition, without any skin pass and with a grain size of 18 mu m. This material was cold rolled in order to obtain sets of samples with true strain from 2% up to 29%. X-ray diffraction was used to estimate the dislocation density. The analysis of magnetic properties was performed by Barkhausen noise measurements and also by analyzing the hysteresis loops obtained from Epstein frame measurements for different inductions and different frequencies (including the quasi-static regime for hysteresis loss measurements). These data allowed us to observe that most of the well known total loss increase with plastic deformation is due to an increase in the hysteresis loss component, while excess loss decreases to become negligible. This behavior can be explained if it is assumed that the plastic deformation lead to an increase in the number of domain walls per unit volume, thereby decreasing the excess loss. Barkhausen peak area increases with plastic deformation, reproducing results taken from samples of different silicon content.

Subdivision of Hysteresis Loss in Mn-Zn Ferrite Toroidal Cores

The hysteresis loss subdivision method proved to be a strong tool to help in the analysis of different energy dissipation mechanisms along the quasi-static hysteresis loop measured on electrical steels. This paper used the samemethod to discuss the mechanisms involving the energy loss dissipation in Mn-Zn ferrite toroidal cores. The samples, sintered under controlled atmosphere in industrial conditions, were measured under triangular waveform excitation at very low frequency (5 mHz) and peak flux densities varying from 0.05 T to 0.45 T. The results show a different behavior between the low inductions hysteresis loss (WLI) and the high induction hysteresis loss (WHI) which proves the existence of different energy dissipation mechanisms affecting these loss components.

A Chaotic Approach of Differential Evolution Optimization Applied to Loudspeaker Design Problem

Over the past few years, the field of global optimization has been very active, producing different kinds of deterministic and stochastic algorithms for optimization in the continuous domain. These days, the use of evolutionary algorithms (EAs) to solve optimization problems is a common practice due to their competitive performance on complex search spaces. EAs are well known for their ability to deal with nonlinear and complex optimization problems. Differential evolution (DE) algorithms are a family of evolutionary optimization techniques that use a rather greedy and less stochastic approach to problem solving, when compared to classical evolutionary algorithms. The main idea is to construct, at each generation, for each element of the population a mutant vector, which is constructed through a specific mutation operation based on adding differences between randomly selected elements of the population to another element. Due to its simple implementation, minimum mathematical processing and good optimization capability, DE has attracted attention. This paper proposes a new approach to solve electromagnetic design problems that combines the DE algorithm with a generator of chaos sequences. This approach is tested on the design of a loudspeaker model with 17 degrees of freedom, for showing its applicability to electromagnetic problems. The results show that the DE algorithm with chaotic sequences presents better, or at least similar, results when compared to the standard DE algorithm and other evolutionary algorithms available in the literature.

Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning to Optimization of Broad-Band Reflector Antennas Satellite

This paper aims to provide an improved NSGA-II (Non-Dominated Sorting Genetic Algorithm-version II) which incorporates a parameter-free self-tuning approach by reinforcement learning technique, called Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning (NSGA-RL). The proposed method is particularly compared with the classical NSGA-II when applied to a satellite coverage problem. Furthermore, not only the optimization results are compared with results obtained by other multiobjective optimization methods, but also guarantee the advantage of no time-spending and complex parameter tuning.

Bat-Inspired Optimization Approach for the Brushless DC Wheel Motor Problem

This paper presents a metaheuristic algorithm inspired in evolutionary computation and swarm intelligence concepts and fundamentals of echolocation of micro bats. The aim is to optimize the mono and multiobjective optimization problems related to the brushless DC wheel motor problems, which has 5 design parameters and 6 constraints for the mono-objective problem and 2 objectives, 5 design parameters, and 5 constraints for multiobjective version. Furthermore, results are compared with other optimization approaches proposed in the recent literature, showing the feasibility of this newly introduced technique to high nonlinear problems in electromagnetics.

Multiobjective Biogeography-Based Optimization Based on Predator-Prey Approach

Biogeography is the science that studies the geographical distribution and the migration of species in an ecosystem. Biogeography-based optimization (BBO) is a recently developed global optimization algorithm as a generalization of biogeography to evolutionary algorithm and has shown its ability to solve complex optimization problems. BBO employs a migration operator to share information between the problem solutions. The problem solutions are identified as habitat, and the sharing of features is called migration. In this paper, a multiobjective BBO, combined with a predator-prey (PPBBO) approach, is proposed and validated in the constrained design of a brushless dc wheel motor. The results demonstrated that the proposed PPBBO approach converged to promising solutions in terms of quality and dominance when compared with the classical BBO in a multiobjective version.

Using Equivalent Emission Sources to Evaluate the Coupling Between Components

The electromagnetic interference between the electronic systems or their components influences the performance of the systems. For that reason, it is important to model these interferences in order to optimize the position of the systems or their components. In this paper, a method is proposed to construct the equivalent emission source models of systems. The proposed method is based on the multipolar expansion by representing the radiated emission of generic structures in a spherical reference (r, theta, phi). Some results are presented illustrating our method.

Magnetic Properties of γ - Fe2O3 Nanoparticles at the Verge of Nucleation Process.

A low-energy new method based in a one-step synthesis at room temperature produces very small maghemite nanopar ticles. The fast neutralization reaction (co-precipitation) of a ferric solution (FeCl3 aqueous) in a basic medium (NH4OH concentrated) produces an intermediate phase, presumably two-line ferrihydrite, that in oxidizing conditions is transformed to maghemite nanopar ticles. That “primordial soup” is characterized by small atom arrangements that are the base for maghemite tiny crystals. The final product of the reaction was characterized by X-ray diffraction, high-resolution transmission electron microscopy, X-ray absorption fine structure, Mössbauer spectroscopy, and magnetometry.