A novel approach based on pattern recognition techniques to evaluate magnetic properties of a non-grain oriented electrical steel in the secondary recrystallization process

Duarte, Larissa Moreira; Santos, José Daniel de Alencar; Freitas, Francisco Nélio Costa; Filho, Pedro Pedrosa Rebouças; Abreu, Hamilton Ferreira Gomes de

doi:10.1016/j.measurement.2020.108135

Cited by 7 publications

(2 citation statements)

References 64 publications

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“…(3) hybrid method of hysteresis model and loss separation [16]. Currently, with the increasing development of artificial intelligence, some scholars also use machine learning methods to figure out the losses of soft magnetic materials [17]. The J-A model has high computational efficiency, accurate parameter description, clear physical concepts, and it can be also extended to dynamic hysteresis models for low, medium and high frequency bands [18,19].…”

Section: Introductionmentioning

confidence: 99%

Hysteresis and loss characteristics of Fe-based nanocrystalline alloys based on a novel variable-temperature dynamic Jiles–Atherton hysteresis model

Xu,

Zhao,

Ren

et al. 2023

J. Phys. D: Appl. Phys.

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The magnetic characteristics of Fe-based nanocrystalline alloys can be influenced by temperature. The conventional dynamic Jiles–Atherton (J-A) hysteresis model does not take into consideration the impact that temperature has on magnetic characteristics. A novel variable-temperature dynamic J-A hysteresis model is proposed in this paper to effectively address the issue. Firstly, the hysteresis loops of Fe-based nanocrystalline are measured at −50 °C–130 °C and DC state. The five parameters of the J-A hysteresis model are identified at various temperatures using the particle swarm optimization algorithm, and five parameters are fitted as functions of temperature. Subsequently, the five parameters as functions of temperature are introduced into the conventional dynamic J-A hysteresis model to construct a novel variable-temperature dynamic J-A hysteresis model, which can not only reflect the impact of temperature but also accurately calculate the losses. Finally, hysteresis loops and losses of Fe-based nanocrystalline alloy are simulated and calculated at different temperatures and frequencies by the variable-temperature dynamic J-A hysteresis model. Meanwhile, this paper also investigates the trends and percentages of hysteresis loss, excess loss as well as eddy current loss with frequency and temperature. Compared to the results of measured data, the maximum average error of the variable-temperature dynamic J-A hysteresis model is 5.83%.

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Section: Introductionmentioning

confidence: 99%

Hysteresis and loss characteristics of Fe-based nanocrystalline alloys based on a novel variable-temperature dynamic Jiles–Atherton hysteresis model

Xu,

Zhao,

Ren

et al. 2023

J. Phys. D: Appl. Phys.

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“…There is an increasing need for highly power-efficient electrical machines for a wide range of applications in which silicon electrical steel is the core material. For an optimal design of the electromagnetic properties, the chemical composition, and the recrystallization annealing of the steel are the most important influencing parameters [1][2][3][4]. Because the interest will continue to grow for high-specific-power electrical machines, especially for various new and un-conventional applications, the development of new classes of highspecific-power electrical machines and drives is required [4].…”

Section: Introductionmentioning

confidence: 99%

Kinetics of Arsenic Surface Segregation in Scrap-Based Silicon Electrical Steel

Petrovič

2020

Metals

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The segregation kinetics of surface-active, residual elements are investigated in an in situ study of annealing scrap-based silicon electrical steel sheet where the arsenic (As) surface segregation is highlighted. During annealing in the temperature range of 300–950 °C, different kinds of interactions between the segregated residual elements were observed. Attractive interactions between the segregands produced co-segregation, e.g., between Sn and Sb, whereas repulsive interactions resulted in site competition, e.g., between Sn and As. These competing interactions are strongly time dependent. In spite of there being twice as much Sn compared to As in the bulk material, the As prevailed in the surface enrichments of the polycrystalline silicon steel at 950 °C. The intensity of the As surface segregation in the temperature range 800–950 °C is proportional to the calculated amount of γ-austenite phase in the (α + γ) steel matrix. The detected phenomenon of the As versus Sn site competition could be valuable for the texture design and surface engineering of silicon steels with a thermodynamically stable two-phase (α + γ) region.

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Effects of Asymmetric Cross-Rolling and Initial Annealing on the Microstructure, Crystallographic Texture, and Magnetic Behavior of Silicon Steel with Different Amounts of Antimony

Babapour

Hosseinipour

Jamaati

et al. 2022

J. of Materi Eng and Perform

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A novel approach based on pattern recognition techniques to evaluate magnetic properties of a non-grain oriented electrical steel in the secondary recrystallization process

Cited by 7 publications

References 64 publications

Hysteresis and loss characteristics of Fe-based nanocrystalline alloys based on a novel variable-temperature dynamic Jiles–Atherton hysteresis model

Hysteresis and loss characteristics of Fe-based nanocrystalline alloys based on a novel variable-temperature dynamic Jiles–Atherton hysteresis model

Kinetics of Arsenic Surface Segregation in Scrap-Based Silicon Electrical Steel

Effects of Asymmetric Cross-Rolling and Initial Annealing on the Microstructure, Crystallographic Texture, and Magnetic Behavior of Silicon Steel with Different Amounts of Antimony

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