Classification of Grain-Oriented Electrical Steel Sheets by Magnetic Barkhausen Noise Using Time-Frequency Analysis and Selected Machine Learning Algorithms
Abstract:In this paper, a combination of Magnetic Barkhausen Noise (MBN) and several classical machine learning (ML) methods were used to evaluate both the grade and the magnetic directions of conventional and high grain oriented electrical sheets subjected to selected surface engineering methods. The presented analysis was conducted to compare the performance of two machine learning approaches, classical ML and deep learning (DL), in reference to the same MBN examination problem and based on the same database. Thus, d… Show more
“…This model aims to improve the accuracy of data repair and ensure that monitoring data reflect the actual safety conditions of the dam. In article [6], authors investigate the use of magnetic Barkhausen noise MBN combined with classical machine learning methods to assess the grade and magnetic anisotropic properties of electrical sheets. The study compares the performance of classical machine learning and deep learning approaches using 26 algorithms.…”
Structural health monitoring (SHM) is focused on the systematic monitoring of the state of structures to determine their safety, dependability, and durability [...]
“…This model aims to improve the accuracy of data repair and ensure that monitoring data reflect the actual safety conditions of the dam. In article [6], authors investigate the use of magnetic Barkhausen noise MBN combined with classical machine learning methods to assess the grade and magnetic anisotropic properties of electrical sheets. The study compares the performance of classical machine learning and deep learning approaches using 26 algorithms.…”
Structural health monitoring (SHM) is focused on the systematic monitoring of the state of structures to determine their safety, dependability, and durability [...]
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