In this paper, magnetic Barkhausen noise (MBN) is employed to quantitatively predict the
hardness of GCr15 bearing steel. Firstly, to thoroughly investigate the relationship between …

A novel approach was presented to characterize microstructural features of thermal barrier
coatings (TBCs) using terahertz spectroscopy based on machine learning algorithms. In this …

Material properties can vary both along a sheet-metal coil and from coil to coil despite tight
tolerances influencing the process stability of sheet-metal processes and the part quality …

The digital transformation is fundamentally changing our industries, affecting planning,
execution as well as monitoring of production processes in a wide range of application …

The measurement of mechanical properties parameters has been found as the standard
process to predict the quality of ferromagnetic materials, which is a critical step in the …

Abstract In this paper, Monte Carlo simulations are performed based on the two-dimensional
Ising model with the objective of matching the simulated magnetic Barkhausen noise (MBN) …

Ferromagnetic materials are widely used in industry and risking the hazards of aging and
degradation of their mechanical properties. This paper proposed a non-destructive method …

Tensile strength (TS) is an important mechanical property of a material. The conventional
mechanical measurement method destroys the object under investigation; hence, the non …