Research on Fatigue Damage of Ferromagnetic Material by Metal Magnetic Memory Methods

Abstract

Tension–tension fatigue tests of notched 18CrNi4A steel specimens were carried out under three different fatigue stresses, and metal magnetic memory (MMM) signals were detected. The effects of fatigue damage and fatigue stress on MMM signals were investigated. The results show that the absolute values of the feature parameters Hp(y)max, Hp(y)min and Hp(y)sub increase with the aggravation of the fatigue damage. There is an inherent relationship between the fatigue stress and the values of the Hp(y)sub; the larger the fatigue stress is, the larger the absolute values of the Hp(y)sub is. Fatigue-damaged locations can be effectively predicated according to the mutational character of the Hp(y) curve and the K curve, and zero-crossing points of the Hp(y) curve, respectively. Fatigue damage degree can be effectively predicated according to the value of the Kmax and the Hp(y)max, Hp(y)min and Hp(y)sub.

Effect of tensile stress on the variation of magnetic field of low-alloy steel

“…2b). The study on low cycle fatigue experiment of 18CrNi4A [10] and static tensile test of 45 steel [11] showed that the zero-crossing point was not stress concentration zone because of the influence of initial field. To eliminate its influence, let initial H p (y) (H p0 (y)) be reference values, and those after loading H p (y) (H pi (y)) minus the reference values, i.e.…”

Magnetic Dipole Model and Experimental Analysis of Magnetic Signal Detection Based on Magnetic Memory

“…Residual stress and hidden damage generated in the production and manufacturing process will lead to its failure or even fracture under long-term fatigue damage. Serious or even catastrophic accidents will seriously threaten people's property and life safety [2][3], so it is particularly important to assess the damage of ferromagnetic specimens in the early stage [4]. Metal magnetic memory detection technology was first proposed by Professor DOUBOV in 1994 [5][6].…”