MAgnetic Barkhausen noise

The aeromagnetic data of the Northern part of the Central Eastern Desert that bounded by latitudes 25˚5525˚55 ‫׳‬ 00 ‫״‬ to 26 ̊ 16 ‫׳‬ 00 ‫״‬ N and longitudes 32 ̊ 45 ‫׳‬ 00 ‫״‬ to 33˚52´00˝33˚52´33˚52´00˝ E and covers approximately 3852 km² have been digitized, gridded, processed and interpreted to estimate the magnetic basement depth (consequently the thickness of the sedimentary cover). Two methods were used to achieve that objective. The Euler deconvolution method and source parameter imaging (SPI). The results obtained from applying the two methods show depth ranges from 0 to 1 km. It was clearly evident that the results obtained from both methods were nearly identical. The shallow sources are observed in the eastern part of the study area where the outcropping basement rocks occupied, whereas the western part entails the deep sources where the sedimentary cover located. Moreover, a magnetic basement depth map was prepared from the results obtained from Euler deconvolution method. Again, the map showed that the depth was increasing towards the western part of the map and decrease towards the eastern side where the outcropping basement rocks were located.

The average temporal shape of avalanches has been a fruitful application of universality and critical scaling, with experimental and theoretical investigations particularly in the field of magnetic Barkhausen noise. The mean-field shapes of these avalanches have been thought to come in two forms: inverted parabolas for the infinite-range model and one lobe of a sinusoid for the single-degree of freedom ABBM model. We show that the infinite-range model can be mapped onto the earlier ABBM model, and that the average shape for both mean field theories is an inverted parabola, seemingly resolving the ambiguity. However, we also propose a new mean-field model including the effects of local saddle-node bifurcations on the dynamics, and analyze both its predictions for dynamical exponents and temporal average shapes. We compare with experimental results on sheared granular materials.

The Magnetic Barkhausen Noise (MBN) is a phenomenon occurring in ferromagnetic materials undergoing changes in magnetization. This phenomenon is very sensitive to material microstructural changes and, as a consequence, the MBN can be applied as a non-destructive monitoring technique for detecting plastic deformation in the material of mechanical components subjected to thermo- mechanical processes, such as machining and forming processes.

This paper deals with a multi-features numerical instrument to estimate and qualify Barkhausen noise. Starting from traditional instruments based on RMS value of the band-pass filtered measured signal, the proposed method is based on the simultaneous analysis of the excitation voltage, the excitation current and the induced signal. The aim is to overcome the well-known limits in terms of measurement repeatability and noise immunity. A good repeatability improvement is achieved by monitoring the excitation impedance, while synchronizing the RMS evaluation to the excitation current signal increases the robustness with respect to the environmental electromagnetic noise. Moreover, the use of shape-based parameters is encouraged to better qualify the Barkhausen signal

.    This paper discusses a new methodology for characterizing the magnetic properties of ferromagnetic materials. The method uses an alternating electric current to periodically magnetize ferromagnetic materials. The periodic magnetization generates a high-frequency electric potential noise between two electrodes within the excitation circuit. The magnetically induced electric potential noise (MIPN) is related to the discontinuous processes that occur during