netization curves [5] measurement methods. A promising method for measuring axes of easy and hard magnetization is the magnetic Barkhausen noise method. It is related to the Barkhausen effect occurring during the process of magnetic domain structure reorganization which takes place when the AC magnetic field is applied to the ferromagnetic material. The Barkhausen effect has a stochastic, non-stationary nature and its course strictly depends on the microstructure and mechanical stress of the tested material [10]. The rearrangement of the domain structure causes local abrupt changes of the magnetization in the sample. When a coil is applied to such a material, a corresponding voltage will be induced in the coil, called the MBN signal [11]. Considering the close relationship between the mechanical and magnetic properties of ferromagnetic materials, it becomes possible both to influence the magnetic properties of steel using engineering methods and to test those steels subsequently as well [10]. Due to these properties, the MBN method is also applicable to study the anisotropy of the magnetic properties of steel [12; 13; 14; 15; 16; 17; 18; 19]. The subjects of the research are often steel elements used in pipelines services. Strongly directional magnetic properties in these elements, e.g., can have a large impact on the effectiveness of the non-destructive method used to test these components, such as the magnetic flux leakage [10; 12; 14; 15]. In [12], the authors used the MBN method to investigate the origin of the magnetic easy axis and characterize the anisotropy of pipeline API X70 steel. In paper [12], the authors proposed a method for determining the magnetic easy axis affected by the roll magnetic anisotropy in API-5L steel, while in [14; 15], the authors presented the results of a study on the identification of various processes distinguished in magnetization dynamics based on the analysis of an MBN course. In [17], the authors presented the results of research on the utilization of MBN for the monitoring of variation in magnetic anisotropy affected by crystallographic texture in cold rolled low carbon steel sheets. Anisotropy was also tested in grain-oriented steels. Exemplary, in [13] the authors demonstrated the possibility of conducting quick tests and showing the relationship between the initial permeability and the root mean square of the MBN signal. Nevertheless, given the complexity of Barkhausen noise signals, the application of data processing techniques becomes a critical step in obtaining often hidden and complex components of knowledge about the state of the material under study. The majority of MBN analyses are performed in the time domain \(T\), however the frequency domain \(F\) is also considered [20]. However, it should be noted that the MBN signal changes both in time and frequency, and the nature and dynamics of the Barkhausen effect are dependent on the type of material and the homogeneity of its structure. As a result, it becomes crucial to track changes in the dynamics of the MBN course over time. Thus, a variety of analytic approaches based on time-frequency (_TF_) transformations of the MBN signal have recently been developed [21; 22; 23; 24; 25]. The article [21] presents an analysis of the MBN _TF_ representations obtained for the determination of the influence of case hardening on MBN characteristics. Several different transformation algorithms were applied and qualitatively compared. Studies [22] and [23] analyze MBN spectrograms to investigate the processes taking place in electrical steel sheets during magnetization and provide a quantitative description of these phenomena as a function of the measurement angle. In [23], a resultant anisotropy of the steel was analyzed based on the _TF_ spectrograms of the entire MBN burst, while in [22] the possibility of determining the influence of various factors on the magnetization dynamics was considered by extraction of bursts subsequences.