Application of Neural Networks and Axial Flux for the Detection of Stator and Rotor Faults of an Induction Motor

The paper presents the possibility of using neural networks in the detection of stator and rotor electrical faults of induction motors. Fault detection and identification are based on the analysis of symptoms obtained from the fast Fourier transform of the voltage induced by an axial flux in a measurement coil. Neural network teaching and testing were performed in a MATLAB–Simulink environment. The effectiveness of various neural network structures to detect damage, its type (rotor or stator damage) and damage levels (number of rotor bars cracked or stator winding shorted circuits) is presented.

Application of Arduino Module to Research in Surface Physics

During the semiconductor or graphene wafers surface were investigated, the Arduino module was applied to control the impact point of the laser beam. While the pulse signal of laser beam impacts to surface selected material and the material is exposed to enough strong magnetic field, the photomagnetoelectric effect takes place. This causes the electrical signal in the measurement coil, which is connected to amplifiers. The paper presents application of Arduino UNO module to control the position in two dimensions (in the XY plane) of investigated silicon or graphene wafers while the photomagnetoelectric effect is measuring. The Arduino drive (through the integrated circuit with power transistors) the steps and shift of a dedicated table with a sample situated at the top of the table. Constructed equipment, based on Arduino board, allows for one step size of 1.25 μm in X-axis and Y-axis, and in effect, the each square millimeter contains 640000 measurement points. We are able also to modify the Arduino program for motors controller any moment. Moreover, it is also possible to apply the obtain method to investigate another semiconductor materials. The commercially available similar devices don’t have all need functions and they are incomparably more expensive.

Results of magnetometry data processing for non-destructive testing of compressive mechanical stress levels in steels

We plotted the fields of measurement coil signal as functions inversely proportional to reversible magnetisation in low-carbon St20 steel plates subjected to plastic tensile strain. Performing an additional approximation of our experimental data using three pseudo-Voigt functions allowed us to detect the information concerning irreversible motion of the 90-degree domain walls that are most sensitive to mechanical stresses. As a result of performing mathematical processing of experimental data we managed to improve validity of estimating the fields of stress-induced magnetic anisotropy and mechanical stresses.

Sensitivity analysis of electromagnetic quantities in time domain by means of fem

Sensitivity analysis belongs to the most important tools in optimization theory. It determines the dependence of global or local electromagnetic quantities on geometrical and physical parameters expressed in the form of an objective function. For several objective functions the sensitivity may be directly calculated differentiating the objective function versus one of material or geometric parameters. Such approach needs large computational effort, especially while evaluating in time domain. This paper presents effective methods for computing of sensitivity of nodal potentials in finite elements versus perturbations in conductivity of analyzed model in time domain. Derived equations are based on the method of stiffness and mass matrices derivative and Tellegen?s theorem known from circuit theory and have been expanded on field theory. Numerical example presented in the paper shows sensitivity of voltage induced in measurement coil versus variation of electrical conductivity in single finite element as function of time. The proposed methods calculate the sensitivity versus all finite elements in area of analysis at once. On the basis of sensitivity information the iterative algorithm for identification of shape and conductivity distribution of material flaws could be applied.