Magnetic fluid seals (MFS) are beginning to be used to seal rotating shafts in electric motors operating in conditions of high humidity, dust and pollution. Friction torque and heating are the most important operational indicators of MFS depending on the design parameters and operation conditions: rotation frequency, operation time, temperature and clearance (taking into account roughness and waviness). An urgent task is to study the influence of design parameters and operating conditions on the performance indicators of MFS of such electric motor shafts. The modeling of rough surfaces was performed using orthogonal transformations of roughness matrix vectors and a visual representation. The contact area of the magnetic fluid with rough surfaces was determined by mathematical modeling. The experimental studies were performed on a test bench. Wear sleeves and poles made of various steels with different roughness parameters were used. Models of MFS clearances formed by surfaces with different roughness have been obtained. The contact areas of the magnetic fluid with the surfaces of MFS at different roughness values have been determined. Nonlinear dependences and variation limits of the friction torque and MFS temperature on the surface roughness of the poles and sleeves, rotation frequencies of the electric motor, and the external temperature have been obtained. Clearance models allow determining the roughness of MFS surfaces. The developed experimental unit allows carrying out studies on the effect of changes of design parameters and operating conditions on the performance indicators of MFS. At a 5,21 time higher rotation frequency (from 556 to 2897 rpm), the MFS temperature can increase by up to 2 times, the friction torque – by up to 2,2 times. If the temperature rises by 50 оC, the friction torque can drop by up to 3 times. With an increase in the surface roughness from 0,357 to 7,21 μm, the temperature of the MFS can rise by 20 %, and the friction torque by 55 %.
When testing asynchronous machines, it is important to use energy-efficient methods, for example, the method of mutual loading of two machines with articulated shafts. One machine operates in the mode of the motor – frequency converter, the second machine operates in the mode of the generator – industrial frequency network. Both machines are simultaneously tested under load and energy costs for testing are reduced due to its recuperation. The method requires a correct loading algorithm. The modeling of the method based on chain models does not consider the implementation feature. Thus, it is advisable to refine the simulation of the asynchronous machine testing system by the mutual load method. The method is based on strict models considering the coupling of machine torque on a common shaft, the operation of machines in the mode of frequency converter, non-sinusoidal supply voltage, saturation of steel, displacement of current in conductors, for example, based on the associated analysis of electromagnetic fields in both machines. The authors have applied the packages of electromechanical units with electrical and mechanical Ansys Simplorer ports and finite element analysis of electromagnetic fields Ansys Maxwell for refined simulation of the asynchronous machine testing system by the method of mutual loading. Experimental studies of the system have been carried out on laboratory equipment using certified devices. A refined simulation of an energy-efficient testing system of asynchronous machines by the method of mutual loading has been carried out. It is based on calculations of the electromagnetic field and allows us to read the transient and steady-state modes of operation of a two-machine unit with a common shaft. An automated stand has been created that allows testing asynchronous machines by the method of mutual loading. The developed refined simulation of electromechanical processes in asynchronous machines during tests by the method of mutual loading with associated calculations of electromagnetic fields in both machines provides calculated results with an error of no more than 5–7 % in comparison with 40 % error of calculations in the transient modes of operation using chain models.
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