Method for Determining the Parameters of an Induction Motor

2021 ◽  
Vol 64 (1) ◽  
pp. 30-36
Author(s):  
Yuri Kulinich ◽  
◽  
Sergey Shuharev ◽  
Alexander Kaminsky ◽  
Sergey Kovalenko ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Induction Motor ◽  
Asynchronous Motor ◽  
Rotation Frequency ◽  
Engineering Practice ◽  
Experimental Stand ◽  
Electromagnetic Moment ◽  
Stable Part ◽  
Pie Chart ◽  
New Iterative Method

The paper proposes a new iterative method for determining the parameters of an induction motor. The method is based on the measured values of no-load current and active resistance of the stator winding. The calculated parameters are used to build the mechanical characteristics of the engine. To assess its accuracy, a comparative analysis with a pie chart was carried out. In the practical part of the work, on the basis of the experimental stand, measurements were made of the magnitude of the electromagnetic moment of the investigated asynchronous motor AIR71A4 at different values of the rotation frequency on the stable part of the mechanical characteristic. In a comparative analysis of the calculated and experimental data, it was found that the proposed method has sufficient accuracy in calculating the primary parameters of the engine. This provides a basis for the practical use of the proposed calculation method in engineering practice

scholarly journals Low Speed Estimation of Sensorless DTC Induction Motor Drive Using MRAS with Neuro Fuzzy Adaptive Controller

2018 ◽  
Vol 8 (5) ◽  
pp. 2691
Author(s):  
Mini R ◽  
Shabana Backer P. ◽  
B. Hariram Satheesh ◽  
Dinesh M. N
Keyword(s):  
Comparative Analysis ◽  
Induction Motor ◽  
Reactive Power ◽  
Adaptive Controller ◽  
Operating Conditions ◽  
Estimation Methods ◽  
Speed Estimation ◽  
Loop Model ◽  
Low Speed ◽  
Rotor Flux

<p>This paper presents a closed loop Model Reference Adaptive system (MRAS) observer with artificial intelligent Nuero fuzzy controller (NFC) as the adaptation technique to mitigate the low speed estimation issues and to improvise the performance of the Sensorless Direct Torque Controlled (DTC) Induction Motor Drives (IMD). Rotor flux MRAS and reactive power MRAS with NFC is explored and detailed analysis is carried out for low speed estimation. Comparative analysis between rotor flux MRAS and reactive power MRAS with PI as well as NFC as adaptive controller is performed and results are presented in this paper. The comparative analysis among these four speed estimation methods shows that reactive power MRAS with NFC as adaptation mechanism shows reduced speed estimation error and actual speed error at steady state operating conditions when the drive is subjected to low speed operation. Simulation carried out using MATLAB-Simulink software to validate the performance of the drive especially at low speeds with rated and variable load conditions.</p>

scholarly journals FLAT ASYNCHRONOUS ELECTRIC DRIVE OF STONE MILL

2019 ◽  
Vol 14 (2) ◽  
pp. 77-82
Author(s):  
Рустам Аипов ◽  
Rustam Aipov ◽  
Рустам Галиуллин ◽  
Rustam Galiullin ◽  
Раушан Нугуманов ◽  
...  
Keyword(s):  
Asynchronous Motor ◽  
Rotation Frequency ◽  
Point Of View ◽  
Working Zone ◽  
Electric Drives ◽  
Belt Drives ◽  
Asynchronous Electric Drive ◽  
Asynchronous Motors ◽  
Longitudinal Edge ◽  
Flour Production

In modern flour production, the preservation of all vitamins and minerals in it is relevant. Minerals and vitamins are stored in flour, ground from whole grains. In the stone mills, the grain is subjected to repeated exposure to the working surfaces of the millstones, as a result of which the flour contains a large percentage of the most important components of the grain. The stone mill’s drive should provide a low rotational speed of the mills (peripheral speed up to 10 m/sec.) and the possibility of smooth control of its speed and torque without reducing the performance of the mill. From this point of view, it is promising to use in the mill’s drive, instead of asynchronous motors, rotation with additional devices (gearboxes, belt drives, V-belt drives, etc.) of flat asynchronous electric drives. The article suggests possible variants of technical solutions for stone mills with flat electric drives. It was concluded that the use of a flat asynchronous motor in the mill’s drive allows not only smoothly adjusting the frequency and torque of the millstones, but also because of the presence of edge effects, to prevent flour sticking in the millstone working zone. Compiled with the possibility of solving by analytical methods a mathematical model of mill’s drive, based on a flat electric drives, taking into account the longitudinal edge effect, the strength of viscous (internal) and dry (external) friction. The mechanical characteristics of the drive were found when moving the flat electric drives inductors and the dependencies of the change in the mill productivity on the millstone rotation frequency when grinding various grains, changing the fill factor of the grinding zone and the gap between the millstones were obtained.

Detection of Stator and Rotor Faults in Asynchronous Motor Using Artificial Intelligence Method

2018 ◽  
pp. 278-285
Author(s):  
K. Vinoth Kumar ◽  
Prawin Angel Michael
Keyword(s):  
Induction Motor ◽  
Asynchronous Motor ◽  
Feed Forward Neural Network ◽  
Identification Scheme ◽  
Hardware System ◽  
Rotor Faults ◽  
Squirrel Cage ◽  
Three Phase ◽  
Neural Network Structure ◽  
Trained Network

This chapter deals with the implementation of a PC-based monitoring and fault identification scheme for a three-phase induction motor using artificial neural networks (ANNs). To accomplish the task, a hardware system is designed and built to acquire three phase voltages and currents from a 3.3KW squirrel-cage, three-phase induction motor. A software program is written to read the voltages and currents, which are first used to train a feed-forward neural network structure. The trained network is placed in a Lab VIEW-based program formula node that monitors the voltages and currents online and displays the fault conditions and turns the motor. The complete system is successfully tested in real time by creating different faults on the motor.

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