scholarly journals Efficiency of Cascaded Neural Networks in Detecting Initial Damage to Induction Motor Electric Windings

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1314
Author(s):  
Maciej Skowron ◽  
Teresa Orłowska-Kowalska
Keyword(s):  
Neural Networks ◽  
Induction Motor ◽  
High Efficiency ◽  
Supply Voltage ◽  
Frequency Converter ◽  
Damage Classification ◽  
Voltage Frequency ◽  
Rotor Winding ◽  
Cage Induction Motor ◽  
Diagnostic Software

This article presents the efficiency of using cascaded neural structures in the process of detecting damage to electrical circuits in a squirrel cage induction motor (IM) supplied from a frequency converter. The authors present the idea of a sequential connection of classic neural structures to increase the efficiency of damage classification and detection presented by individual neural structures, especially in the initial phase of single or multiple electrical failures. The easily measurable axial flux signal is used as a source of diagnostic information. The developed cascaded neural networks are implemented in the measurement and diagnostic software made in the LabVIEW environment. The results of the experimental research on a 1.5 kW IM supplied by an industrial frequency converter confirm the high efficiency of the use of the developed cascaded neural structures in the detection of incipient stator and rotor winding faults, namely inter-turn stator winding short circuits and broken rotor bars, as well as mixed failures in the entire range of changes of the load torque and supply voltage frequency.

The Influence of Supply Voltage Amplitude Variation Law on AC Induction Motor Efficiency in Variable-Speed Drive

2010 ◽  
Vol 164 ◽  
pp. 1-4 ◽  
Author(s):  
V. Bleizgys ◽  
A. Baskys
Keyword(s):  
Induction Motor ◽  
High Efficiency ◽  
Supply Voltage ◽  
Frequency Converter ◽  
Voltage Amplitude ◽  
Variable Speed ◽  
Amplitude Variation ◽  
Variable Speed Drive ◽  
Motor Efficiency ◽  
Ac Induction Motor

This paper presents investigation results of the influence of the supply voltage amplitude variation law on the efficiency of AC induction motor in variable-speed drive based on the frequency converter. It is demonstrated that the commonly employed linear and square voltage amplitude variation laws do not provide the highest efficiency of the AC induction motor. The corrected AC voltage amplitude variation dependences for different motor load torque, at which high efficiency of the motor supplied by the frequency converter is maintained, are proposed and discussed. Reported experimental study was performed on a special test bench.

scholarly journals Study and analysis the effect of variable applied voltage on SCIM performances based on FEA

2020 ◽  
Vol 11 (3) ◽  
pp. 1230
Author(s):  
Waleed Khalid Shakir Al-Jubori ◽  
Yasir Abdulhafedh Ahmed
Keyword(s):  
Steady State ◽  
Induction Motor ◽  
Applied Voltage ◽  
Supply Voltage ◽  
Finite Elements Analysis ◽  
Steady State Condition ◽  
Squirrel Cage ◽  
Voltage Variation ◽  
Three Phase ◽  
Cage Induction Motor

Study and analysis the effect of variable applied voltage on SCIM performances based on FEA is presented. Three phase squirrel cage induction motor SCIM has been investigated and numerically simulated using finite element method (FEM) with the aid of ANSYS software (RMxprt and Maxwell 2D/3D). This research presents study and analysis of the effects of the voltage variation on performance and efficiency of the three-phase induction motor of the squirrel cage type. The Finite Elements Analysis Method FEA is used as one of the best methods for analysis and simulation of electrical motors in addition to the possibility of dealing with nonlinear equations, Since the induction motor is a complex electromagnetic reaction, the researchers used the ANSYS program to represent and analyze the performance of the motor under variable supply voltage. The case studied in this research is three phases, 380V, 50Hz, 2.2kW, induction motor that widely use in industrial application. The aim of this research is to study the effect of voltage variation on efficiency, current value, power factor and torque of SCIM.  The RMxprt software has been used for modeling and simulating the induction motor and calculating the values of phases currents, input and output power in additional of overall efficiency at steady state condition. The next stage of the research is creating Maxwell 2-D design from the base model of RMxprt software, Maxwell 2-D model has the ability to computing the distribution of magnetic field and explaining the performance under steady-state operation. The obtained results show significant reduction of motor performance due to the effect of variation of apply voltage.

scholarly journals The model of double-cage induction motor for the analysis of thermal fields in transient operations

2017 ◽  
Vol 66 (2) ◽  
pp. 397-408 ◽  
Author(s):  
Jan Mróz
Keyword(s):  
Induction Motor ◽  
Supply Voltage ◽  
Thermal Fields ◽  
Squirrel Cage ◽  
Measurement Results ◽  
Network Method ◽  
Thermal Network Method ◽  
Cage Induction Motor ◽  
Transient Operations ◽  
Motor Model

AbstractEmergency motor switch-on happens occasionally while operating a doublesquirrel- cage motor at full supply voltage with the rotor blocked (e.g., in coal mills). After releasing the blockage, the by now heated motor is started up again. However, the mechanical stress caused by the increased temperature poses considerable hazards to the squirrel-cage winding. This paper presents a double-cage induction motor model for analysis of thermal fields in transient operation. The thermal field for the rotor of a doublesquirrel- cage motor of soldered or cast structure, operating in the conditions described, has been calculated in the present paper using a thermal network method. Measurement results have been presented for the double-squirrel-cage winding temperature for a soldered cage construction in the blocked rotor state.

scholarly journals Modeling of induction motor drive of a mine hoist on the basis of a doubly-fed electric machine

2021 ◽  
Vol 330 ◽  
pp. 03008
Author(s):  
Viktor Ostrovlyanchik ◽  
Ivan Popolzin ◽  
Vasiliy Kubarev ◽  
Dabin Qi
Keyword(s):  
Mathematical Model ◽  
Induction Motor ◽  
Supply Voltage ◽  
Frequency Converter ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Doubly Fed ◽  
Doubly Fed Machine ◽  
Mine Hoist ◽  
The Mathematical Model

One of the options for the modernization of existing hoist electric drives with a wound-rotor induction motor is its starting according to the scheme of a doubly-fed machine. For this purpose, a frequency converter with an adjustable amplitude, frequency and phase shift of the voltage at its output is connected to the motor rotor. At the same time, the problem of obtaining a mathematical model of both the double fed machine itself and the speed control system based on it is relevant due to the need to take into account the additional supply voltage in the differential equations drawn up in accordance with the Kirchhoff’s law for the stator and rotor windings. The paper proposes a structural diagram for the mathematical model of an induction motor drive of a hoist based on a doubly fed machine.

scholarly journals Evaluation of the behaviour of an induction motor for fan system under various external factors

2022 ◽  
Vol 1216 (1) ◽  
pp. 012007
Author(s):  
S Rachev ◽  
L Dimitrov
Keyword(s):  
Induction Motor ◽  
Supply Voltage ◽  
Electrical Power ◽  
Rotational Frequency ◽  
External Factors ◽  
State Regime ◽  
Process Observation ◽  
Cage Induction Motor ◽  
And Control ◽  
The Impact

Abstract Paper concerns a mathematical model developed for working process observation of a fan system squirrel-cage induction motor electric drive. The electric motor in question is designed for permanent, uninterruptible operation. The system of differential equations is converted and processed with the help of appropriate software. The impact of external factors is assessed – supply voltage deflection and variation of rates of mechanical quantities involved in the motion equation. Electrical power losses in steady-state regime and energy losses at start-up are calculated. The results obtained are practical oriented when considering methods to start and control the rotational frequency to imrove energy efficiency.

Induction Motor Drive Parameters Identification Applying Difference Schemes

2014 ◽  
Vol 698 ◽  
pp. 65-68 ◽  
Author(s):  
Eugene Bolovin ◽  
Alexander Glazyrin ◽  
Vladimir Polichshuk
Keyword(s):  
Induction Motor ◽  
Equation System ◽  
Difference Schemes ◽  
Parameters Identification ◽  
Total Delay ◽  
Equivalent Time ◽  
The Difference ◽  
Relative Errors ◽  
Rotor Winding ◽  
Cage Induction Motor

The authors have developed and tested by mathematical modeling the method of the induction motor parameters identification based on the difference schemes. When obtaining a difference equation system, the total delay time was taken to be equal to a quarter of a stator voltage period. The nonlinear predictive filtration was used to determine the expected value. The authors determined the estimators of rotor active resistance reduced to the stator; the rotor winding equivalent inductance; the stator winding equivalent inductance, the resulting inductance conditioned by the magnetic flux in the machine air gap; equivalent time constant for rotor circuit in the squirrel cage induction motor. The root mean square values of relative errors of parameters estimations total less than 4 %.

scholarly journals Effectiveness of Selected Neural Network Structures Based on Axial Flux Analysis in Stator and Rotor Winding Incipient Fault Detection of Inverter-fed Induction Motors

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2392 ◽  
Author(s):  
Maciej Skowron ◽  
Marcin Wolkiewicz ◽  
Teresa Orlowska-Kowalska ◽  
Czeslaw T. Kowalski
Keyword(s):  
Neural Network ◽  
Fault Detection ◽  
Induction Motor ◽  
Supply Voltage ◽  
Hopfield Network ◽  
Variable Load ◽  
Flux Analysis ◽  
Network Structures ◽  
Axial Flux ◽  
Rotor Winding

This paper presents a comparative study on the application of different neural network structures to early detection of electrical faults in induction motor drives. The diagnosis inference of the stator inter-turn short-circuits and broken rotor bars is based on the analysis of an axial flux of the induction motor. In order to automate the fault detection process, three different structures of neural networks were used: multi-layer perceptron, self-organizing Kohonen network and recursive Hopfield network. Tests were carried out for various levels of stator and rotor failures. In order to assess the sensitivity of the applied neural detectors, the tests were carried out for variable load conditions and for different values of the supply voltage frequency. Experimental results of the elaborated neural detectors are presented and discussed.

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