Three-phase Induction Motor Operation Trend Prediction Using Support Vector Regression for Condition-based Maintenance

2006 ◽  
Author(s):  
Yanfeng Li ◽  
Haibin Yu
Keyword(s):  
Support Vector Regression ◽  
Induction Motor ◽  
Condition Based Maintenance ◽  
Support Vector ◽  
Trend Prediction ◽  
Three Phase ◽  
Motor Operation

scholarly journals Robust Speed Control of a Three Phase Induction Motor Using Support Vector Regression

2021 ◽  
Vol 11 (6) ◽  
pp. 7861-7866
Author(s):  
N. H. Mugheri ◽  
M. U. Keerio ◽  
S. Chandio ◽  
R. H. Memon
Keyword(s):  
Support Vector Regression ◽  
Induction Motor ◽  
High Efficiency ◽  
Speed Control ◽  
Pi Controller ◽  
Learning Ability ◽  
Maintenance Cost ◽  
Support Vector ◽  
Three Phase ◽  
Speed Response

The Three Phase Induction Motor (TIM) is one of the most widely used motors due to its low price, robustness, low maintenance cost, and high efficiency. In this paper, a Support Vector Regression (SVR) based controller for TIM speed control using Indirect Vector Control (IVC) is presented. The IVC method is more frequently used because it enables better speed control of the TIM with higher dynamic performance. Artificial Neural Network (ANN) controllers have been widely used for TIM speed control for several reasons such as their ability to successfully train without prior knowledge of the mathematical model, their learning ability, and their fast implementation speed. The SVR-based controller overcomes the drawbacks of the ANN-based controller, i.e. its low accuracy, overfitting, and poor generalization ability. The speed response under the proposed controller is faster in terms of rising and settling time. The dynamic speed response of the proposed controller is also superior to that of the ANN-PI controller. The performance of the proposed controller was compared for TIM speed control with an ANN-PI controller via simulations in SIMULINK.

scholarly journals Modeling of three-phase electric motor operation by the MATLAB system with deteriorated power quality in the 0.38 kV distribution networks

2018 ◽  
Vol 58 ◽  
pp. 03016 ◽  
Author(s):  
I.V Naumov ◽  
N.V. Savina ◽  
M.V. Shevchenko
Keyword(s):  
Induction Motor ◽  
Power Quality ◽  
Electric Motor ◽  
Distribution Networks ◽  
Negative Sequence ◽  
Operation Modes ◽  
Three Phase ◽  
Sequence Components ◽  
Motor Operation ◽  
The Impact

One of the main operation modes that characterizes power quality in distribution networks is asymmetry of three-phase voltage system. Operation of an induction motor (IM) with disturbed voltage symmetry in the supply network can not be considered as a rated one. The system of voltages applied to the stator winding of IM under these conditions contains positive- and negative-sequence components. This worsens the performance characteristics of IM essentially. In order to balance the 0.38 kV network operation and enhance the efficiency of the three-phase electric motor operation it is suggested to use a special balancing unit (BU) that minimizes the negative-sequence components of current and voltage. The operation modes of the obtained system “supply source – induction motor – balancing unit” are simulated within the MATLAB software package of applied programs, which allows one to assess the impact of low quality of power on the operating characteristics of the electric motor and the efficiency of the balancing unit to increase the “durability” of the motor under the asymmetrical power consumption.

Z-Source Inverter Fed Induction Motor Drive Control Using Hybrid Methodology

2017 ◽  
Vol 27 (03) ◽  
pp. 1850042 ◽  
Author(s):  
S. Mythili ◽  
K. Thiyagarajah
Keyword(s):  
Induction Motor ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Drive System ◽  
Voltage Source ◽  
Support Vector ◽  
Motor Drive ◽  
Hybrid Technique ◽  
Induction Motor Drive ◽  
Three Phase

In this paper, a hybrid technique is proposed for controlling the [Formula: see text]-source inverter fed induction motor drive system. The hybrid technique is the combination of the gravitational search algorithm (GSA) and the support vector machine (SVM), which is utilized to improve the performance of the induction motor (IM). The novelty of the study is to control the [Formula: see text]-Source Inverter for improving the stability and performance of the IM drive system with the help of the proposed hybrid technique. Subsequently, the total harmonic distortion (THD) is decreased and the oscillation period of the stator current, torque and speed are eliminated. The inputs of the proposed technique are motor speed and reference speed. The output of the proposed system is reference quadrature axis current. Moreover, the PI controller is optimized for getting an optimal result to produce reference quadrature axis current. After that, the SVM is used to predict the control pulses of voltage source inverter. Here, the three-phase reference current is used to generate the accurate control pulses. In three-phase reference current, SVM is trained by the input motor quadrature axis current and the reference quadrature axis current with the associated target reference. The proposed technique is implemented in the MATLAB/simulink platform. The performance of the proposed method is determined and compared with the existing methods such as PSO-SVM and SVM methods.

scholarly journals Estimation of Stator Winding Temperature of a Three-Phase Induction Motor

2019 ◽  
pp. 9-17
Keyword(s):  
Induction Motor ◽  
Stator Winding ◽  
Squirrel Cage ◽  
Software Methodology ◽  
Software Packages ◽  
Three Phase ◽  
Network Method ◽  
Thermal Network Method ◽  
Motor Operation ◽  
Good Agreement

This paper adopted a thermal network method (TNM) based on Motor-CAD with MATLAB/Simulink software, and finite element method (FEM) based on Motor- CAD with Flux2D software, to estimate the stator winding temperature of a totally enclosed fan-cooled (TEFC), squirrel cage, three-phase induction motor. The three software packages were adopted successfully with a good agreement among their results resulting in preferring using Motor-CAD in obtaining results, and using Flux2D with MATLAB to validate these results. The success of triple-software methodology will give the induction motor designer a well-validated tool in attaining a safe motor operation without exceeding the maximum allowable stator winding temperature rise, and without using an experimental test based on an expensive manufacturing motor.

Detection of Deterioration of Three-phase Induction Motor using Vibration Signals

2019 ◽  
Vol 19 (6) ◽  
pp. 241-249 ◽  
Author(s):  
Adam Glowacz ◽  
Witold Glowacz ◽  
Jarosław Kozik ◽  
Krzysztof Piech ◽  
Miroslav Gutten ◽  
...  
Keyword(s):  
Induction Motor ◽  
Nearest Neighbor ◽  
Recognition Rate ◽  
Vibration Signal ◽  
Diagnostic Techniques ◽  
Support Vector ◽  
Vibration Signals ◽  
Linear Discriminant ◽  
Three Phase ◽  
Vector Sum

Abstract Nowadays detection of deterioration of electrical motors is an important topic of research. Vibration signals often carry diagnostic information of a motor. The authors proposed a setup for the analysis of vibration signals of three-phase induction motors. In this paper rotor fault diagnostic techniques of a three-phase induction motor (TPIM) were presented. The presented techniques used vibration signals and signal processing methods. The authors analyzed the recognition rate of vibration signal readings for 3 states of the TPIM: healthy TPIM, TPIM with 1 broken bar, and TPIM with 2 broken bars. In this paper the authors described a method of the feature extraction of vibration signals Method of Selection of Amplitudes of Frequencies – MSAF-12. Feature vectors were obtained using FFT, MSAF-12, and mean of vector sum. Three methods of classification were used: Nearest Neighbor (NN), Linear Discriminant Analysis (LDA), and Linear Support Vector Machine (LSVM). The obtained results of analyzed classifiers were in the range of 97.61 % – 100 %.

A method for real-time wireless monitoring of the efficiency and conditions of three-phase induction motor operation

2018 ◽  
Vol 157 ◽  
pp. 70-82 ◽  
Author(s):  
Daniel P. de Carvalho ◽  
Fernando B. Silva ◽  
Wagner E. Vanço ◽  
Felipe A. da Silva Gonçalves ◽  
Carlos A. Bissochi ◽  
...  
Keyword(s):  
Real Time ◽  
Induction Motor ◽  
Wireless Monitoring ◽  
Three Phase ◽  
Motor Operation
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