Novel approach using Hilbert Transform for multiple broken rotor bars fault location detection for three phase induction motor

2018 ◽  
Vol 80 ◽  
pp. 439-457 ◽  
Author(s):  
Mina B. Abd-el-Malek ◽  
Ahmed K. Abdelsalam ◽  
Ola E. Hassan
Keyword(s):  
Induction Motor ◽  
Hilbert Transform ◽  
Fault Location ◽  
Broken Rotor Bars ◽  
Novel Approach ◽  
Three Phase ◽  
Location Detection

scholarly journals Novel approach for SVPWM of two-level inverter fed induction motor drive

2020 ◽  
Vol 11 (4) ◽  
pp. 1750
Author(s):  
Olwi A. Elkholi ◽  
Mohamed A. Enany ◽  
Ahmed F. Abdo ◽  
Mahmoud Eid
Keyword(s):  
Induction Motor ◽  
Pulse Width Modulation ◽  
Frequency Converter ◽  
Harmonic Distortion ◽  
Motor Drives ◽  
New Approaches ◽  
Novel Approach ◽  
Three Phase ◽  
Dc Bus ◽  
Bus Voltage

<p class="Abstract">Due to their better DC bus utilization and easier digital realization, Space Vector Pulse Width Modulation (SVPWM) scheme is the most widely used PWM scheme. Also two level inverter is the traditional frequency converter because it has fewer components and is lower complex to control, but on the other hand it generates higher harmonic distortion. This paper presents the realization of novel SVPWM approaches applied to the three phase induction motor drives. Specifically various schemes are based on using more combinations of step operation in each cycle to approximate the reference vector, such as 24 and 48 step operations in each cycle. The basic principle of conventional SVPWM with different modulation index M is presented. The switching sequences of new approaches are described. The modulation signals waveforms, DC bus voltage utilization, De-rated motor torque, standard error of average torque, voltage and current harmonic of new approaches are analyzed by the MATLAB/SIMULINK software. The results confirms that 48 step SVPWM approach is the best compared to other approaches.</p>

scholarly journals Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniques

2010 ◽  
Vol 20 (3) ◽  
pp. 363-376 ◽  
Author(s):  
Rudra Dash ◽  
Bidyadhar Subudhi
Keyword(s):  
Fault Detection ◽  
Induction Motor ◽  
Fault Location ◽  
Single Phase ◽  
Fuzzy Inference ◽  
Induction Machine ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Three Phase ◽  
Fuzzy Techniques

Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniquesMotivated by the superior performances of neural networks and neuro-fuzzy approaches to fault detection of a single phase induction motor, this paper studies the applicability these two approaches for detection of stator inter-turn faults in a three phase induction motor. Firstly, the paper develops an adaptive neural fuzzy inference system (ANFIS) detection strategy and then compares its performance with that of using a multi layer perceptron neural network (MLP NN) applied to stator inter-turn fault detection of a three phase induction motor. The fault location process is based on the monitoring the three phase shifts between the line current and the phase voltage of the induction machine.

scholarly journals Broken Rotor Bars Fault Detection of The Three-phase Induction Motor(Arabic)

2012 ◽  
Vol 20 (5) ◽  
pp. 25-32
Author(s):  
Prof. B. M. Saied ◽  
Dr. Y. M.Y. Ameen ◽  
M. H. Saud
Keyword(s):  
Fault Detection ◽  
Induction Motor ◽  
Broken Rotor Bars ◽  
Three Phase
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