A Review of Application of Signal Processing Techniques for Fault Diagnosis of Induction Motors – Part I
J.
Faiz
School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran
author
A. M.
Takbash
Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada
author
E.
Mazaheri-Tehrani
School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran
author
text
article
2017
eng
Abstract - Use of efficient signal processing tools (SPTs) to extract proper indices for fault detection in induction motors (IMs) is the essential part of any fault recognition procedure. The Part1 of the two parts paper focuses on Fourier-based techniques including fast Fourier transform and short time Fourier transform. In this paper, all utilized SPTs which have been employed for fault fetection in IMs are analyzed in details. Then, their competency and their drawbacks for extracting indices in transient and steady state modes are criticized from different aspects. The considerable experimental results are used to certificate demonstrated discussion. Different kinds of faults, including eccentricity, broken bar and bearing faults as major internal faults, in IMs are investigated. The use of efficient signal processing tools (SPTs) to extract proper indices for faultdetection in induction motors (IMs) is the essential part of any fault recognition procedure. In thefirst part of the present paper, we focus on Fourier-based techniques, including fast Fourier transformand short time Fourier transform. In this paper, all utilized SPTs which have been employed forfault detection in IMs are analyzed in detail. Then, their competency and their drawbacks to extractindices in transient and steady state modes are criticized from different aspects. Different kinds offaults, namely, eccentricity, broken bar, and bearing faults as the major internal faults in IMs, areinvestigated.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
109
122
https://eej.aut.ac.ir/article_1970_041ac2f10d8a5a556c322789094e12d7.pdf
dx.doi.org/10.22060/eej.2017.13219.5142
Data Hiding Method Based on Graph Coloring and Pixel Block‘s Correlation in Color Image
G.
Ghadimi
Dept. of Electrical Engineering, Emam Ali University, Tehran, Iran
author
M.
Nejati Jahromi
Dept. of Electrical Engineering, Shahid Sattary Aeronautical University of Science and Technology, Tehran, Iran
author
E. Ghaemi
Ghaemi
Dept. of Electrical Engineering, Ahar University, Ahar, Iran
author
A. H.
Heydari
Department of Electrical and Electronic Engineering, Amirkabir University of Technology, Tehran, Iran
author
text
article
2017
eng
An optimized method for data hiding into a digital color image in spatial domainis provided. The graph coloring theory with different color numbers is applied. To enhance thesecurity of this method, block correlations method in an image is used. Experimental results showthat with the same PSNR, the capacity is improved by %8, and also security has increased in themethod compared with other methods. In the correlation block-based image method, data hidingcapacity of the host image varies according to image type and defined threshold level. In theproposed algorithm, during graph explanation, independent pixels placed side by side were colored.Then, based on “pixel block correlation data hiding” process is done. This method grows thesecurity and capacity of hiding process. Besides, this increases the effects of image format andcorrelation threshold on security and capacity.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
123
130
https://eej.aut.ac.ir/article_1048_dcbf57b70bbd41ddb2f69cc182ab5568.pdf
dx.doi.org/10.22060/eej.2017.10676.4868
Performance Analysis Of Mono-bit Digital Instantaneous Frequency Measurement (Difm) Device
Y.
Norouzi
Dept. of Elrctrical Engineering, Amirkabir University of Technology, Tehran, Iran
author
H.
Shahbazi
Dept. of Science and Research, Azad University, Tehran, Iran
author
S.
Mirzaei
Dept. of Elrctrical Engineering, Amirkabir University of Technology, Tehran,Iran
author
text
article
2017
eng
Instantaneous Frequency Measurement (IFM) devices are the essential parts of anyESM, ELINT, and RWR receiver. Analog IFMs have been used for several decades. However, thesedevices are bulky, complex and expensive. Nowadays, there is a great interest in developing a wideband, high dynamic range, and accurate Digital IFMs. One Digital IFM that has suitably reached allthese requirements is mono-bit zero-crossing IFM, made by some different producers at present. Inthis paper, the performance of mono-bit digital Instantaneous Frequency Measurement (IFM) deviceis analyzed. This analysis includes quantization error, thermal noise, clock jitter, comparator bias andalso “Pulse-on-Pulse” occurrence. The error limits due to all these factors are computed and analyzed,and a unified approach to the system design is presentedIn this paper, the performance of mono-bit digital Instantaneous frequency measurement (IFM) device is analyzed. This analysis includes quantization error, additive (thermal) noise, clock jitter, comparator bias and also “Pulse-on-Pulse” occurrence. The error limits due to all these factors are computed and analyzed, and a unified approach to the system design is presented
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
131
140
https://eej.aut.ac.ir/article_1985_ba25fee5986f35673c87c8b5e2ba10a2.pdf
dx.doi.org/10.22060/eej.2017.12155.5050
Cascaded Multilevel Inverters with Reduced Structures Based on a Recently Proposed Basic Units: Implementing a 147-level Inverter
M. J.
Mojibian
Department of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran
author
M.
Tavakoli Bina
Department of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran
author
B.
Eskandari
Department of Electrical Engineering, Malayer University, Malayer, Iran
author
text
article
2017
eng
A multilevel inverter is capable of generating high-quality stepwise pseudo-sinusoidalvoltage with low THD , applicable to high-power and high-voltage systems. These types of topologiesmay require a large number of switches and power supplies. This leads to much cost, large size, andcomplicated control algorithms. Thus, newer topologies are being proposed to decrease the numberof power electronic devices for a large number of levels in output voltage. Recently, a new multilevelinverter has been reported in the literature to reduce component count. Its structure requires a lowernumber of active switches as compared to the existing ones. The available literature presents ageneralization of the topology with an especial asymmetrical sources ratio, but no investigations aremade for other symmetrical or asymmetrical sources ratio with cascaded configurations. This studypresents a comprehensive analysis of cascaded topologies with the proposed basic units. The topologyis analysed for both symmetric and asymmetric DC source configurations. Also, two algorithms forasymmetric source configuration suitable for cascaded structures are proposed. Moreover, the designand simulation of a 147-level inverter are presented under an optimal number of DC sources and powerswitches. Furthermore, experimental validation is performed by implementing a laboratory prototype.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
141
150
https://eej.aut.ac.ir/article_964_e9d67543741c53cc60863075e0d9ba96.pdf
dx.doi.org/10.22060/eej.2017.11432.4967
Investigating Direct Torque Control of Six-Phase Induction Machines Under Open Phase Fault Conditions
R.
Kianinezhad
Department of Electrical Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
author
A.
Hajary
Department of Electrical Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
author
text
article
2017
eng
This paper presents analysis and evaluation of classical direct torque control(DTC), for controlling a symmetrical six phase induction motor (SPIM) under open phasefault conditions. The machine has two three-phase windings spatially shifted by 60 electricaldegrees. The strategy of the proposed method consists of choosing the switching modesaccording to the configuration of living phases in such a way that it generates vectors thathave higher amplitude in α-β plane while their projections on z axis give zero or near zeroamplitude vectors. The goal is reducing parasitic currents and torque ripples of SPIM underfaulty mode. Based on the theoretical analysis, it will be shown that in the open phase faultconditions, the only non-pulsating operation is obtained by opening the fault three-phasewinding. Experimental test results are provided o support theoretical analysis in open phasefault conditions for SPIM.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
151
160
https://eej.aut.ac.ir/article_1974_d089edf0b2460c10b04eb1be568c6025.pdf
dx.doi.org/10.22060/eej.2017.11535.4974
Optimization of Mixed-Integer Non-Linear Electricity Generation Expansion Planning Problem Based on Newly Improved Gravitational Search Algorithm
F .J.
Ardakani
Energy Research Center, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
author
M. M.
Ardehali
Energy Research Center, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
author
text
article
2017
eng
Electricity demand is forecasted to double in 2035, and it is vital to address the economicsof electrical energy generation for planning purposes. This study aims to examine the applicability ofGravitational Search Algorithm (GSA) and the newly improved GSA (IGSA) for optimization of themixed-integer non-linear electricity generation expansion planning (GEP) problem. The performanceindex of GEP problem is defined as the total cost (TC) based on the sum of costs for investment andmaintenance, unserved load, and salvage. In IGSA, the search space is sub-divided for escaping fromlocal minima and decreasing the computation time. Four different GEP case studies are considered toevaluate the performances of GSA and IGSA, and the results are compared with those from implementingparticle swarm optimization algorithm. It is found that IGSA results in lower TC by 7.01%, 4.08%,11.00%, and 6.40%, in comparison with GSA, for the four case studies. Moreover, as compared withGSA, the simulation results show that IGSA requires less computation time, in all cases.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
161
172
https://eej.aut.ac.ir/article_1959_2a71b0a0f931434f4c10a5974c3ff6e9.pdf
dx.doi.org/10.22060/eej.2017.12123.5041
Increasing Voltage Gain by New Structure of Inductive Switching DC-DC Converter
S.
Nabati
Department of Electrical Eng., Science and Research Branch, Islamic Azad University, Tehran, Iran
author
A.
Siadatan
Dept. of Electrical Eng., Faculty of Technical & Engineering, West Tehran Branch, Islamic Azad University, Tehran, Iran
author
S. B.
Mozafari
Department of Electrical Eng., Science and Research Branch, Islamic Azad University, Tehran, Iran
author
text
article
2017
eng
In a photovoltaic system, sun light energy is converted to electricity. The generatedelectricity has a low DC voltage. In order to increase voltage generated by photovoltaic cells (PV),an additive DC-DC converter is required to raise the low voltage to a good level which provides theconditions for connection to DC-DC converters. Low wastes, low costs, and high efficiency are someother specifications of such converters. This paper presents a new structure for an additive DC-DCconverter with inductive and capacitor switching for increasing high voltage gain to be used in PVsystem. It is based on the inductive and non-insulated switching which increases voltage in a duty cycleup to 10 times of input voltage. In addition, using a switch, low elements, and also low voltage stresson the switch is the advantage of this new setup. The easy increasing of levels to reach the highervoltages is another benefit of this structure. The paper continues with the analysis of circuit functionand PWM (Pulse Width Modulation) adjustments. PSCAD/EMTDC software is used for confirming theauthenticity of the performance of the suggested model. The results are presented.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
173
178
https://eej.aut.ac.ir/article_1047_6b99877c4800b8b9d799fd1bce29dc40.pdf
dx.doi.org/10.22060/eej.2017.11555.4978
Measurement and Computational Modeling of Radio-Frequency Electromagnetic Power Density Around GSM Base Transceiver Station Antennas
P.
Nassiri
Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
author
M.
Saviz
Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
author
M.
Helmi-kohnehShahri
Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
author
M.
Pourhosein
Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
author
R.
Divani
Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
author
text
article
2017
eng
Evaluating the power densities emitted by GSM1800 and GSM900 BTS antennas isconducted via two methods. Measurements are carried out in half a square meter grids around twoantennas. CST Microwave STUDIO software is employed to estimate the power densities in order fordetailed antenna and tower modeling and simulation of power density. Finally, measurements obtainedfrom computational and experimental methods were compared through the contour lines using thestatistical Surfer software. After measuring and simulating all values, it turns out that power density isgenerally lower than the permissible exposure limits although exceeds the limits in some sample points. According to the measurements, simulation error in stations GSM900 and GSM1800 are 10% and 8%,respectively. Findings from contour-line-maps illustrates that direct measurement method follows thesame emission pattern as the computational method does. It validates the computational approach andthe models attained for BTS power density estimation.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
179
186
https://eej.aut.ac.ir/article_1969_490c4f2ca8f97d93b92cabc1091d926e.pdf
dx.doi.org/10.22060/eej.2017.12018.5026
Combination of Transformed-means Clustering and Neural Networks for Short-Term Solar Radiation Forecasting
M.
Ghayekhloo
Young Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin, Iran
author
M. B.
Menhaj
Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
author
text
article
2017
eng
In order to provide an efficient conversion and utilization of solar power, solar radiation datashould be measured continuously and accurately over the long-term period. However, the measurement ofsolar radiation is not available to all countries in the world due to some technical and fiscal limitations. Hence,several studies were proposed in the literature to find mathematical and physical models to estimate andforecast the amount of solar radiation such as stochastic prediction models based on time series methods. Thispaper proposes a hybridization framework, considering clustering, pre-processing, and training steps for shorttermsolar radiation forecasting. The proposed method is a combination of a novel data clustering method,time-series analysis, and multilayer perceptron neural network (MLPNN). The proposed Transformed-Means clustering method is based on inverse data transformation and K-means algorithm that presents moreaccurate clustering results when compared to the K-Means algorithm; its improved version and also otherpopular clustering algorithms. The performance of the proposed Transformed-Means is evaluated usingseveral types of datasets and compared with different variants of K-means algorithm. The proposed methodclusters the input solar radiation time-series data into an appropriate number of sub-datasets which are thenpreprocessed by the time-series analysis. The preprocessed time-series data provide the input for the trainingstage where MLPNN is used to forecast the solar radiation. Solar time-series data with different solar radiationcharacteristics are also used to determine the accuracy and the processing speed of the developed forecastingmethod with the proposed Transformed-Means and other clustering techniques.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
187
194
https://eej.aut.ac.ir/article_942_8c27e9fa2507f7e0a9a8490a7f9a4497.pdf
dx.doi.org/10.22060/eej.2017.12487.5077
Implementation of a Low- Cost Multi- IMU by Using Information Form of a Steady State Kalman Filter
A. M.
Shahri
Department of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Tehran, Iran
author
R.
Rasoulzadeh
Department of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Tehran, Iran
author
text
article
2017
eng
In this paper, a homogenous multi-sensor fusion method is used to estimate the trueangular rate and acceleration with a combination of four low cost (< 10$) MEMS Inertial MeasurementUnits (IMU). An information form of steady state Kalman filter is designed to fuse the output of four lowaccuracy sensors to reduce the noise effect by the square root of the number of sensors. A hardware isimplemented to test the method with three types of experiments: static test, constant rate, and oscillatingtest. Results of static test for z-axis show that ARW coefficient reduces to 0.0022°/√s and VRW error isdecreased by %50. Also, dynamic test results show the reduction of the standard deviation of combinedrate signal up to six times compared with a single sensor. A comparison between the proposed filter andthe simple averaging method is made in which the results indicate that the Kalman filter is more accuratecompared to the averaging method.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
195
204
https://eej.aut.ac.ir/article_1972_38ceb31639cc65cc871f53c941bb3f05.pdf
dx.doi.org/10.22060/eej.2017.12045.5028
Internal Fault Detection, Location, and Classification in Stator Winding of the Synchronous Generators Based on the Terminal Voltage Waveform
M.
Fayazi
Dept. of Electrical Engineering, Shahid Beheshti University, Tehran, Iran
author
F.
Haghjoo
Dept. of Electrical Engineering, Shahid Beheshti University, Tehran, Iran
author
text
article
2017
eng
In this paper, a novel method is presented for detection and classification of the faultyphase/region in the stator winding of synchronous generators on the basis of the resulting harmoniccomponents that appear in the terminal voltage waveforms. Analytical results obtained through DecisionTree (DT) show that the internal faults are not only detectable but also they can be classified andthe related region can be estimated. Therefore, this scheme can be used to protect the synchronousgenerators against the various internal faults. Fuji technical documents and data sheets for an actualsalient pole synchronous generator (one unit of an Iran’s hydroelectric power plants) are used for themodeling. Simulations in Maxwell software environment are presented. All the related parameters, suchas B-H curve, unsymmetrical air gap and pole saliency, slot-teeth effect, and other actual parameters, areconsidered to obtain a comprehensive model to generate acceptable terminal voltage waveforms withoutany simplification.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
205
214
https://eej.aut.ac.ir/article_1977_11740ac95bc98317614f241d4faf020e.pdf
dx.doi.org/10.22060/eej.2017.12131.5043
K-Complex Detection Based on Synchrosqueezing Transform
Z.
Ghanbari
Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
author
M. H.
Moradi
Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
author
text
article
2017
eng
K-complex is an underlying pattern in the sleep EEG. Due to the role of sleep studies inneurophysiologic and cognitive disorders diagnosis, reliable methods for analysis and detection of this patternare of great importance. In our previous work, Synchrosqueezing Transform (SST) was proposed for analysisof this pattern. SST is an EMD-like tool, which benefits from wavelet transform and reallocation approaches.This method is able to decompose signals into their time-varying oscillatory ingredients. In addition, itprovides a time-frequency representation with less blurring compared to wavelet transform. In this paper,firstly, the ability of SST is investigated by applying the ANOVA test, which is approved by proper p-values.This paper proposes SST for K-complex detection. The proposed method is based on a so-called “detectionof K-complexes and sleep spindles” (DETOKS) framework. DETOKS is based on spares optimizationand decomposes signals into four components, namely transient, low frequency, oscillatory, and a residual.Applying the Teager-Kaiser energy operator and setting a threshold on the low-frequency component resultin K-complex detection. We modify DETOKS using SST. The proposed method is applied to DREAMSdataset. The dataset provides two visual scorings accompanied by an automatic one. As the visual labels wereextremely different, the automatic detection is considered as the third expert’s scoring and data is re-labeledby a voting approach among three experts. For DETOKS, DETOKS modified by CWT, and the proposedmethod, MCC measure is 0.62, 0.71, and 0.76, respectively. It shows superiority of the proposed method.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
214
222
https://eej.aut.ac.ir/article_1973_d79c497bc933dd892d0446093bb36060.pdf
dx.doi.org/10.22060/eej.2017.12577.5096
Combination of Feature Selection and Learning Methods for IoT Data Fusion
V.
Sattari-Naeini
Dept. of Computer Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
author
Zahra
Parizi-Nejad
Dept. of Computer Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
author
text
article
2017
eng
In this paper, we propose five data fusion schemes for the Internet of Things (IoT) scenario,which are Relief and Perceptron (Re-P), Relief and Genetic Algorithm Particle Swarm Optimization (Re-GAPSO), Genetic Algorithm and Artificial Neural Network (GA-ANN), Rough and Perceptron (Ro-P)and Rough and GAPSO (Ro-GAPSO). All the schemes consist of four stages, including preprocessingthe data set based on curve fitting, reducing the data dimension and identifying the most effective featuresets according to data correlation, training classification algorithms, and finally predicting new databased on classification algorithms. The results derived from five compound schemes are investigated andcompared with each other with three metrics, namely, Quality of Train (QoT) Accuracy (Ac) and StorageCapacity (SC). While the Re-P scheme is only capable of separating classes that are linearly separable,Re-GAPSO one is a dynamic method, appropriate for constantly changing problems of the real life. Onthe other hand, GA-ANN is a Wrapper method and despite Relief can adapt itself to the machine learningalgorithm. Meanwhile, Ro-P scheme is useful for analyzing vague and imprecise information and, unlikeGA-ANN, has less calculative costs. Among these five schemes, Ro-GAPSO is a more precise one, whichhas less calculative cost and does not become stuck in local minima. Experimental results show that Re-Poutperforms other proposed and existing methods in terms of computational time complexity.
AUT Journal of Electrical Engineering
Amirkabir University of Technology
2588-2910
49
v.
2
no.
2017
223
232
https://eej.aut.ac.ir/article_1960_5b7511e4f87d3b6a9eb1a6bc95cececc.pdf
dx.doi.org/10.22060/eej.2017.12151.5046