Original Research Paper
Nonlinear System
A.R. Ghomi Taheri; F. Setoudeh; M. B. Tavakoli
Abstract
Background and Objectives: The Differential transform method (DTM) is used in the analysis of ordinary, partial, and high-order differential equations. Recently, the DTM is used in the nonlinear analysis of physical nonlinear dynamic systems.Methods: The DTM method is used to analyze and analytically ...
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Background and Objectives: The Differential transform method (DTM) is used in the analysis of ordinary, partial, and high-order differential equations. Recently, the DTM is used in the nonlinear analysis of physical nonlinear dynamic systems.Methods: The DTM method is used to analyze and analytically solve the nonlinear mathematical model of bias current-controlled Colpitts oscillator with variable coefficients. Intervals of the validity of the proposed method are evaluated by using the fourth order Runge-Kutta method (RK4M). In this note, the Lyapunov exponent (LE) can be used to analyze the Colpitts oscillator. By using DTM, the LEs are calculated analytically with unknown parameters in a short interval of time t[0, 3 Sec]. Results: In this paper, intervals of the validity of the proposed method are evaluated using RK4M. In addition, LEs are calculated using analytical and numerical methods based on DTM technique and Wolf method, respectively. LEs of the proposed system are presented as a function of the control parameter to confirm the applied technique’s usefulness. Conclusion: By comparing these two methods, the proposed DTM analytical technique is relatively more precise. Simulation results confirmed the impact of different parameters on LEs with two different initial conditions. The results show good accuracy of the DTM in short time intervals t[0, 3 Sec].
Original Research Paper
Control
S. Khodakaramzadeh; M. Ayati; M. R. Haeri Yazdi
Abstract
Background and Objectives: Designing a terminal sliding mode observer (TSMO) in order to estimate the potential faults in a wind turbine with a doubly fed induction generator (DFIG) has been studied in previous research works. In this paper, a method for fault detection of a permanent magnet synchronous ...
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Background and Objectives: Designing a terminal sliding mode observer (TSMO) in order to estimate the potential faults in a wind turbine with a doubly fed induction generator (DFIG) has been studied in previous research works. In this paper, a method for fault detection of a permanent magnet synchronous generator (PMSG) wind turbine using a TSMO is developed.Methods: The wind turbine (WT) dynamic model including, blades, drive train, PMSG, maximum power capture controller, and pitch controller is linearized around its equilibrium point and is simulated in MATLAB Simulink. A PID controller is designed for capturing the maximum power from wind. Also, a PI controller is designed in order to control the pitch angle. In this research, the blade imbalance fault (BIF), which is due to the difference between turbine blades’ mass distribution, is investigated. This fault may happen over time and causes rotor mass imbalance that leads to vibrations in the generator’s shaft rotating speed. A fault detection system (FDS) is proposed using a terminal sliding mode observer in order to diagnose the BIF. Results: Using the designed TSMO, the estimation errors of not only measured states but also unmeasured states converge to zero in finite time. This leads to the fast action of the FDS before a failure happens. Using the proposed FDS, the states and fault are estimated such that the estimation errors of states and the fault converge to zero in 0.035 seconds.Conclusion: The convergence of state estimation errors to zero in finite time, which is verified by simulation results, satisfies the authors’ expectation that using TSMO, the estimation errors of both output and non-output states converge to zero in finite time.
Original Research Paper
Analogue Integrated Circuits
F. Shakibaee; A. Bijari; S.H. Zahiri
Abstract
Background and Objectives: Comparators play a critical role in the analog to digital converters (ADCs) and digital to analog converters (DACs). So, different structures have been proposed to improve their performance. Power, delay, offset, and noise are the important factors that have significantly affect ...
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Background and Objectives: Comparators play a critical role in the analog to digital converters (ADCs) and digital to analog converters (DACs). So, different structures have been proposed to improve their performance. Power, delay, offset, and noise are the important factors that have significantly affect the comparator’s performance. In low power applications, power consumption and delay are the critical concerns that should be minimized to obtain better performance. In this work, a low-power and high-speed comparator has been proposed, which is suitable for applications operating at a low power supply.Methods: Based on the conventional structure of the comparator, some modifications are implemented to achieve better performance in terms of power consumption and delay. Additionally, the proposed structure gives great performance when the difference of inputs is very small. To verify the proposed structure, it is designed and simulated in a 0.18 μm CMOS technology with a power supply of 1 V and sampling frequency of 2 MHz.Results: To draw a fair comparison, the conventional and proposed structure is simulated in equal circumstance. The size of transistors is designed with appropriate W/L ratios to achieve appropriate performance. The proposed structure not only reduces the power consumption by 44%, but also it decreases the delay by 9.1%. The power consumption of the proposed structure is around 0.12 µw. The total occupied area by the proposed structure is approximately 127.44 µm2.Conclusion: In this paper, we presented a delay analysis for the proposed dynamic comparator. Also, based on theoretical analyses, a new dynamic comparator consumes less power and operates faster compared with the conventional structure. The simulation results verify the theoretical analysis.
Original Research Paper
Microphone Array Processing
M. Kalantari
Abstract
Background and Objectives: One major problem in the minimum power distortionless response (MPDR) beamformer is the signal cancellation problem, i.e., the desired signal is canceled by the reflected signal, even though the distortionless response constraint is satisfied. Solving this problem is the objective ...
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Background and Objectives: One major problem in the minimum power distortionless response (MPDR) beamformer is the signal cancellation problem, i.e., the desired signal is canceled by the reflected signal, even though the distortionless response constraint is satisfied. Solving this problem is the objective of this paper. Methods: It is well known that the signal cancellation problem can be avoided by minimizing the cross-spectrum matrix of noise, i.e., using the minimum variance distortionless response (MVDR) beamformer. But, in the case of disturbance signals which have correlation with the desired signal, estimation of this matrix is a challenging problem. In this paper we propose an approach for estimating the cross-spectrum matrix of noise signal from which we can solve the signal cancellation problem. Results: Simulation examples show that using the proposed method we can bypass the signal cancellation problem completely. Conclusion: A common belief is that in the case of a disturbance that is a reflected version of the desired signal, due to cohesive appearance and disappearance of both the disturbance and the desired signal, the estimation of cross-spectrum matrix of noise signal is typically not possible in practice. So, based on this common belief, we can’t use the MVDR beamformer in this case. In this paper, we show that this common belief is a fault. We propose a general approach for estimating the cross-spectrum matrix of noise signal that is applicable even in the case of correlated disturbances.
Original Research Paper
Power Systems
H. Sahraei; M. Tolou Askari
Abstract
Background and Objectives: With the ever-increasing growth of electric loads, the need for generating electric power grows correspondingly. By considering the limitations of power generation, utilizing novel technologies has gained persistent momentum, one of which is deploying Phase-Shifting Transformers ...
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Background and Objectives: With the ever-increasing growth of electric loads, the need for generating electric power grows correspondingly. By considering the limitations of power generation, utilizing novel technologies has gained persistent momentum, one of which is deploying Phase-Shifting Transformers (PSTs). Among the more important available relays for the transmission lines are Distance Relays. To this end, Distance Relays measure the voltage and current of the transmission line in its final installation location. On the other hand, the existence of Phase-Shifting Transformers on transmission lines alters the voltage and current signals at the relay location. This issue causes the impedance calculated by the relay to differ from its actual value at the fault location. As a result, the relay detects the fault location falsely, or in some cases does not recognize it at all.Methods: The effect of phase shifting transformer on the relay performance of the distances has been investigated in this study. Furthermore, the digital distance relays are modeled in a software environment and its validity is investigated through analytical relationships. Next, the efficacy of the transformer on distance protection is analytically studied. Finally, a new method has been proposed to improve distance relay performance.Results: Results from analysis and modelling shows that the effect of phase shifting transformers in relay-computed impedance has two faces, the first of which is related to the internal impedance of the transformer, while the other regards the serial voltage of the transformer. The latter face is much more influential than the former one. Conclusion: This fact renders the mere inner Impedance of phase-shifting transformer insufficient for using it to eliminate its effect. To this end, a method has been developed in which the voltages of both ends of the phase shifting transformer are measured by the PMUs and then sent to the facility for protecting power system after synchronization. There, this voltage is reduced from the voltage calculated by the relay, which renders the effect of the phase shifting transformer in the impedance calculated by the relay completely eliminated.
Original Research Paper
Photonics
F. Parandin
Abstract
Background and Objectives: Universal NOR gate is one of the most important gates in digital design. The all-optical NOR gate can be designed using photonic crystals. These types of gates have a small size and can be integrated.Methods: In this paper, an optical NOR gate is designed based on 2D photonic ...
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Background and Objectives: Universal NOR gate is one of the most important gates in digital design. The all-optical NOR gate can be designed using photonic crystals. These types of gates have a small size and can be integrated.Methods: In this paper, an optical NOR gate is designed based on 2D photonic crystals. A square lattice has been used to design this structure. This logic gate has two main inputs, a bias input and an output. Because the output of the NOR gate must be “1” for zero inputs, a bias input is required. A combination of linear and point defects has also been used to create waveguides. Results: One of the characteristics of this structure is its small size for use in optical integrated circuits. The use of a small number and simple point defects makes the design of this gate easier. The obtained delay time for this gate is 0.06ps. Due to these features, this gate can be used in high-speed optical integrated circuits.Conclusion: In this paper, an all-optical NOR logic gate is designed and simulated using photonic crystals. The use of a small number of point defects has reduced the delay time of this gate. The proposed NOR gate can be used in high-speed optical integrated circuits.
Original Research Paper
Image Processing
A. Fallah; A. Soliemani; H. Khosravi
Abstract
Background and Objectives: Lane detection systems are an important part of safe and secure driving by alerting the driver in the event of deviations from the main lane. Lane detection can also save the lifes of car occupants if they deviate from the road due to driver distraction.Methods: In this paper, ...
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Background and Objectives: Lane detection systems are an important part of safe and secure driving by alerting the driver in the event of deviations from the main lane. Lane detection can also save the lifes of car occupants if they deviate from the road due to driver distraction.Methods: In this paper, a real-time and illumination invariant lane detection method on high-speed video images is presented in three steps. In the first step, the necessary preprocessing including noise removal, image conversion from RGB colour to grey and the binarizing input image is done. Then, a polygon area as the region of interest is chosen in front of the vehicle to increase the processing speed. Finally, edges of the image in the region of interest are obtained with edge detection algorithm and then lanes on both sides of the vehicle are identified by using the Hough transform.Results: The implementation of the proposed method was performed on the IROADS database. The proposed method works well under different daylight conditions, such as sunny, snowy or rainy days and inside the tunnels. Implementation results show that the proposed algorithm has an average processing time of 28 milliseconds per frame and detection accuracy of 96.78%.Conclusion: In this paper a straightforward method to identify road lines using the edge feature is described on high-speed video images. ======================================================================================================Copyrights©2021 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.======================================================================================================
Original Research Paper
Object Tracking
E. Pazouki; M. Rahmati
Abstract
Background and Objectives: Object tracking in video streams is one of the issues in machine vision that has many applications. Depending on the type of the object, the number of objects and other inputs used in tracking, object tracking is divided into several different categories. Multi-object tracking ...
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Background and Objectives: Object tracking in video streams is one of the issues in machine vision that has many applications. Depending on the type of the object, the number of objects and other inputs used in tracking, object tracking is divided into several different categories. Multi-object tracking in a camera network is one of the most complex types of object tracking. In this type of tracking, the goal of the algorithm is to extract the persistent trace of several objects moving simultaneously in a wide area that is monitored by a network of cameras. This type of tracking is often done in two steps. In the first step, the traces of each object in each camera is called tracklets are extracted. Then, the persistent trace of the objects are obtained by associating the extracted tracklets of all cameras in the monitored wide area. Here, we introduce a novel variational approach based on the deep features to associate the tracklets.Methods: For this purpose a variational model with multiphase level set representation is introduced. The persistent trace of all objects are obtained by optimizing the proposed variational model. The proposed variational model is optimized by employing the Euler-Lagrange equation. CNN and deep learning are used to extract the deep features of appearance and motion of objects. Here, a ResNet50 network that is pre-trained on ImageNet and a transformer neural network which is trained with motion parameters of tracklets such as acceleration and orientation change rate are used for extracting deep features.Results: The results on the three well-known datasets which are real and a synthesized dataset show that the proposed model takes competitive performance, while using less extra context information of the camera network and objects, compared to the other proposed methods. The evaluations show the quality of the proposed model in solving complex problems using the minimum required initial knowledge.Conclusion: The multiphase model using deep features presented in this paper provide 9% better results than the multiphase model without deep features based on TCF and FS metrics and 8% better results based on MT metric.
Original Research Paper
Nonlinear Control
N. Ghaffari; A. Zakipour; M. Salimi
Abstract
Background and Objectives: In this paper, a novel approach for regulation of the output current in the grid-connected three-level flying capacitor inverter is presented by using the sliding mode (SM) method. In the proposed method, it is possible to control the active and reactive components of the inverter ...
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Background and Objectives: In this paper, a novel approach for regulation of the output current in the grid-connected three-level flying capacitor inverter is presented by using the sliding mode (SM) method. In the proposed method, it is possible to control the active and reactive components of the inverter output current independently, and therefore it can be employed for grid connection of the renewable energy resources or for harmonic and reactive power compensation of the local loads. The designed controller uses an external loop to control the voltage of the inverter DC link and has a constant switching frequency. The stability of the proposed method has also been proved by using the Lyapunov stability theory. The simulation results show that in different operating conditions, the proposed controller has a stable and robust response.Methods: Grid-connected three-level flying capacitor inverter is modeled by using averaged state space technique. Considering nonlinearity of the obtained model, an equivalent SM controller is developed for output current control of the multilevel grid connected inverter. To improve robustness and stability of the system against uncertainty of model parameters, a nonlinear component is added to the equivalent controller. Results: The proposed controller enjoys very fast dynamic response, so it can be employed in wide ranges of application e.g. reactive compensation and harmonic mitigation modes. In active power filtering operation, it is able to eliminate harmonic components of the grid from 20.61% to 1.34% which is compatible with IEEE and IEC standards.Conclusion: The stability of the proposed method has also been proved by using the Lyapunov stability theory. The simulation results show that in different operating conditions, the proposed controller has a stable and robust response.
Original Research Paper
Geographic Information System
E. Norouzi; S. Behzadi
Abstract
Background and Objectives: Climate phenomena such as quantity of surface evaporation are affected by many environmental factors and parameters, which makes modeling and data mining difficult. On the other hand, the estimation of surface evaporation for a target station can be difficult as a result of ...
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Background and Objectives: Climate phenomena such as quantity of surface evaporation are affected by many environmental factors and parameters, which makes modeling and data mining difficult. On the other hand, the estimation of surface evaporation for a target station can be difficult as a result of partial or complete lack of local meteorological data under many conditions. In this regard, satellite imagery can play a special role in modeling and data mining of climatic phenomena, because of their significant advantages, including availability and their potential analysis. Therefore, addressing the improvement and expansion of machine learning methods and modeling algorithms along with remote sensing data is inevitable.Methods: In this research, we intend to study the ability of 11 machine-learning modeling algorithms to model data and surface evaporation phenomena using satellite imagery. We used two methods to prepare the database: PCA and its opposite method using standard deviation and correlation.Results: The calculation of the Root Mean Squared Error (RMSE) indicated that, in general, the use of the PCA method has a better result in preparing and reducing the dimensions of large databases for all methods of machine learning. The SEGPR model was ranked first with the least error (93.49%) in the Principal Component Analysis (PCA) method, and the Artificial Neural Network (ANN) model performed well in both data preparation methods (93.42, 93.38), and the Classification-Tree-Coarse model had the highest error in both methods (92.66, 92.67).Conclusion: Consequently, it can be said that by changing the methods of database preparation in order to train models, the modeling results can be changed effectively.
Original Research Paper
Pulsed Power
A. Nejadmalayeri; H. Bahrami; َA. Bali Lashak; I. Soltani
Abstract
Background and Objectives: Dielectric Barrier discharge (DBD) is a suitable method to generating Non-thermal plasma at atmospheric pressure, which utilizes Pulsed power supplies as exciters. Increasing pulse voltage range and frequency and compactness are important issues that should be taking into consideration.Methods: ...
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Background and Objectives: Dielectric Barrier discharge (DBD) is a suitable method to generating Non-thermal plasma at atmospheric pressure, which utilizes Pulsed power supplies as exciters. Increasing pulse voltage range and frequency and compactness are important issues that should be taking into consideration.Methods: The high voltage pulse generators which are introduced in the literature have some disadvantages and complexities such as need of additional winding to reset the transformer core and operating under hard switching which increases electromagnetic noise and loss. The leakage inductance of the high voltage transformer increases the rise time of the pulse which is undesirable for DBD applications. The energy stored in the leakage inductance causes the voltage spike across the switch, witch necessitates the use of snubber circuits. The main contribution of this paper is a new high voltage pulse generator with the following characteristics, 1) a capacitor is paralleled with the main switch to reset the transformer core and to provide the soft switching condition for the switch. 2) The resonant charging technique is used which doubles the secondary winding voltage which reduces the turns ratio of high voltage transformer for a certain output pulse peak. 3) The sharpening circuit using magnetic switch produces a sharp high voltage pulse.Results: The proposed high voltage pulse generator is designed and simulated using Pspice software. To verify the theoretical results, a prototype with the input voltage 48 V, the output voltage pulse 1.5 kV, and the rise time of the output pulse 50 ns is constructed and tested.Conclusion: This paper proposes a new pulse generator (PG). The proposed PG uses three techniques named forward, resonant charging, and magnetic switch to produce a high-voltage nanosecond pulse. The resonant charging double the secondary voltage of the pulse transformer, which causes reduction in turn ratio of the pulse transformer and decreases the weigh, volume, and price of the PT. The magnetic switch section finally produces a nanosecond high-voltage pulse. The magnitude of the output pulse can be varied using the input source voltage, the MS reset current and the duty cycle. The core of the pulse transformer resets by using a capacitor paralleled with the switch and the PG does not need any additional reset winding like the conventional DC-DC forward converter.
Original Research Paper
Recommender Systems
K. Vahidy Rodpysh; Seyed Javad Mirabedini; T. Banirostam
Abstract
Background and Objectives: The main purpose of the recommender system is to estimate the user's desire and provide a list of items predicted using the appropriate information. Recommender systems offering suggestions items to users face the two challenges of cold start and sparse data. Methods: This ...
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Background and Objectives: The main purpose of the recommender system is to estimate the user's desire and provide a list of items predicted using the appropriate information. Recommender systems offering suggestions items to users face the two challenges of cold start and sparse data. Methods: This paper aims to propose a novel method to overcome the cold start and sparse data challenges in recommender systems. Singular value decomposition is one of the most common methods to reduce sparse data in recommender systems by reducing dimensions. However, the basic singular value decomposition can only extract the feature vectors of users and items, potentially resulting in lower recommendation precision. Using similarity criteria between entities, in addition to being able to reduce cold start that can solve the problem of singular value decomposition through extracting more refined factor vectors. Besides, considering the context dimensions as the third dimension of the matrix requires the use of another flexible algorithm, such as tensor factorization offering a viable solution to minimize the sparse data challenge. We propose a novel method named TCSSVD. First, a two-level matrix is obtained through similarity criteria between the user and the item to reduce the cold start challenge. The second step, to reduce the challenge of sparse data, contextual information is used with the help of tensor in the two level singular value decomposition.Results: Two data sets IMDB and STS due to the exerting of users feature, items feature and contextual information to review the proposed method. In order to the accuracy of the prediction of the criterion RMSE with an accuracy of 95%. However, since the user's rating of the item is of particular importance in the recommender systems. The method TCSSVD compared to the methods tensor factorization, HOSVD, BPR, and CTLSVD are used evaluation measure Precision, Recall, F1-score, and NDCG.Conclusion: The findings indicate that the use of innovative similarity criteriato extract user attributes, items to reduce the cold start and the use of contextual information through the tensor in the TCSSVD in order to sparse data. The results contribute to improving the accuracy of the suggestions given to users in recommender systems.
