Recent Advances in Electrical & Electronic Engineering - Volume 10, Issue 3, 2017

Background: Analytical modeling of circumferential-flux disk-type hysteresis motors by using contemporary methods do not lead to accurate results, unlike other types of hysteresis motors. This is due to the considerable radial variation of magnetic field distribution inside these motors. Methods: This paper proposes a novel approach to overcome aforementioned problem. Based on this approach, the motor is considered as the series connection of several imaginary thin motors, by radially dividing it into a finite number of narrow sections. Governing equations of each section are derived by using Ampere's Circuital Law, Magnetic Flux Continuity Law, and Faraday's Law of Induction. This procedure includes a new technique for considering the effect of air-gap leakage on exciting current of motor. Obtained equations have led to a new equivalent electric circuit for motor. To implement the proposed approach, a new iterative modeling algorithm with multiple nested iteration loops has also been introduced. This algorithm finds the working hysteresis loop of each section and the exciting current of motor, for any value of terminal voltage. Results: Due to the generality of the proposed method, it has been successfully employed for modeling a multi-stack slotless motor. Some of the required parameters for modeling of this motor have been calculated by finite element analysis. Different performance characteristics of this motor, including input current, power factor, input power, core and copper losses, developed torque, and efficiency have been obtained over a wide range of terminal voltage. Conclusion: Proposed method could properly predict the radial variations of magnetic field distribution.

Background: Credibility problems in the cloud service are very important issues in cloud computing alliance. Methods: By using the small world model in complex networks, a relationship model of cloud computing alliance can be established; defense game model is established under the cloud alliance by game theory; by combining the self-organization of small world model with self-constraint binding of game model, offensive and defensive game model of incomplete information is realized. Through the simulation experiments, they verify trusted resource management functions in the cloud computing alliance. Results: Moreover, by using unsupervised and supervised management conditions, access requesting nodes for cloud service and comparative analysis of respondents in the cloud service get a better resource management effect.

Background: The Equivalent Salt Deposit Density (ESDD) is the basis of determining pollution classes and mapping grid pollution areas. The influence of environmental factors on the ESDD is complex, and it is difficult to establish an accurate mathematical model to fit the nonlinear relationship between them. Methods: In order to predict effectively the ESDD, a model of Adaptive Quantum Particle Swarm Optimized BP neural network (AQPSO-BP) was proposed. In this algorithm, the encoding mechanism based on probability amplitude of quantum bits was used to expand the ergodicity of population. The position and velocity information of each particle was applied to adaptively adjust the inertia factor. At the same time, the non-linear dynamic adjustment strategy of acceleration factors and mutation operation were introduced to reduce the probabilities of trapping in the local optima solution. Results: The prediction results show that the average relative error, the mean absolute error, the mean squared error and the coefficient of determination are 0.1393%, 1.27E-04, 2.33E-06 and 0.9830, respectively; the average relative variance is 0.0171. Conclusion: Compared with the Particle Swarm Optimized BP network (PSO-BP) and Quantum Particle Swarm Optimized BP network (QPSO-BP) models, the AQPSO-BP algorithm has higher prediction accuracy and stronger generalization ability, and is suitable for evaluating the contamination level to prevent flashover on polluted insulators.

Background: The literature has presented three different classes of the quadrature oscillators, namely the class I oscillators, the class II oscillators, and the class III oscillators. Methods: The work of this paper is supplemented to the literature. Three new different topological classes of the quadrature oscillators, called the class IV, V, and VI oscillators, are added by Nodal Admittance Matrix (NAM) expansion method. The fourth has 32 different forms, the fifth has 12 different forms, and the sixth has eight different forms. In all, 52 double-mode quadrature oscillators using Current Controlled Current Conveyor Transconductance Amplifiers (CCCCTAs) are obtained. The derived oscillators use canonic number of components, then they are easy to be integrated and there is an independent electronic control between the condition for oscillation and the frequency of oscillation. Results: The hand and computer analysis results have been included to support the generation method.

Background: Compressed Sensing (CS) is an emerging signal processing technique for signal acquisition and reconstruction which recently finds applications in array processing. Direction of Arrival (DOA) is a well-known problem in array signal processing which can be treated with methods based on compressed sensing. Methods: In this work, a novel algorithm has been developed based on sparse multiple measurement vector model (MMV) to estimate DOAs of far-field and narrowband sources in linear arrays scenarios. The proposed algorithm exploits singular value decomposition denoising to enhance the reconstruction process. Conclusion: Several simulations have been carried out to show the superior performance of proposed method in comparison to simultaneous orthogonal matching pursuit (S-OMP), Ι2,1 minimization and root-MUISC in both uniform linear array (ULA) and nonuniform linear array (NLA) scenarios.

Background: Wireless Sensor Networks (WSNs) have become an important part in recent years with a wide range of applications from low traffic to high traffic applications (e.g. Multimedia, VoIP, IOT, IOE). These applications require collection and transmission of the high amount of data in a timely manner. In WSNs, sensors are randomly deployed in ad hoc fashion and as per application requirement are inactive for a long time and quickly activate when any event is detected. Designing a good MAC is important to optimize the energy at the data link layer of the communication model. Proposed protocol EE-MMAC is an energy-efficient multichannel MAC for high traffic applications. Methods: The primary objective of EE-MMAC is to cut energy consumption at the data link layer based on following multi-channel attributes: Idle listening, elimination of collisions, overhearing and reducing the control packet overhead. EE-MMAC uses periodically sleep technique in the multi-channel environment based on the directional antenna, which is different from the traditional IEEE 802.11 MAC and IEEE 802.15.4. When a node is transmitting data, during that time other nodes must be in sleep mode motivated by S-MAC, PAMAS. Nodes must exchange control packets on CC (control channel) to choose DC (data channel) for communication and to decide the beam direction of the flow. Results: The proposed algorithm results show that the EE-MMAC achieves significant energy gains (30% to 45% less than comparable to IEEE 802.11, and MMAC) based on mainly energy efficiency, PDR (packet delivery ratio) and throughput.

Background: In this paper, as to the nonlinearity of the Linear Power Amplifier (LPA) in Protective Relay Test Device (PRTD), a digital predistorter based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed and is named as ANFIS digital predistorter. Method: By merely modifying the software of the Industrial Personal Computer (IPC) of the PRTD, ANFIS digital predistorter can upgrade the traditional PRTD to a new generation one, making the PRTD fulfill the accuracy requirement of fault waveform reproduction and the limited bandwidth and output capacity of the LPA be better exploited. The ANFIS digital predistorter adaptively learns the total nonlinearity of both LPA and its load, and therefore the nonlinear error resulting from any component can all be compensated, which lowers the accuracy requirement of every single component. Conclusion: And with the quasi-online learning mode, the ANFIS digital predistorter can be realized on general IPCs, and thus maintains the high performance-price ratio of the traditional PRTD.

Background: Image inpainting is a technique that can be used to restore missing or damaged pixels in images. Owing to its high practical value, image inpainting has been a research field for many years. For image inpainting, the Total Variation (TV) model is always a powerful and popular tool. However, when TV norm is involved, most of the conventional image inpainting methods suffer from difficulty in the numerical solution. Methods: To improve the speed and efficiency of handling TV-regularized image inpainting problem, this paper proposes a novel method that mainly employs variable splitting and alternating minimization. The proposed method first converts the classical TV model into an equivalent unconstrained minimization problem. Then, by applying variable splitting and alternating minimization, the minimization problem is decomposed into several subproblems with a smaller size. In an iterative process, by alternately addressing these subproblems with the help of corresponding appropriate methods, the optimal solution of the original problem can be efficiently obtained. In image inpainting application, the proposed method smoothly completes four damaged images with 50% of pixels lost, and the restored images illustrate good visual sense and high values of improved signal-to-noise ratio. Conclusion: Using numerical experiments, the effectiveness of the proposed method is validated as well as the advantages of the proposed method over three similar state-of-the-art methods.

Background: Reducing Reradiation Interference (RRI) on radio stations from adjacent UHV power lines is one of the key issues urged to be solved in UHV power projects undergoing in China. Methods: In this paper, advances in three aspects, namely the mechanism of RRI, distance-based protecting measures and detuning-based protecting measures are introduced. Combining with the up-to-date studies on induced current and resonance for RRI in MW frequency band, we analyzed and summarized the efforts in the three aspects. Conclusion: It is concluded that the key issue in RRI protection is to clarify the resonance mechanism as well as the determining factor of RRI. Since the researches from IEEE were mainly based on field intensities, they cannot obtain resonance mechanism for RRI at frequencies above 1.7 MHz, which resulted in the ignorance of resonance in protecting distance calculation in China that induced exaggeration in the distance. Plus, the protecting distance cannot deal with the RRI problems at SW and above frequency bands already existed in China. Therefore, it is suggested to apply the generalized resonance theory or other novel methods to determine the resonance mechanism of RRI at SW and above frequencies.

Background: Split ring resonators are fundamental structures used to design metamaterial structures. These split ring resonators are designed for various scientific applications with complex and simple geometrical shapes. Metamaterials provide the extended spectral resolution, which is beyond the scope of conventional devices reported in open literature. Such metamaterials when operated on the non-ionizing terahertz frequencies (0.1-10 THz) are highly suitable for non destructive sensing of living organisms. Methods: The objective of this research work is to evaluate the performance of classic square split ring resonator as a metamaterial biosensor operating at terahertz frequency by depositing thin layers of dielectric materials resembled as hybridized layers of DNA sample. Results: Highly localized surface electric field distribution indicates strong LC resonance at resonant frequency. Electric field is focused on the capacitive coupled split gap area. The effective parameters of biosensor clearly showed left handedness that is negative permittivity and permeability and refractive index. Biosensor was analyzed by observing shift in transmission (S21) coefficients. Resonant frequency shifts itself towards the lower end of terahertz band due to the loading of thin layers of samples that are composed of different dielectric materials. Conclusion: Metamaterial biosensor sense the presence of tiny layers of different dielectric materials. This was due to the fact that disturbances in the surface electric field caused change in transmission of sensor's resonant frequency. The simple design of the sensor would overcome the issue of reusability of circuit. Such sensor would highly be suitable for sensing the presence of tiny bio molecules.

Background: The paper proposes a positioning algorithm of sensor nodes based on node hop count and Kernel Method. Methods: The algorithm uses kernel method to map the number of nodes to the high dimensional feature space to construct the relationship between the number of hops and the real distance, which builds the model of measuring distance and physical distance model. Results: The experiments demonstrate that the proposed HK algorithm achieves satisfactory results and is rarely influenced by the number of beacon nodes and occlusions. Furthermore, the proposed algorithm can be adapted to various network topologies with high robustness.

Background: This paper investigates the impacts of uncertainties on flow-gate marginal pricing (FMP) as an efficient tool for analyzing financial transmission rights (FTR) in deregulated electricity markets. Methods: The proposed method provides a mathematical formulation for optimal power flow (OPF) and FMP is defined through OPF. Several parameters in electric power systems are modeled as probability distribution function (PDF) and Monte-Carlo simulation (MCS) is utilized to cope with the uncertainties. In order to indicate the priority of the parameters on FMP, sensitivity analysis is carried out and the priority list is derived. Conclusion: Many analyses and assessments demonstrate that network uncertainty makes great impacts on FMP and it is inevitable to include such uncertainties in FMP calculations. Results also emphasize the major effects of FMP in electric power systems under deregulated environments.

Background: Because the fractional-order calculus operator is an irrational function of the complex variable, it is required to deal with rational approximation. Objective: It is difficult to directly implement the fractional-order calculus operator in the numerical simulation and practical application. Methods: So the minimum amplitude frequency approximation error and phase frequency approximation error of rational approximation function are comprehensively considered in the same rational function class. And the rational approximation function construction method and combined optimal rational approximation method of fractional-order calculus operator based on the function approximation theory and logarithmic frequency characteristic asymptote idea are described in detail. Then, an approximation method of fractional-order calculus operator based on the combined optimal rational approximation is proposed in this paper. The approximation effectiveness of fractional-order calculus operator is analyzed by using s-0.6 . And the combined optimal rational approximation method is applied to the design and digital realization of fractional-order controller. In order to simplify the controller design, the controller structure of parallel connection mode is used and the simplified rational approximation expression and transform of fractionalorder integral operator in the different order is obtained. Results: The analyzed results show that the combined optimal rational approximation method of fractional-order calculus operator is consistent with the ideal c in amplitude frequency domain and has smallest error for the phase frequency characteristic. And the applied results show that the proposed combined optimal rational approximation method can conveniently control and simulate the practical computer control system by analyzing the simplified rational approximation expression and z transform of fractional-order integral operator. Conclusion: So the combined optimal rational approximation method can provide better engineering applications of fractional-order controller in the practical control system.