Recent Advances in Electrical & Electronic Engineering - Volume 12, Issue 3, 2019

Background: Switches are important component in electrical system. The switches needs to have the advantages of low ON-state resistance, very high OFF-state resistance, high isolation, no leakage current, less power loss, fast switching, high linearity, small size, arcless and low cost in bulk production. Also these switches have to be reliable and environmental friendly. Methods: In this paper, macro and microswitches for power applications are extensively reviewed and summarized. Various types of switches such as mechanical, solid-state, hybrid and micromechanical switches have been used for power applications are reviewed. The importance and challenge in achieving arcless switching is presented. Results: The use of micromechanical switches for power applications, actuation techniques, switching modes, reliability and lifetime are also reviewed. The modeling and design challenges are also reviewed. Conclusion: The applications of micromechanical switches shows that the switches can reduce the leakage current in battery operated systems and reduce the size of the system considerably.

Background: Renewable energy generation using wind energy has emerged worldwide and has opened up significant new markets in electrical power generation. However, different factors that affect power quality performance of Wind Turbine (WT) applications such as wind speed fluctuation and use of power electronic based devices have been presented due to the rapid increase of WT installations. Methods: Accordingly, it is worth to measure, assess and evaluate the quality of the generated power of these WTs in order to ensure their compliance with the grid-integration conditions. In this work, first, a general classification of WTs and their operating principle is reviewed. Because variable speed WTs are frequently used in today’s power systems, much attention was paid to this type of turbines. Second, the various power quality aspects caused due to the integration of the wind energy systems into the grid were presented and discussed. Flickers, harmonic distortion, response to voltage dip, active power, and reactive power requirements, fault-ride through and short-circuit current contribution were the addressed power quality problems. Results: Further, the study pointed out the need for a unified evaluation process to assess the power quality performance of the grid-connected wind systems. Conclusion: Also, it was concluded that success in integrating more wind energy systems hinges on accurate power quality performance assessment.

In order to solve the trust problems between users and cloud computing service providers in cloud computing services, the existing trust evaluation technology and access control technology in the cloud computing service are analyzed. And the evaluation index of cloud computing is also analyzed. Users can calculate the relevant indicators of cloud computing service according to their own business goals, and choose the appropriate cloud computing services according to their own trust need. In addition, the reliability assessment method of users based on the service process is proposed. Cloud computing access control system can be used for user credibility evaluation, and it can handle user access requests according to user's creditability. In the study, a cloud computing service trust evaluation tool is designed, and the modeling and architecture designs of trust evaluation are also given. The effectiveness of the method is verified by experiments on cloud computing service evaluation methods.

Background: This paper proposes a novel MultiChannel Caucus based Medium Access Control (MC2-MAC) protocol to diminish collisions between different data packets to reduce energy dissipation of nodes and latency of data packets transmitted by the sensors communicating in Line of Sight (LOS) communication deployed to supervise distinct raucous provinces in the smart grid. Methods: The performance diminishing major problems such as wastage of battery power, bottlenecks and collisions need to be mitigated to elongate lifespan and to diminish data latency. The employment of caucus based efficient scheduling scheme enhances synchronization and multiple channels prevent collisions by reducing the number of contending nodes. The utilization of multiple channels enables sink node to communicate simultaneously with numerous nodes. Results: The influence of multichannel is evaluated by comparing the simulation results of the networks implementing ZigBee, C-MAC and MC2-MAC protocols. QualNet 6.1 simulator is used to perform the simulations. Conclusion: The work resolute to evaluate and correlate the impact of the multichannel scheme to optimize the performance metrics of sensors deployed in distinct raucous provinces communicating in LOS environs in the smart grid and to gain the attention of scholars in this emerging field of research.

Background: A current-mode universal first-order filter with three input terminals and one output terminal is presented. Methods: The proposed circuit uses one differential difference current conveyor (DDCC), one grounded capacitor and two resistors. Results: This circuit offers the following advantageous features: high output impedance, employing only one active component, using a grounded capacitor, the versatility to synthesize any type of first-order filter transfer functions. Conclusion: Each standard first-order filter function can be obtained by using only one current input signal from the proposed circuit.

Background: Network on chip is proposed as new reusable and scalable communication system for applications with important number of IPs. The NoC architecture characteristics are based on several factors: the implementation strategy of IPs, the power dissipation, the placement of IPs, data transfer time, the requirements of the given application, etc. The NxM Mesh topology combined with the XY routing algorithm are generally chosen in many studies. Hardware IPs proposed in the literature, for various applications as example video encoders, operates at different frequencies and generally implemented according to several strategies and different bus sizes. Connecting these IPs using the same communication system is very difficult. Methods: In this paper, we present a new topology based on multi-layer mesh topology and adapted for video coding applications. The proposed topology exploits the video coding information regarding groups of cores that communicate through two cores only. The idea is to use a specific NoC for each group of cores and connect the NoCs with bridge in the positions of two communication cores. The choice of parameters in each NoC depends on the characteristic of IPs in the same group in order to maximize communication adaptivity and performance. Results: Synthesis results show that the proposed multi-layer mesh topology NoC uses much less resources than the traditional NxM mesh topology NoC. Conclusion: This reduction in term of resources is assured by the considerable reduction in the length and number of global interconnects, resulting in an increase in the performance and decrease in the power consumption and area of wire limited circuits.

Background: Vibration signature acquired from a gear mesh can be used to identify the defect present in a gear mesh hence can be used to diagnose the condition of a gear mesh. But the signal acquired from the subject may not be noise free and may be non stationary. Methods: Before going for the analysis of the acquired signal a preprocessing on the acquired signal is required to make it noise free. In the present work in first phase, the acquired vibration signal is filtered to reduce the noise and to improve the SNR (signal to noise ratio). The filtering is done by an Adaptive Noise Cancellation (ANC) technique. A modified Leaky Least Mean Square (LLMS) based adaptive algorithm along with a digital filter is used to achieve the ANC. The signal acquired from a healthy gear is used as the reference signal for the adaptive filter based de-noising process. In the second phase of the present work Adaptive Wavelet Transform (AWT) is used to detect the fault by extracting the features from the filtered vibration signal. From the signal pattern the adaptive wavelet is designed. The adaptive wavelet scalogram is compared with the standard wavelet scalogram. Results: The result shows that the adaptive wavelet scalogram is better in analyzing the vibration signal. In this work a gear drive experimental set-up is made. Two different types of defective gears are used for the experiment. In type-1 defective gear one tooth is broken and in type-2 defective gear two teeth are broken. Initially, the vibration signal is acquired from a healthy gear which is used as the reference signal. Then the vibration signal from type-1 defective gear and type-2 defective gear is acquired and processed for the analysis and to identify the defects. Conclusion: The present work shows that with the application of modified-LLMS algorithm and AWT the proposed technique of signal processing is more suitable for the fault identification and hence for the condition monitoring of the gear.

Background: A multi-scale multidirectional image fusion method is proposed, which introduces the Nonsubsampled Directional Filter Bank (NSDFB) into the multi-scale edge-preserving decomposition based on the fast guided filter. Methods: The proposed method has the advantages of preserving edges and extracting directional information simultaneously. In order to get better-fused sub-bands coefficients, a Convolutional Sparse Representation (CSR) based approximation sub-bands fusion rule is introduced and a Pulse Coupled Neural Network (PCNN) based detail sub-bands fusion strategy with New Sum of Modified Laplacian (NSML) to be the external input is also presented simultaneously. Results: Experimental results have demonstrated the superiority of the proposed method over conventional methods in terms of visual effects and objective evaluations. Conclusion: In this paper, combining fast guided filter and nonsubsampled directional filter bank, a multi-scale directional edge-preserving filter image fusion method is proposed. The proposed method has the features of edge-preserving and extracting directional information.

Background: In the field of video image processing, the segmentation and tracking method has become a hot research field. According to the characteristics of soccer video and VAR (Video Assistant Referee) System, in the paper, it proposes a fast algorithm of segmentation and tracking of the players in the video. Methods: First, according to complementary advantages on the color expression in RGB (Red, Green, Blue) space and HSI (Hue, Saturation, Intensity) space, it adopts the method based on combining the main and auxiliary space to make segmentation of the objects in the video. Then, it compares with the normalized color histogram of targets to make identification of which team the players belong to. Results: Finally, it adopts the context features of the players in the soccer video sequence; it combines the method of template matching to realize the player tracking in the soccer video. Conclusion: The experimental results show that the tracking algorithm proposed in this paper can solve the objects occlusion problem of the different players in the soccer match, and can track the different players steadily, and it also can be adopted in the VAR system.

Background: The effective diagnosis of wind turbine gearbox fault is an important means to ensure the normal and stable operation and avoid unexpected accidents. Methods: To accurately identify the fault modes of the wind turbine gearbox, an intelligent diagnosis technology based on BP neural network trained by the Improved Quantum Particle Swarm Optimization Algorithm (IQPSOBP) is proposed. In IQPSO approach, the random adjustment scheme of contractionexpansion coefficient and the restarting strategy are employed, and the performance evaluation is executed on a set of benchmark test functions. Subsequently, the fault diagnosis model of the wind turbine gearbox is built by using IQPSO algorithm and BP neural network. Results: According to the evaluation results, IQPSO is superior to PSO and QPSO algorithms. Also, compared with BP network, BP network trained by Particle Swarm Optimization (PSOBP) and BP network trained by Quantum Particle Swarm Optimization (QPSOBP), IQPSOBP has the highest diagnostic accuracy. Conclusion: The presented method provides a new reference for the fault diagnosis of wind turbine gearbox.