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Experimental PI Fuzzy Controller to Control Pinch-roll Pressure via Hydraulic servo-valves in Continuous Casting Machines in Mobarakeh Steel Company 用PI模糊控制器控制连铸机液压伺服阀夹辊压力的实验研究
Q4 Engineering Pub Date : 2020-09-01 DOI: 10.29252/MJEE.14.3.8
Mohammad-Reza Askari, A. Daghighi
In this paper, the Fuzzy PI controller is used to control the hydraulic servo-valves in Saba iron casting facility in Mobarakeh Steel Company. The electronic and control circuitry in the hydraulic servo-valves was damaged and the oil pressure sensor was not working anymore. The roles were bending and slabs were occasionally broken. Any replacement of the whole servo-valve system was not an option. Therefore, a pressure sensor for the oil outlet is installed and using the input to the control unit, the pressure is controlled. Fuzzy membership functions were defined in PLC to implement a PI Fuzzy Controller. The servo-valve was modeled and simulation results shows good controllability of the process in presence of disturbance. The experimental measurements of the slab pressure proved promising application of Fuzzy PI controller for the system under consideration.
本文将模糊PI控制器应用于Mobarakeh钢铁公司Saba铸铁厂液压伺服阀的控制。液压伺服阀中的电子和控制电路损坏,油压传感器不再工作。角色是弯曲的,石板偶尔被打破。对整个伺服阀系统进行任何替换都是不可能的。因此,安装了一个油出口压力传感器,并使用输入到控制单元,控制压力。在PLC中定义模糊隶属函数,实现PI模糊控制器。对伺服阀进行了建模,仿真结果表明,在存在干扰的情况下,伺服阀具有良好的可控性。通过对板坯压力的实验测量,验证了模糊PI控制器在系统中的应用前景。
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引用次数: 0
Routing Improvement in Underwater Wireless Sensor Networks for Energy Saving Purposes 以节能为目的的水下无线传感器网络路由改进
Q4 Engineering Pub Date : 2020-09-01 DOI: 10.29252/mjee.14.3.7
Mohammad Nokhodian, F. Mesrinejad, H. Emami
Underwater wireless sensor networks have attracted much attention in various applications such as natural disasters monitoring, defense, industries, etc. A new routing algorithm for underwater wireless sensor networks is developed and tested. The algorithm shows a better end-to-end delay yet less energy consumption. This was achieved by limiting the data transmission to a number of specific adjacent nodes to whom the transmitter is authorized to send the message. The algorithm performance was compared with other algorithms (depth based routing and cooperative depth based routing protocols) and the results show a better performance.
水下无线传感器网络在自然灾害监测、国防、工业等领域受到广泛关注。提出并测试了一种新的水下无线传感器网络路由算法。该算法具有较好的端到端时延和较低的能耗。这是通过将数据传输限制到一些特定的相邻节点来实现的,发送器被授权向这些节点发送消息。将该算法的性能与其他算法(基于深度的路由协议和基于协作深度的路由协议)进行了比较,结果表明该算法具有更好的性能。
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引用次数: 0
Creating Balance on Bandwidth Consumption using Network Coding in Wireless Sensor Networks 在无线传感器网络中使用网络编码实现带宽消耗平衡
Q4 Engineering Pub Date : 2020-09-01 DOI: 10.29252/mjee.14.3.3
Ehsan Kharati
In recent years, Network Coding (NC) has been used to increase performance and efficiency in Wireless Sensor Networks (WSNs). In NC, Sensor Nodes (SNs) of network first store the received data as a packet, then process and combine them and eventually send them. Since the bandwidth of edges between SNs is limited, management and balancing bandwidth should be used for NS. In this paper, we present an optimization model for routing and balancing bandwidth consumption using NC and multicast flows in WSNs. This model minimizes the ratio of the total maximum bandwidth to the available bandwidth in network's edges and we use the dual method to solve this model. We also use the Karush–Kuhn–Tucker conditions (KKT) to calculate a lower bound and find the optimal solution and point in optimization model. For this purpose, we need to calculate the derivative of the Lagrangian function relative to its variables, in order to determine the condition as a multi-excited multi-equation device. But since the solution of equations KKT is centralized and for WSNs with a large number of SNs, it is very difficult and time consuming and almost impractical, we provide a distributed and repeatable algorithm for solving proposed model in which instead of deriving derivatives, combination Sub-gradient method and network flow separation method are used, thus allow each SN locally and based on the information of its neighboring nodes performs optimal routing and balances bandwidth consumption in the network. The effectiveness of the proposed optimization model and the proposed distributed algorithm with multiple runs of simulation in terms of the number of Source SNs (SSNs) and Lagrange coefficient and step size have been investigated. The results show that the proposed model and algorithm, due to informed routing and NC, can improve the parameters of the average required time to find the route optimal, the total amount of virtual flow in network’s edges, the average latency end-to-end of the network, the consumed bandwidth, the average lifetime of the network and the consumed energy, or not very weak compared to other models. The proposed algorithm also has great scalability, because computations are done distributed and decentralized, and there is an insignificant dependence between the SNs.
近年来,网络编码(NC)被用于提高无线传感器网络(WSNs)的性能和效率。在NC中,网络的传感器节点(SNs)首先将接收到的数据以数据包的形式存储,然后对其进行处理、合并并最终发送出去。由于SNs之间的边带宽有限,因此需要对NS进行带宽管理和带宽均衡。本文提出了一种基于NC流和组播流的无线传感器网络路由和平衡带宽消耗的优化模型。该模型最小化了网络边缘的总最大带宽与可用带宽之比,并使用对偶方法求解该模型。我们还利用Karush-Kuhn-Tucker条件(KKT)计算了一个下界,并找到了优化模型的最优解和最优点。为此,我们需要计算拉格朗日函数相对于其变量的导数,以确定其作为多激励多方程装置的条件。但由于方程KKT的求解是集中的,且对于具有大量SNs的WSNs,求解非常困难、耗时且几乎不切实际,因此我们提供了一种分布式、可重复的算法来求解所提出的模型,该模型采用组合子梯度法和网络流分离法,而不是求导。从而允许每个SN在本地并根据相邻节点的信息进行最优路由,均衡网络带宽消耗。从源SNs (ssn)数量、拉格朗日系数和步长等方面考察了所提出的优化模型和分布式算法的有效性。结果表明,该模型和算法由于采用了知会路由和NC技术,在寻找路由最优的平均所需时间、网络边缘虚拟流总量、网络端到端平均时延、网络消耗的带宽、网络平均生存期和网络消耗的能量等参数上都有显著提高,与其他模型相比并不是很弱。该算法还具有很好的可扩展性,因为计算是分布式和去中心化的,并且SNs之间的依赖性很小。
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引用次数: 1
The FDTD Simulation of QDLED Performance Dependency on the Location of Colloidal Quantum Dots 胶体量子点位置对量子点发光二极管性能影响的FDTD模拟
Q4 Engineering Pub Date : 2020-09-01 DOI: 10.29252/MJEE.14.3.11
N. Heydari, S. Ghorashi, M. Fathollahi
All types of Light Emitting Diodes (LEDs) are desirable because of their widespread applications. The Quantum Dot-Based Light Emitting Diodes (QDLEDs) have a lot of unique properties attracting more attention. Predicting performance of QDLEDs can lead to a better and more efficient design of the device. In this paper, we have attempted to investigate the dependency of the device performance on the location of Quantum Dots (QDs) and determine the best location for the QDs in the QDLEDs. We use FDTD method to simulate and analysis the QDLEDs structure. The QDs are located in five different positions in TPBi layer then results are compared with each other. The results show that the closer the QDs to the hole transport layer (HTL), the better the luminescence. This improvement would be explained by two charge transport mechanisms including direct charge injection and exciton energy transfer. The results show that when the QDs are closer to the HTL, the device performance is better due to the greater balance of carriers.  In this condition holes can transfer from the HTL to the valence band easier.
所有类型的发光二极管(LED)由于其广泛的应用而是合乎需要的。量子点基发光二极管(QDLED)具有许多独特的特性,越来越受到人们的关注。预测QDLED的性能可以带来更好、更有效的器件设计。在本文中,我们试图研究器件性能对量子点(QDs)位置的依赖性,并确定量子点在QDLED中的最佳位置。我们使用FDTD方法对QDLED结构进行了仿真和分析。量子点位于TPBi层中的五个不同位置,然后将结果相互比较。结果表明,量子点离空穴传输层越近,发光效果越好。这种改进可以用两种电荷传输机制来解释,包括直接电荷注入和激子能量转移。结果表明,当量子点更接近HTL时,由于载流子的平衡性更大,器件性能更好。在这种情况下,空穴可以更容易地从HTL转移到价带。
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引用次数: 0
FAHPBEP: A Fuzzy Analytic Hierarchy Process Framework in Text Classification 文本分类中的模糊层次分析法框架
Q4 Engineering Pub Date : 2020-09-01 DOI: 10.29252/MJEE.14.3.14
R. Asgarnezhad, S. A. Monadjemi, M. Soltanaghaei
With the availability of websites and the growth of comments, reviews of user-generated content published on the Internet. Sentiment Classification is one of the most common problems in text mining, which applies to categorize reviews into positive and negative classes. Pre-processing has an important role when these textual contexts employed by machine learning techniques. Without efficient pre-processing methods, unreliable results will achieve. This research probes to investigate the performance of pre-processing for the Sentiment Classification problem on three popular datasets. We suggest a high-performance framework to enhance classification performance.  First, features of user's opinions are extracted based on three methods: (1) Backward Feature Selection; (2) High Correlation Filter; and (3) Low Variance Filter. Second, the error rate of the primary classification for each method calculated through the perceptron. Finally, the best method selected through the fuzzy analytic hierarchy process. This framework is beneficial for companies to observe people's comments about their brands and for many other applications. The current authors have provided further evidence to confirm the superiority of the proposed framework. The obtained results indicate that on average this proposed framework outperformed its counterparts. This framework yields 90.63 precision, 90.89 accuracy, 91.27 recall, and 91.05% f-measure.
随着网站的可用性和评论的增长,在互联网上发布的用户生成内容的评论。情感分类是文本挖掘中最常见的问题之一,它适用于将评论分为正面和负面两类。当机器学习技术使用这些文本上下文时,预处理具有重要作用。如果没有有效的预处理方法,将获得不可靠的结果。本研究试图在三个流行的数据集上研究情绪分类问题的预处理性能。我们建议使用一个高性能的框架来提高分类性能。首先,基于三种方法提取用户意见的特征:(1)向后特征选择;(2) 高相关滤波器;以及(3)低方差滤波器。其次,通过感知器计算出每种方法的初级分类的错误率。最后,通过模糊层次分析法选出最佳方法。该框架有利于公司观察人们对其品牌的评论,也有利于许多其他应用。目前的作者提供了进一步的证据来证实所提出的框架的优越性。所获得的结果表明,平均而言,这一拟议框架的表现优于同行。该框架的准确度为90.63,准确率为90.89,召回率为91.27,f-measure为91.05%。
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引用次数: 4
Energy Scheduling in a Hybrid DC/AC Micro-Grid Considering Battery/Wind/Photovoltaic Power Sources using Heuristic Optimization Algorithm 基于启发式优化算法的考虑电池/风能/光伏电源的DC/AC混合微电网能量调度
Q4 Engineering Pub Date : 2020-09-01 DOI: 10.29252/MJEE.14.3.13
J. Ebrahimi, T. Niknam, B. Bahmanifirouzi
This paper is treated with optimum energy management in a DC/AC Microgrid (MG) containing hybrid power sources to supply the load within cost minimization. In this hybrid electrical networks, energy sources are exploited as DC and AC manner, in which the Independent System Operator (ISO) should provide a practical coordination between them in order to procure the demand load optimally. This paper presents a framework that all available resources are formulated mathematically in hybrid microgrid with full constraints along with Demand Response (DR) programs implementation. The network under consideration can operate both in grid-tied and autonomous modes to manage power exchanging. Uncertainty and intermittent of Photovoltaic (PV) with Maximum Power Point Tracker (MPPT) equipped, Wind Turbine (WT), Energy Storage Systems (ESS) and DR programs are also considered to achieve the optimal control and operation. The ESSs are capable to connect both DC and AC links and the State of Charge (SOC) is maintained within permissible range. The proposed DG control framework and operation scheduling has facilitated the energy management of renewables using dynamic programing approach. A 24-hour time horizon simulation and discussion through three scenarios verified on a IEEE 33 bus distribution network, is done to represent the effectiveness of proposed energy management strategy to keep the whole hybrid grid stable.
本文研究了含有混合电源的DC/AC微电网(MG)中的最优能量管理,以在成本最小化的情况下为负载供电。在这种混合电力网络中,能源以直流和交流的方式利用,其中独立系统运营商(ISO)应在它们之间提供实际的协调,以最佳地获得需求负载。本文提出了一个框架,即在具有完全约束的混合微电网中,所有可用资源都是用数学公式表示的,以及需求响应(DR)程序的实施。所考虑的网络可以在并网模式和自主模式下运行,以管理电力交换。还考虑了配备最大功率点跟踪器(MPPT)的光伏(PV)、风力涡轮机(WT)、储能系统(ESS)和DR程序的不确定性和间歇性,以实现最佳控制和运行。ESS能够连接直流和交流链路,并且充电状态(SOC)保持在允许范围内。所提出的DG控制框架和运行调度促进了使用动态规划方法的可再生能源能源管理。通过在IEEE 33总线配电网上验证的三种场景进行了24小时时间范围的模拟和讨论,以表明所提出的能源管理策略对保持整个混合电网稳定的有效性。
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引用次数: 0
Noise Reduction of Depth Cameras Images Based on Deep Neural Network 基于深度神经网络的深度相机图像降噪
Q4 Engineering Pub Date : 2020-09-01 DOI: 10.29252/MJEE.14.3.12
Seyed m. Mahdavi, M. Ashourian
Today, infrared sensors or depth sensors are widely used to control applications, games, information acquisition, dynamic and static 3D scenes. Despite the widespread use of these images, their quality is limited to low-quality images, as the infrared sensor does not have high resolution and the images produced by it have noise. Therefore, given the problems and the importance of using 3-D images, the quality of these images should be improved in order to provide accurate images from depth cameras. In this paper, the noise reduction of depth images using convolutional neural networks is considered. A convolutional neural network with a depth of 20 and three layers and a pre-trained neural network is used. We developed the system and tested its performance for two datasets of depth and color images, Middlebury and EURECOM Kinect Face. Results show that for EURECOM Kinect Face images, PSNR improvement is approximately 8 to 15 dB and for Middlebury images the PSNR improvement is about 5 to 14 dB.
如今,红外传感器或深度传感器被广泛用于控制应用、游戏、信息采集、动态和静态3D场景。尽管这些图像被广泛使用,但它们的质量仅限于低质量图像,因为红外传感器不具有高分辨率,并且由其产生的图像具有噪声。因此,考虑到使用3D图像的问题和重要性,应该提高这些图像的质量,以便从深度相机提供准确的图像。本文考虑了使用卷积神经网络对深度图像进行降噪。使用深度为20和三层的卷积神经网络和预先训练的神经网络。我们开发了该系统,并在Middlebury和EURECOM Kinect Face两个深度和彩色图像数据集上测试了其性能。结果表明,对于EURECOM Kinect Face图像,PSNR改善约为8-15dB,而对于Middlebury图像,PSNR改善约为5-14dB。
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引用次数: 0
Online Persian/Arabic Writer Identification using Gated Recurrent Unit Neural Networks 使用门控递归单元神经网络的在线波斯语/阿拉伯语作家识别
Q4 Engineering Pub Date : 2020-09-01 DOI: 10.29252/MJEE.14.3.9
Mahsa Aliakbarzadeh, F. Razzazi
Conventional methods in writer identification mostly rely on hand-crafted features to represent the characteristics of different handwritten scripts. In this paper, we propose an end-to-end model for online text-independent writer identification on Persian/Arabic online handwritten scripts by using Gated Recurrent Unit (GRU) neural networks. The method does not require any specific knowledge for handwriting data analysis. Because of the exclusive ability of deep neural networks, we just represented our data by Random Strokes (RS) representations, which are differential horizontal and vertical coordinates extracted from different handwritings with a predefined length. This representation is a context independent representation. Therefore, this writer identification at RS level is more general than character level or word level in identification systems, which require character or word segmentation. The RS representation is then fed to a GRU neural network to represent the sequence for final classification. All RS features of a writer are then classified independently, and in the final stage, the posterior probabilities are averaged to make the final decision. Experiments on KHATT database, which consists of online handwritings of Arabic writers, gave us 100% accuracy on 10 writers and 76% accuracy on 50 writers, which is much better than previous works on online Persian/Arabic writer identification.
传统的书写者识别方法主要依靠手工制作的特征来表示不同手写体的特征。在本文中,我们提出了一个端到端的模型,用于使用门控递归单元(GRU)神经网络识别波斯语/阿拉伯语在线手写体的在线文本独立作者。该方法不需要任何用于手写数据分析的特定知识。由于深度神经网络的排他性,我们只是用随机笔划(RS)表示来表示我们的数据,这是从不同的手写中提取的具有预定义长度的差分水平和垂直坐标。此表示是与上下文无关的表示。因此,在需要字符或单词分割的识别系统中,这种RS级别的作者识别比字符级别或单词级别更通用。然后将RS表示馈送到GRU神经网络以表示用于最终分类的序列。然后,对作者的所有RS特征进行独立分类,并在最后阶段对后验概率进行平均,以做出最终决定。在由阿拉伯作家在线手写组成的KHATT数据库上进行的实验,对10名作家的准确率为100%,对50名作家的正确率为76%,这比以前关于波斯/阿拉伯作家在线识别的工作要好得多。
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引用次数: 0
AC Optimal Power Flow Problem Considering Wind Energy by an Improved Particle Swarm Optimization 基于改进粒子群优化的考虑风能的交流最优潮流问题
Q4 Engineering Pub Date : 2020-09-01 DOI: 10.29252/mjee.14.3.1
M. Ansari, Hossein Ramzaninezhad
This paper presents an AC Optimal Power flow (AC-OPF) problem of a power system, considering wind energy. Wind energy is an environmental-friendly energy source to produce electrical power and it includes less operating costs compared with other sources of electrical power production. Wind generators also affect the operation cost of a power system as well as transmission losses, based on generators locations and speed of wind. In addition, wind speed is a parameter with uncertainty and considering this uncertainty is an important issue in operation of wind generators in the AC-OPF problem. The proposed AC-OPF formulation includes the integer variables in addition to continuous variables and studies the effects of wind energy, transformer tap settings, and shunt capacitors on fuel cost, transmission losses as well as up and down spinning reserves. To solve the AC-OPF model, an Improved Particle Swarm Optimization (IPSO) is presented. The IPSO algorithm in this work includes velocity mirror effect that causes improvement in the quality of the results. The proposed method is applied on modified IEEE 30 bus test system, and obtained results approve the validity and effectiveness of the proposed method.
本文提出了一个考虑风能的电力系统交流最优潮流(AC-OPF)问题。风能是一种生产电力的环保能源,与其他电力生产来源相比,它的运营成本更低。风力发电机还根据发电机的位置和风速影响电力系统的运行成本以及输电损耗。此外,风速是一个具有不确定性的参数,在AC-OPF问题中,考虑这种不确定性是风力发电机运行中的一个重要问题。所提出的AC-OPF公式包括连续变量和整数变量,并研究了风能、变压器抽头设置和并联电容器对燃料成本、输电损耗以及上下旋转储备的影响。为了求解AC-OPF模型,提出了一种改进的粒子群优化算法(IPSO)。这项工作中的IPSO算法包括速度镜效应,这会提高结果的质量。将该方法应用于改进后的IEEE30总线测试系统,结果验证了该方法的有效性和有效性。
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引用次数: 1
High-Speed Low-Power Approach for Implementation of 8B/10B Encoder for High-Speed Communications 高速通信用8B/10B编码器的高速低功耗实现方法
Q4 Engineering Pub Date : 2020-07-03 DOI: 10.29252/MJEE.14.3.10
S. Aalinejad
In this paper, the design methodology for a high-speed 8B/10B encoding architecture has been discussed. By means of the new truth table and with the help of Pass-Transistor Logic (PTL), a new structure has been designed in CMOS technology, which shows a superior speed performance. Also, power consumption is optimized because of careful design considerations. These features, along with the simplicity of the employed circuitry are the quality of this work to be repeatedly used in high-speed communication systems. The design process has been explained in detail so that the idea can completely be understood. Moreover, the proposed structure has been demonstrated in the circuit level for better clarification. Post-layout simulation results for TSMC 0.18µm standard CMOS technology depict the correct behavior of the proposed architecture whilst the power consumption is 1.64mW from 1.8v power supply.
本文讨论了高速8B/10B编码结构的设计方法。利用新的真值表,并借助于传输晶体管逻辑(PTL),在CMOS技术中设计了一种新的结构,显示出优越的速度性能。此外,由于仔细的设计考虑,功耗得到了优化。这些特征,以及所采用电路的简单性,是这项工作在高速通信系统中重复使用的质量。对设计过程进行了详细的解释,以便能够完全理解这个想法。此外,所提出的结构已经在电路级别上进行了演示,以便更好地说明。TSMC 0.18µm标准CMOS技术的布局后模拟结果描述了所提出架构的正确行为,同时1.8v电源的功耗为1.64mW。
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引用次数: 0
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Majlesi Journal of Electrical Engineering
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