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IEEE EUROCON 2021 - 19th International Conference on Smart Technologies最新文献

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Determining a Train Location at Level Crossing Approach Section by Track Circuit Input Impedance Processing Using ANN 利用神经网络进行轨道电路输入阻抗处理,确定平交道口进近段列车位置
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535620
V. Havryliuk
The possibility of determining a train location at level crossing approach section by measuring the input impedance of the track circuit with subsequent processing of the results using an artificial neural network has been carried out. The need to measure the coordinates and speed of the train at the section approaching the level crossing is associated with the need to improve traffic safety at the level crossing and reduce the waiting time for a train (especially for a slow moving one) for vehicles. The investigations of the track circuit input impedance dependences on factors such as the train coordinate on it, the resistance of the ballast layer of the track and the frequency of the signal current were carried out by modeling and experimental measurements on a real track circuit. The monotonic dependences of the track circuit input impedance on the train location make it possible to use these dependences to monitor the train location on the track circuit. However, the strong influence of the ballast resistance on the input impedance makes it impossible to directly use the input impedance for positioning the train. Two methods have been considered for determining the coordinates of a train on a track circuit by using its input impedance. The error in determining the train coordinates at the level crossing approach section by processing the track circuit input impedance using ANN shows that this method is promising for practical use.
通过测量轨道电路的输入阻抗来确定列车在平交道口进近段的位置,并利用人工神经网络对结果进行后续处理。在接近平交道口的路段测量列车的坐标和速度的需要与改善平交道口的交通安全以及减少车辆等待火车(特别是缓慢行驶的火车)的时间有关。通过对实际轨道电路的建模和实验测量,研究了轨道电路输入阻抗与列车座标、轨道道砟层电阻、信号电流频率等因素的关系。轨道电路输入阻抗对列车位置的单调依赖性使得利用这些依赖性来监测列车在轨道电路上的位置成为可能。然而,由于镇流器电阻对输入阻抗的强烈影响,无法直接利用输入阻抗对列车进行定位。本文考虑了两种利用输入阻抗确定轨道电路上列车坐标的方法。利用人工神经网络处理轨道电路输入阻抗确定平交道口进近段列车坐标的误差表明,该方法具有实际应用价值。
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引用次数: 1
Synthesis and Applications of Oriented Gaussian FIR Filters 定向高斯FIR滤波器的合成与应用
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535614
R. Matei
An analytical design procedure is proposed for 2D Gaussian orientation-selective FIR filters, based on a frequency transformation applied to a Gaussian prototype. The synthesis starts from a Gaussian filter with specified selectivity with a frequency response approximated as a factored trigonometric polynomial. An efficient frequency mapping is derived and applied to each factor, leading to the desired oriented filter, whose transfer function finally results in matrix form. The 2D filters have a correct shape, with good linearity, a low ripple and negligible distortions. Several design examples for imposed specifications are provided, and also applications in directional filtering are shown, proving the filter capabilities.
提出了一种基于高斯原型的频率变换的二维高斯定向FIR滤波器的解析设计方法。合成从具有特定选择性的高斯滤波器开始,其频率响应近似为因式三角多项式。推导出一个有效的频率映射,并将其应用于每个因子,得到所需的定向滤波器,其传递函数最终得到矩阵形式。二维滤波器具有正确的形状,良好的线性度,低纹波和可忽略的失真。给出了几个强制规范的设计实例,并给出了在定向滤波中的应用,证明了该滤波器的性能。
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引用次数: 1
Fine-Tuning Convolutional Neural Network Based Railway Damage Detection 基于微调卷积神经网络的铁路损伤检测
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535585
A. Aydin, Mehmet Umut Salur, I. Aydin
Due to the rapid development of the railway industry, the task of checking the fit and defects of rails has become of high importance. The train tracks, which are kilometers long, are obtained with hours of video recording. It is almost impossible to examine the images obtained by one or more human eyes. Even if factors that may affect people (such as discomfort, fatigue) are ignored, we can easily state that the time required for the completion of damage assessment will take weeks or months. During the period of investigation, the condition of serious damage may worsen and undesirable results may occur. Therefore, it will save time and cost if the flaws on the rails are made by a deep learning model instead of being made by humans. At the same time, safety in rail transport will be ensured. We propose a high-performance fine-tuning convolutional neural network model that can be improved with negligible losses by using image data to detect defects that occur depending on time or impact on the rail surfaces they use for the transportation of trains. In our study, a two-step approach is followed. In the first stage, we get cropped images focused on the train tracks instead of the rail image captured with a large area. In the second stage, various convolutional neural network models were applied using the cropped images and the classification was provided. While our model continues to work with high success, it works with increasing parameters that accelerate training, such as batch size, and it works very little or even without any loss of success. Experimental results show that our model is better than previous studies.
由于铁路工业的快速发展,对钢轨的配合和缺陷的检查工作变得非常重要。这些铁轨长达数公里,是通过数小时的视频记录得来的。用一只或多只眼睛来检查获得的图像几乎是不可能的。即使忽略可能影响人们的因素(如不适、疲劳),我们也可以很容易地说,完成损害评估所需的时间将需要数周或数月。在调查期间,严重损坏的情况可能会恶化,并可能产生不良后果。因此,如果轨道上的缺陷由深度学习模型制造,而不是由人工制造,将节省时间和成本。同时,确保铁路运输安全。我们提出了一种高性能的微调卷积神经网络模型,该模型可以通过使用图像数据来检测根据时间或对用于火车运输的轨道表面的影响而发生的缺陷,从而在可忽略不计的损失下进行改进。在我们的研究中,遵循两步方法。在第一阶段,我们获得聚焦在火车轨道上的裁剪图像,而不是用大面积捕获的铁路图像。第二阶段,对裁剪后的图像应用各种卷积神经网络模型进行分类;虽然我们的模型继续以很高的成功率工作,但它可以使用越来越多的参数来加速训练,例如批处理大小,并且它的工作非常少,甚至没有任何成功的损失。实验结果表明,我们的模型优于以往的研究。
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引用次数: 2
Design of a Digital Following System of Welding Robot With a Visual Sensor 带有视觉传感器的焊接机器人数字跟随系统设计
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535643
B. Pryymak, S. Korol, M. Ostroverkhov
This paper proposes a variant of solving the problem of synthesis of a digital following system of the welding robot when using a visual sensor as the meter of the relative position of the torch and the parts being welded. A discrete mathematical model of the controlled plant was derived. Structural and parametric synthesis of the control algorithm was performed, which includes a state observer and a modal combined regulator of welding robot link position. The performance of the proposed digital following system of welding robot link was studied.
本文提出了一种以视觉传感器作为焊枪与被焊件相对位置测量仪表的焊接机器人数字跟随系统综合问题的解决方案。建立了被控对象的离散数学模型。对焊接机器人连杆位置的状态观测器和模态组合调节器进行了结构和参数综合。对所提出的焊接机器人连杆数字跟随系统的性能进行了研究。
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引用次数: 0
Method for indirect measurement of the phase capacitance of a distribution substation and the single-phase earth fault current 配电变电所相容和单相接地故障电流的间接测量方法
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535640
A. Neftissov, A. Biloshchytskyi, A. Novozhilov, A. Kislov
This paper presents a theoretical justification for the possibility of determining the current of a single-phase earth fault in an indirect way, as well as a method for determining the line capacitance. An experiment was carried out to measure the current of a single-phase earth fault through a capacitive shunt. Comparison of calculated data and measured results is presented.
本文提出了用间接方法确定单相接地故障电流的可能性的理论依据,以及确定线路电容的方法。进行了通过容性并联装置测量单相接地故障电流的实验。给出了计算数据与实测结果的比较。
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引用次数: 0
Control of PV Distributed Systems Based on Three-Phase Triple Inverters to Support Grids with Unbalanced Loads 基于三相三联逆变器支持电网不平衡负荷的光伏分布式系统控制
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535568
V. Pires, D. Foito, A. Cordeiro, J. F. Silva
This paper is focused on the control system for photovoltaic (PV) generators using three-phase triple inverters. These inverters allow for a distributed PV system, and at the same time, they provide AC multilevel operation. The proposed controller is designed to allow the operation of the inverter in a way that it can extend support to the grid with ancillary services. One of the ancillary services that the three-phase triple inverter can support is the injection of unbalanced currents in order to eliminate or attenuate grid load unbalances. Therefore, the proposed topology will be extended to accommodate four wires. The capability of the system to support the grid with ancillary services, especially the compensation of unbalanced loads, the four-wire multilevel topology operation and the proposed controller will be verified through several simulation tests.
本文主要研究了采用三相三逆变器的光伏发电机组控制系统。这些逆变器允许分布式光伏系统,同时,它们提供交流多级操作。所提出的控制器被设计为允许逆变器以一种方式运行,它可以通过辅助服务扩展对电网的支持。三相三联逆变器可以支持的辅助服务之一是注入不平衡电流以消除或衰减电网负载不平衡。因此,建议的拓扑结构将被扩展以容纳四条线。系统支持电网辅助服务的能力,特别是不平衡负载的补偿,四线多电平拓扑操作和所提出的控制器将通过几个仿真测试来验证。
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引用次数: 0
The Power Components Distribution Investigating in Idle Mode of Three-Phase Transformer with Damage Winding 绕组损坏三相变压器怠速工况下功率分量分布研究
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535558
I. Reva, O. Bialobrzheskyi, O. Todorov, M. Bezzub
Transformers in today's network are increasingly affected by distribution generation. Due to significant fluctuations in source primary energy flow arise idling mode in transformer, increasing loss of saturated magnetic circuit. In this regard, the transformer condition monitoring problems arise and are solve, taking into account its power distribution, especially in damages case. Existing studies in most cases are based on the power distribution analysis, or its harmonic components for normal operating condition. The rules for power distribution determining process of three-phase transformer with inter-turn fault in the windings group of one of the phases is proposed. An experimental study the three-phase transformer idling mode was performed on the laboratory equipment. Developed the primary sequence of the conducting an experiment for research and monitoring of three-phase transformer energy performance in idle mode with a damaged winding. The method was used for this purpose - the power harmonic componets distribution analysis of three-phase transformer provided that the determination location of the damage is by infrared measurement. It is noted that the power of harmonics current and voltage, significantly different from the power harmonics in each of the phases transformer and between phases in general. This allows to apply previously known criteria for evaluating the power distortion character as transformer damage indicators. The results of the study can be used as components for a hybrid monitoring and expert system in SmartGrid.
在当今的电网中,变压器越来越多地受到配电系统的影响。由于源一次能流波动较大,变压器出现空转模式,增加了饱和磁路的损耗。为此,变压器的状态监测问题出现并得到解决,要考虑到其配电情况,特别是在损坏情况下。现有的研究大多是基于功率分布分析,或其谐波分量为正常运行状态。提出了三相变压器某一相绕组组匝间故障时的配电判定规则。在实验设备上对三相变压器空转模式进行了实验研究。制定了在绕组损坏的情况下进行三相变压器空转工况能量性能研究与监测实验的基本流程。该方法用于三相变压器电力谐波分量分布分析,采用红外测量法确定损坏位置。值得注意的是,电流和电压的功率谐波,明显不同于变压器各相和一般相间的功率谐波。这允许应用以前已知的标准来评估功率失真特性作为变压器损坏指标。研究结果可作为智能电网混合监测和专家系统的组成部分。
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引用次数: 0
Heun-King-Werner Method’s based approaches for the solution of the Load Flow Problem 基于Heun-King-Werner方法的潮流问题求解方法
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535618
Laice Neves de Oliveira, F. Freitas, A. P. Oliveira
This paper presents approaches to the calculation of the solution of the load flow problem in ill-conditioned systems based on Newton’s Continuous philosophy. Two approaches to the Heun-King-Werner method are proposed with the objective of obtaining a better computational cost from the reduction of the number of calculations and factorizations of the Jacobian matrices. The methods performance were compared in terms of convergence with the standard Newton-Raphson and the original Heun-King-Werner method. Experiments carried out in ill-conditioned power system models demonstrated that the proposed approaches can significantly reduce the computational cost employed by the original Heun-King-Werner method.
本文提出了基于牛顿连续原理的病态系统负荷流问题解的计算方法。提出了Heun-King-Werner方法的两种方法,目的是通过减少雅可比矩阵的计算次数和分解来获得更好的计算成本。将该方法的收敛性能与标准Newton-Raphson和Heun-King-Werner方法进行了比较。在病态电力系统模型中进行的实验表明,所提出的方法可以显著降低原始Heun-King-Werner方法所使用的计算成本。
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引用次数: 0
Neural Network Clustering Technology for Cartographic Images Recognition 地图图像识别中的神经网络聚类技术
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535544
V. Zhukovskyy, S. Shatnyi, N. Zhukovska, A. Sverstiuk
It is offered the information system of recognition of cartographic images of soil massifs and classification of landscape areas by types of soil massifs using the neural network. Here was described approaches to architecture design, teaching methods, data preparation for teaching, training and neural network testing. The functional scheme of the neural network is developed, which consists of the input, hidden and output layer, collecting and processing of data, and training algorithm. The analysis of efficiency, speed and accuracy of work of a neural network as a part of information technology is carried out.
提出了基于神经网络的土质地形图图像识别和按土质类型划分景观区的信息系统。本文介绍了体系结构设计的方法、教学方法、教学数据准备、训练和神经网络测试。提出了神经网络的功能方案,包括输入层、隐藏层和输出层,数据的采集和处理,以及训练算法。对作为信息技术一部分的神经网络的工作效率、速度和准确性进行了分析。
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引用次数: 5
Convolutional Gated Recurrent Units (CGRU) for Emotion Recognition in Odia Language 卷积门控循环单元(CGRU)在Odia语言情感识别中的应用
Pub Date : 2021-07-06 DOI: 10.1109/EUROCON52738.2021.9535608
Monorama Swain, B. Maji, Umasankar Das
India’s enormous dialectal diversity motivates researchers to develop efficient speech emotion databases, speech features, and emotion recognition systems. Odia has a long literary history and rich dialectal variations; proper tools and assets are lacking for getting promising results for emotion analysis tasks. This paper represents a detailed study that includes the creation and evaluation of an Odia speech emotional database along with the design and testing of the accuracy label of the model considered for the emotion recognition basis. The prime objective of our work is to develop a model using Concatenated Convolution Neural Network and Gated Recurrent Unit (CGRU) for speech emotion recognition adopting prosodic and spectral features of a speech signal. Our experiments show that CGRU gives approximately 5.36% and 6.52% better results when compared to CNN and GRU for both the Odia dataset and the benchmark RAVDESS dataset. We also demonstrate that our proposed method outperforms the state-of-art methods on the RAVDESS dataset. From this experimental study we also observed that CGRU perform faster than baseline model (CNN and GRU) thus making it well-suited for use in real-time applications.
印度巨大的方言多样性促使研究人员开发高效的语音情感数据库、语音特征和情感识别系统。奥迪亚语有着悠久的文学史和丰富的方言变体;缺乏适当的工具和资产来获得有希望的结果的情绪分析任务。本文代表了一项详细的研究,包括创建和评估Odia语音情感数据库,以及设计和测试用于情感识别基础的模型的准确性标签。我们工作的主要目标是开发一个使用连接卷积神经网络和门控循环单元(CGRU)的模型,用于采用语音信号的韵律和频谱特征进行语音情感识别。我们的实验表明,在Odia数据集和基准RAVDESS数据集上,与CNN和GRU相比,CGRU的结果分别提高了5.36%和6.52%。我们还证明了我们提出的方法在RAVDESS数据集上优于最先进的方法。从这个实验研究中,我们还观察到CGRU比基线模型(CNN和GRU)执行得更快,因此使其非常适合在实时应用中使用。
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引用次数: 2
期刊
IEEE EUROCON 2021 - 19th International Conference on Smart Technologies
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