首页> 外文会议>WSEAS International Conference on MATHEMATICAL METHODS, COMPUTATIONAL TECHNIQUES AND INTELLIGENT SYSTEMS >S-transform Based Support Vector Regression for Detection of Incipient Faults and Voltage Disturbances in Power Distribution Networks
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S-transform Based Support Vector Regression for Detection of Incipient Faults and Voltage Disturbances in Power Distribution Networks

机译:基于S转换的支持向量回归,用于检测配电网络中的初始故障和电压干扰

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Many of the electrical systems throughout the world are experiencing problems with aging insulation. When an insulation failure occurs, it can cause sustained interruption which leads to production loss, expensive equipment damage and substantial financial loses. With the ability to identify incipient fault by detecting potential insulation failures before they occur, power utility's engineer will be able to reduce customers lost profit opportunities. In this paper, a new technique to detect the occurrence of incipient fault and voltage disturbances is proposed. The technique uses the S-transform and the Support Vector Regression (SVR) to extract features from the recorded voltage and currents waveforms and to detect the potential occurrences of incipient fault and voltage disturbance. A case study is presented to evaluate the accuracy of the S-transform based SVR in detecting incipient faults and voltage disturbances occurring in the power distribution networks.
机译:全世界的许多电气系统正在经历老化绝缘的问题。发生绝缘故障时,会导致持续中断,从而导致生产损失,昂贵的设备损坏和大量的财务丢失。通过在发生潜在的绝缘故障之前识别初始故障的能力,电力公用事业工程师将能够将客户降低损失的利润机会。在本文中,提出了一种检测初始故障和电压干扰发生的新技术。该技术使用S转换和支持向量回归(SVR)来从记录电压和电流波形中提取特征,并检测初始故障和电压干扰的潜在发生。提出了案例研究以评估基于S-Dramect基SVR的精度检测功率分配网络中发生的初始故障和电压干扰。

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