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Automated Power Quality Monitoring System for On-line Detection and Classification of Disturbances

机译:电能质量自动监测系统,用于故障的在线检测和分类

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This paper presents a system for detection and classification of power quality (PQ) voltage disturbances. The proposed system applies the following methods to detect and classify the PQ disturbances: digital filtering and mathematical morphology are used to detect and classify transients and waveform distortions, while in case of short and long duration disturbances (such as sags, swells and interruptions) the analysis of the RMS value of the voltage is employed. The decision and classification process is based on disturbances knowledge base of an expert system. The proposed approach identifies the type of the disturbance and its parameters such as time localization, duration and magnitude. The proposed system is suitable for on-line monitoring of the power system and for implementation in a digital signal processor (DSP).
机译:本文提出了一种用于电能质量(PQ)电压扰动检测和分类的系统。拟议的系统采用以下方法对PQ干扰进行检测和分类:数字滤波和数学形态学用于检测和分类瞬变和波形失真,而在短期和长期干扰(例如下垂,骤升和中断)的情况下,对电压的RMS值进行分析。决策和分类过程基于专家系统的干扰知识库。所提出的方法确定了干扰的类型及其参数,例如时间本地化,持续时间和强度。所提出的系统适用于电力系统的在线监测,并适合在数字信号处理器(DSP)中实施。

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