首页> 外文会议>Computational Intelligence, Modelling and Simulation, 2009. CSSim '09 >Rough Set Based Data Mining Strategy for Analyzing Distance Protective Relay Operations
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Rough Set Based Data Mining Strategy for Analyzing Distance Protective Relay Operations

机译:基于粗集的数据挖掘策略,用于距离保护继电分析

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In this paper rough-set-based data mining strategy is formulated to analyze the relay trip assertion, impedance element activation, and fault characteristics of a distance relay decision system. Using rough set theory, the uncertainty and vagueness in the relay event report can be resolved using the concepts of discernibility, elementary sets and set approximations. Nowadays protection engineers are suffering from very complex implementations of protection system analysis due to massive quantities of data coming from diverse points of intelligent electronic devices. To help the protection engineers deal with the crucial necessity and benefit of protection system analysis without the arduous handling of overwhelming data, using recorded data resident in digital protective relays alone in an automated approach called knowledge discovery in database is certainly of an immense help. The rough set approach adopts an individually-event-based paradigm in which detailed time tracking analysis of relay operation has been successfully performed.
机译:本文提出了一种基于粗糙集的数据挖掘策略,以分析继电器跳闸的断言,阻抗元件的激活以及距离继电器决策系统的故障特征。使用粗糙集理论,可以使用可分辨性,基本集和集近似的概念来解决中继事件报告中的不确定性和模糊性。如今,由于来自智能电子设备不同点的大量数据,保护工程师正面临着非常复杂的保护系统分析实施工作。为了帮助保护工程师处理保护系统分析的关键必要性和好处,而又不费力地处理大量数据,仅使用数字保护继电器中驻留的记录数据,以一种称为数据库中知识发现的自动化方法,无疑会带来巨大的帮助。粗糙集方法采用基于单个事件的范例,其中已成功执行了继电器操作的详细时间跟踪分析。

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