数据挖掘技术在二次设备状态评价中的可行性分析报告

The Feasibility Analysis Report of Data Mining Technology in the Secondary Device Status Evaluation

摘要: 面对电力系统数据种类混杂、数据质量差、要求高、实时性等特征，有效数据的提取和处理就成为了势在必行的研究课题。而对于电力系统二次设备的状态评价来说，数据的有效性和准确性更加重要，将直接影响到状态评价的评价结果以及检修计划的制定。本文通过分析现有对二次设备状态评价基础数据处理的方法存在的问题和不足，以及数据挖掘算法中粗糙集与神经网络算法的特征，提出了一种将这两种算法结合用于处理基础数据的思想，从而达到更高效、更客观的为状态评价提供有效状态量的目的。由于目前还没有将数据挖掘技术运用于二次设备状态评价中的例子，因此希望能为今后在二次设备状态评价中的数据挖掘技术研究提供很好的参考价值。

Abstract: Face the characteristics of power system data that mixed type, poor quality, high requirements, real-time, the extraction and processing of the valid data is becoming imperative research topic. For the state evaluation of the power system secondary equipment, the validity and accuracy of the data is more important, it will directly affect the evaluation results of the state evaluation, as well as the formulation of the overhaul plan. In this paper, through the analysis of the problem and inadequacy of basic data processing in existing equipment condition evaluation, and the feature of rough set and neural network algorithm of data mining, put forward a kind of ideas that combine the two algorithms for processing basic data, so as to achieve the purpose of more efficient and more objective for providing effective quantity of state for the state assessment. As there is currently no examples that using data mining technology in the secondary equipment condition evaluation, hope for providing a very good reference value for the research of data mining technology in the secondary device status evaluation in the future.