一体化电网信息系统自动化故障融合检测技术
投稿时间:2019-04-25  修订日期:2019-05-17  点此下载全文
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窦国贤* 安徽继远软件有限公司 230088
高杨 安徽继远软件有限公司 
中文摘要:在电网系统中,故障检测是关系到电网正常运行的关键,本文采用小波变换实现对原始电网信息系统采样信号的特征提取,然后使用遗传算法对最为重要的特征的进行优化和搜索,优化后的数据输出至神经网络模型,神经网络模型对接收到的数据信息进行状态识别、特征分类,有效地提高了分类的准确性和故障诊断的可靠性。本文设计的方案大大提高了计算速度,有利于用户快速从电网数据中把握重要信息,分析影响电网信息自动化系统故障数据信息,从而从根源上解决智能电网运行过程中存在的问题,为智能电网的健康、绿色运行提供较为有价值的技术参考,同时也具有较好的学术研究意义以及工程应用价值。
中文关键词:电网  故障检测  小波变换  遗传算法  神经网络模型
 
Integrated fault information fusion detection technology for integrated grid information system
Abstract:In the grid system, fault detection is the key to the normal operation of the grid. In this paper, the wavelet transform is used to extract the features of the original grid information system sampling signals, and then the genetic algorithm is used to optimize and search the most important features. Then use genetic algorithms to optimize and search for the most important features,the optimized data is output to the neural network model. The neural network model performs state recognition and feature classification on the received data information, which effectively improves the accuracy of classification and the reliability of fault diagnosis. The scheme designed in this paper greatly improves the calculation speed, which helps users to quickly grasp important information from the grid data, analyzes the fault data information affecting the grid information automation system, and solves the problems in the operation of the smart grid from the root cause. Therefore, the problems existing in the operation of the smart grid are solved from the root cause, which provides a valuable technical reference for the health and green operation of the smart grid. It also has good academic research significance and engineering application value.
keywords:Power  grid, fault  detection, wavelet  transform, genetic  algorithm, neural  network model
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