...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Microprocessors and microsystems >Monitoring and optimizing the state of pollution of high voltage insulators using wireless sensor network based convolutional neural network
【24h】

Monitoring and optimizing the state of pollution of high voltage insulators using wireless sensor network based convolutional neural network

机译：基于无线传感器网络的卷积神经网络监测和优化高压绝缘子污染状态

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, a wireless sensor network (WSN) is combined with Convolutional Neural Network (CNN) forming a hybrid framework to detect the pollution state in high voltage insulators. The WSN is formed by the collection of sensor readings from each high voltage insulator over the transmission tower. The collected sensor readings from the sensor network is sent to the processing unit or detection unit, where CNN is used for the purpose of detecting the partial discharged high voltage insulator. The CNN is used with partial discharge diagnosis model to detect the dischargers in high voltage insulators. The extraction of relevant features from the CNN helps to improve the detection. The experimental validation are conducted on the proposed model with collected training datasets and real time testing datasets. The proposed method is compared with existing models to test the partial discharges in high voltage insulators, namely Artificial Neural Network, Fuzzy and Ant Colony Optimization. The result shows that the proposed method is effective in detecting the partial discharges than the existing methods in terms of False Acceptance Rate and Missing Detection Rate.
机译：在本文中，无线传感器网络（WSN）与形成混合框架的卷积神经网络（CNN）组合以检测高压绝缘体中的污染状态。通过从传输塔上从每个高压绝缘体的传感器读数集合形成WSN。来自传感器网络的收集的传感器读数被发送到处理单元或检测单元，其中CNN用于检测部分排出的高压绝缘体。 CNN与局部放电诊断模型一起使用，以检测高压绝缘体中的放电器。来自CNN相关特征的提取有助于改善检测。实验验证是在提出的模型上进行的，采用收集的训练数据集和实时测试数据集。将所提出的方法与现有模型进行比较，以测试高压绝缘体中的部分放电，即人工神经网络，模糊和蚁群优化。结果表明，在错误接受率和缺失检测率方面，所提出的方法在检测部分放电比现有方法中有效。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号