首页> 外文OA文献 >Bayesian neural network and discrete wavelet transform for partial discharge pattern classification in high voltage equipment
【2h】

Bayesian neural network and discrete wavelet transform for partial discharge pattern classification in high voltage equipment

机译:贝叶斯神经网络和离散小波变换在高压设备局部放电模式分类中的应用

摘要

Partial discharge (PD) pattern recognition has been applied for identifying the types of insulation defects in high voltage (HV) equipment. This paper proposes a novel Bayesian neural network (BNN) and discrete wavelet transform (DWT) hybrid algorithm for PD pattern recognition. Laboratory experiments on a number of PD models have been conducted for evaluating the performance of the proposed algorithm.
机译:局部放电(PD)模式识别已用于识别高压(HV)设备中的绝缘缺陷类型。提出了一种新颖的贝叶斯神经网络(BNN)和离散小波变换(DWT)混合算法用于PD模式识别。已经在许多PD模型上进行了实验室实验,以评估所提出算法的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

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