Reliability Analysis of Arc Recognition Method Based on Cumulant Autoregressive Parameters Mahalanobis Distance

摘要：

　　In order to improve the reliability of Aviation series arc fault identification, an aviation AC arc fault detection method based on the combination of autoregressive model (AR model) parameters and Mahalanobis distance was proposed.According to the characteristics of line current waveform distortion when arc fault occurs in electrical equipment and line, the accumulated AR parameter Mahalanobis distance characteristic value of arc fault current waveform was extracted to identify whether arc fault occurs in line.The factors affecting arc fault diagnosis by this method were analyzed and studied, including load variation, power supply frequency and sampling frequency variation.The results show that this method can effectively extract the characteristic difference between arc fault current and normal operation, with high reliability and easy implementation.

关键词： Higher-order cumulant AR model Mahalanobis distance Fault arc Reliability

作者: Ruihua Cui Fengfeng Li

作者单位: State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Electrical Engineering, Hebei University of Technology, Tianjin 300130

会议类型: 国际会议

会议名称: The 7th Intrenational Conference on Reliability of Electrical Products and Electrical Contacts(第七届电工产品可靠性与电接触国际会议)

会议地点: 江苏苏州

会议语种:英文

页码: 396-402

在线出版日期: 2019-11-04（万方平台首次上网日期，不代表论文的发表时间）