500 / 2017-05-10 19:54:24
Research on PD detection of 12kV switchgear based on fuzzy logic algorithm
switchgear,partial discharge,fuzzy logic algorithm,pulse separation
终稿
Weidong Fan / Shenyang University of Technology
ChunGuang Hou / Shenyang University of Technology
Ying Han / Shenyang University of Technology
Cao dong / Shenyang University of Technology
The research on partial discharge(PD) characteristics of 12kV switchgear is based on the off-line experimental data obtained in the lab which can’t reflect the switchgear’s actual working state since there are a lot of external electromagnetic interference in the actual operating environment. The traditional Pulse Current Method will not be suitable for on-line monitoring due to it’s poor noise immunity. The Transient Earth Method (TEV) and the Ultrasonic Method require that the operators have a rich experience in PD detection because of the complex changeable and unforeseeable relationship between the measured signal and magnitude of partial discharge. These two methods are not a good choice for long-term unattended on-line monitoring. In this paper, a new pulse separation technique based on fuzzy logic algorithm is proposed. An equivalent Time-Frequency diagram (TF map) is obtained from the feature extraction and clustering of both PD pulse signal and ambient noise signal. Since different kinds of PD types derived from different PD sources, they will form specific clusters in the TF map while there is no regularity for ambient noise. It provides a possibility to classify the millivolt voltage PD pulse signals from the ambient noise signals up to hundreds of millivolts, enhances the anti-interference ability of the PD detection system, classifies partial discharge patterns and locates PD sources. This paper provides a new idea for the accurate extraction and processing of the PD pulse signal of the 12kV switchgear, which is also helpful to improve the detection sensitivity and locate PD sources.
重要日期
  • 会议日期

    10月22日

    2017

    10月25日

    2017

  • 01月04日 2017

    摘要录用通知日期

  • 03月10日 2017

    初稿录用通知日期

  • 06月30日 2017

    终稿截稿日期

  • 10月25日 2017

    注册截止日期

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