481 / 2017-05-09 20:36:31
Fault Diagnosis for High Voltage Circuit Breaker Based on Hilbert-Huang Transform and Support Vector Machine
High Voltage Circuit Breaker (HVCB),2770,Hilbert-Huang transform (HHT),Support Vector Machine (SVM)
终稿
Chunguang Hou / Shenyang University of Technology
Maoyuan Jia / Shenyang University of Technology
Ying Han / Shenyang University of Technology
Yundong Cao / Shenyang University of Technology
High voltage circuit breaker (HVCB) is one of the crucial equipment in power system, and the power system can be controlled and protected by HVCB. It is necessary to monitor the operation state of the HVCB and analyze the fault by the related signal, the fault of HVCB operating mechanism is closely associated with coil current, mechanical vibration and other factors. Coil current waveform and mechanical vibration signal have different characteristics in different states. A new method of fault diagnosis for HVCB based on Hilbert-Huang transform (HHT) and support vector machine is proposed to analyze faults accurately and quickly in high voltage circuit breakers, determining the characteristic and category of the fault. Compared with Fourier transform-based linear and steady-state spectral analysis, the HHT method can better analyze non-stationary and nonlinear problems. HVCB testing platform based on LabVIEW and NI data acquisition equipment gain the signals of the coil current and mechanical vibration generated by the different fault conditions, these signals are processed by HHT for spectrum analysis, so the normal state and the fault state of the current, mechanical vibration signal and other factors of the characteristics are extracted. The model of fault diagnosis for HVCB is established by using support vector machine (SVM), The characteristics in different states are consider as the input vector of the support vector machine, Data is trained by SVM, and the genetic algorithm is used to optimize the model parameters of the SVM, thus accurate detection of HVCB status is achieved, the type of fault can be clearly determined. This study has carried on the related experiment, the feasibility and the validity of this method has been analyzed and verified. The method can obtain better diagnosis results, it is also suitable for fault diagnosis for HVCB.
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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