Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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Development and Application of Distributed Multilayer On-line Monitoring System for High Voltage Vacuum Circuit Breaker

  • Mei, Fei (School of Electrical Engineering, Southeast University) ;
  • Mei, Jun (School of Electrical Engineering, Southeast University) ;
  • Zheng, Jianyong (School of Electrical Engineering, Southeast University) ;
  • Wang, Yiping (School of Electrical Engineering, Southeast University)
  • Received : 2012.06.05
  • Accepted : 2013.02.04
  • Published : 2013.07.01
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Abstract

On-line monitoring system is important for high voltage vacuum circuit breakers (HVCBs) in operation condition assessment and fault diagnosis. A distributed multilayer system with client/server architecture is developed on rated voltage 10kV HVCB with spring operating mechanism. It can collect data when HVCB switches, calculate the necessary parameters, show the operation conditions and provide abundant information for fault diagnosis. Ensemble empirical mode decomposition (EEMD) is used to detect the singular point which is regarded as the contact moment. This method has been applied to on-line monitoring system successfully and its satisfactory effect has been proved through experiments. SVM and FCM are both effective methods for fault diagnosis. A combinative algorithm is designed to judge the faults of HVCB's operating mechanism. The system's precision and stability are confirmed by field tests.

Keywords

References

  1. Knezev M, Djekic Z and Kezunovic M, "Automated Circuit Breaker Monitoring," in IEEE Power Engineering Society General Meeting, Tampa, USA, June 2007.
  2. Wang Xiaohua, Rong Mingzhe, Wu Yi and Liu Dingxin, "Method of quick fault diagnosis and new knowledge obtainment for high voltage circuit breaker expert system," Proceedings of the CSEE, Vol.27, No.12, pp.95-99, 2007.
  3. Strachan SM, McArthur SDJ, Stephen B, McDonald JR and Campbell A, "Providing decision support for the condition-based maintenance of circuit breakers through data mining of trip coil current signatures," IEEE Trans on Power Delivery, Vol. 22, No. 1, pp. 178-186, 2007. https://doi.org/10.1109/TPWRD.2006.883001
  4. Zhang Xiang, Zhang Jiaosuo, Gockenbach Ernst and Borsi Hossein, "Life Management of SF(6) Circuit Breakers based on Monitoring and Diagnosis," IEEE Electrical Insulation Magazine, Vol. 25, No. 3, pp. 21-29, 2009. https://doi.org/10.1109/MEI.2009.4976899
  5. Stephen B, Strachan SM, McArthur SDJ, McDonald JR and Hamilton K, "Design of trip current monitoring system for circuit breaker condition assessment," IET Generation Transmission & Distribution, Vol. 1, No. 1, pp. 89-95, 2007. https://doi.org/10.1049/iet-gtd:20060074
  6. Jian Huang, Peilei Rao, Xiaoguang Hu and Jin Xiao, "Research of on-line monitoring system of the condition of circuit breaker based on ARM and FPGA," in IEEE International Conference on Control and Automation, Christchurch, New Zealand, Dec, 2009.
  7. Lan Jianjun, Hong Zhiyong, Lin Qingyu and Lun Xianmin, "The Research of Method of High Voltage Circuit Breaker Parameter Monitoring and Life Prediction," Journal of Northeast Dianli University, Vol. 31, No. 1, pp. 57-60, 2011.
  8. Xiong Xiaofu, Sun Xin, Cai Weixian and Yang yang, "Distributed monitoring system based on DSP and ARM for mechanical characteristic of high voltage," Power System Protection and Control, Vol. 37, No. 6, pp. 64-68, 2009.
  9. Ma Qiang, Rong Mingzhe, Jia Shenli, "Study of Switching Synchronization of High Voltage Breakers Based on The Wavelet Packets Extraction Algorithm and Short Time Analysis Method," Proceedings of the CSEE, Vol. 25, No. 13, pp. 149-154, 2005.
  10. Charbkaew N, Suwanasri T, Bunyagul T and Schnettler A, "Vibration signal analysis for condition monitoring of puffer-type high-voltage circuit breakers using wavelet transform," IEEJ Transactions on Electrical and Electronic Engineering, Vol. 7, No. 1, pp. 13-22, 2012. https://doi.org/10.1002/tee.21690
  11. Jiang X, Ma ZGJ, "Crack Detection from the Slope of the Mode Shape Using Complex Continuous Wavelet Transform," Computer-aided Civil and Infrastructure Engineerin, Vol. 27, No. 3, pp. 187-201, 2012. https://doi.org/10.1111/j.1467-8667.2011.00734.x
  12. Zhu Hongjun, Qin Shuren, Peng Liling, "Accurate Detection for Peakvalue Singular Points of the Transient Signal with Wavelet Transforms," Chinese Journal of Mechanical Engineering, Vol. 38, No. 12, pp.10-15, 2002. https://doi.org/10.3901/JME.2002.12.010
  13. Zhang Feng, Liang Jun, Zhang Li and Yun Zhihao, "Traveling Wave Signal Processing Method for Singularity Detection Based on Singularity Value Decomposition and Wavelet Transform," Automation of Electric Power Systems, Vol. 32, No. 20, pp. 57-60, 2008.
  14. Huang NE, Shen Z, Long S, et al, "The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis," Proceedings of the Royal Society of London Series A, 2008.
  15. Guo W, Tse PW, Djordjevich A, "Faulty bearing signal recovery from large noise using a hybrid method based on spectral kurtosis and ensemble empirical mode decomposition," Measurement, Vol. 45, No. 5, pp.1308-1322, 2012. https://doi.org/10.1016/j.measurement.2012.01.001
  16. Yang Xiaoping, Liu Pusen, Zhong Yanru, "Harmonic Detection of Active Power Filter Based on Empirical Mode Decomposition," Transactions of China Electrotechnical Society, Vol. 24, No. 5, pp. 197-202, 2009.
  17. Jia Rong, Xu Qihui, Tian Lulin, Li Hui and Liu Wei, "Denoising of Partial Discharge Based on Empirical Mode Decomposition and Intrinsic Mode Function Reconstruction," Transactions of China Electrotechnical Society, Vol. 23, No. 1, pp. 13-18, 2008.
  18. Wu ZH, Huang NE, "Ensemble empirical mode decomposition: a noise assisted data analysis method," Advances in Adaptive Data Analysis, Vol. 1, No. 1, pp. 1-14, 2009. https://doi.org/10.1142/S1793536909000047
  19. Ni Jianjun, Zhang Chuanbiao, Yang Simon X, "An Adaptive Approach Based on KPCA and SVM for Real-Time Fault Diagnosis of HVCBs," IEEE Trans on Power Delivery, Vol. 26, No. 3, pp. 1960-1971, 2011. https://doi.org/10.1109/TPWRD.2011.2136441
  20. Hoidalen HK, Runde M, "Continuous monitoring of circuit breakers using vibration analysis," IEEE Trans on Power Delivery, Vol. 20, No. 4, pp. 2458-2465, 2005. https://doi.org/10.1109/TPWRD.2005.855486
  21. Huang Jian, Hu Xiaoguang, Yang Fan, "Support vector machine with genetic algorithm for machinery fault diagnosis of high voltage circuit breaker," Measurement, Vol. 44, No. 6, pp. 1018-1027, 2011. https://doi.org/10.1016/j.measurement.2011.02.017
  22. Lu Chao, Yu Honghai, Wang Lixin, "On-line Selflearning Fault Diagnosis for Circuit Breakers Based on Artificial Immune Network," Proceedings of the CSEE, Vol. 29, No. 34, pp. 128-134, 2009.
  23. G Rilling, P Flandrin and P Goncalves, "On empirical mode decomposition and its algorithms," IEEEEURASIP Workshop on NSIP, 2003.

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