References
- [1] L. Fasanotti, S. Cavalieri, M. Tomasini, F. Floreani and S. Ierace: Prognostics algorithms for circuit breaker application: A benchmark analysis, in International Conference on Industrial Informatics, INDIN 2014, 201410.1109/INDIN.2014.6945557
- [2] D. Lee, B. Lithgow and R. Morrison: New fault diagnosis of circuit breakers, IEEE Transactions on Power Delivery, vol. 18, no. 2, pp. 454-459, 200310.1109/TPWRD.2003.809615
- [3] Y. Zhang, Y. Jiang, Y. Chen and Y. Zhang: Fault Diagnosis of High Voltage Circuit Breaker Based on Multi-classification Relevance Vector Machine, Journal of Electrical Engineering and Technology, no. 15, pp. 413-420, 202010.1007/s42835-019-00199-6
- [4] A. Janssen, D. Makareinis and S. Carl-Enjar: International Surveys on Circuit-Breaker Reliability Data for Substation and System Studies, IEEE Transaction on Power Delivery, vol. 29, no. 2, pp. 808-8014, 201410.1109/TPWRD.2013.2274750
- [5] CIGRE Working Group 13.06: Final report ofthe second international enquiry on high voltage circuit-breaker failures and defects in service, CIGRE Tech. Brochure 83, June 1994
- [6] K. Obarcanin, B. Lacevic, M. Ermidoro: A High-Voltage Circuit Breaker Condition Assessment Method using the Vibration Fingerprint based on VMD-EM method, in IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Dubrovnik, Croatia, 202010.1109/I2MTC43012.2020.9128669
- [7] A. Secic and K. Obarcanin: Power circuit breaker condition assessment based on vibration fingerprint measurement and why it can save your day, NETA World Magazine, pp. 89-95, 2017
- [8] Y. Zhang, Y. Shao, W. Gong, Z. Zhang, J. Wu: Research on combined diagnosis of mechanical fault vibration-sound signal of high voltage circuit breaker based on EEMD-energy entropy feature, in International Conference on Sensors and Instruments 2021, Qingdao, China, 202110.1117/12.2603060
- [9] L. Mingliang, W. Keqi, S. Laijun, Z. Jianfeng: A New Fault Diagnosis Method for High Voltage Circuit Breakers Based on Wavelet Packet and Radical Basis Function Neural Network, Open Cybernetics & Systemics Journal, vol. 8, pp. 410-417, 201410.2174/1874110X01408010410
- [10] Q. Yang, J. Ruan, Z. Zhuang, D. Huang: Fault Identification for Circuit Breakers Based on Vibration Measurements, IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 7, pp. 4154 - 4164, 201910.1109/TIM.2019.2946470
- [11] M. Wong, L. Jack, A. Nandi: Modified self-organising map for automated novelty detection applied to vibration signal monitoring, Mechanical Systems and Signal Processing, vol. 20, no. 3, pp. 593-610, 200610.1016/j.ymssp.2005.01.008
- [12] M. Landry, F. Léonard, C. Landry, R. Beauchemin, O. Turcotte, F. Brikci: An improved vibration analysis algorithm as a diagnostic tool for detecting mechanical anomalies on power circuit breakers, IEEE Transactions on Power Delivery, vol. 23, no. 4, pp. 1986-1994, 200810.1109/TPWRD.2008.2002846
- [13] Y. Yeap, A. Ukil: Fault Detection in HVDC System Using Short Time Fourier Transform, in IEEE Power and Energy Society General Meeting (PESGM), 201610.1109/PESGM.2016.7741323
- [14] N. Charbkeaw, T. Suwanasri, T. Bunyagul: Mechanical Defect Detection of SF6 High Voltage Circuit Breaker Using Wavelet Based Vibration Signal Analysis, in 5th International Conference on Electrical EngineeringElectronics Computer Telecommunications and Information Technology, 200810.1109/ECTICON.2008.4600576
- [15] H. Nantian, F. Lihua, C. Huowei, X. Dianguo, C. Huaijin, N. Yonghui: Mechanical Fault Diagnosis of High Voltage Circuit Breakers with Unknown Fault Type Using Hybrid Classifier Based on LMD and Time Segmentation Energy Entropy, Entropy, vol. 18, no. 9, pp. 322 - 341, 201610.3390/e18090322
- [16] Z. Jianfeng, L. Mingliang, W. Keqi, X. Jingyan, S. Shuli: Feature extraction of HV circuit breaker based on ensemble empirical mode decomposition and correlation dimension, in Electronic Measurement & Instruments (ICEMI), 2015 12th IEEE International Conference on, 201510.1109/ICEMI.2015.7494271
- [17] Q. Yang, J. Ruan, Z. Zhuang, D. Huang: Chaotic Analysis and Feature Extraction of Vibration Signals from Power Circuit Breakers, IEEE Transactions on Power Delivery, vol. 35, no. 3, pp. 1124-1135, 201910.1109/TPWRD.2019.2934123
- [18] M. Kapetanovic, High Voltage Circuit Breakers, Sara-jevo: Faculty of Electrical Engineering Sarajevo, 2011
- [19] Q. Yang, J. Ruan, Z. Zhuang, D. Huang, Z. Qiu: A New Vibration Analysis Approach for Detecting Mechanical Anomalies on Power Circuit Breakers, IEEE Access, vol. 7, pp. 14070 - 14080, 201910.1109/ACCESS.2019.2893922
- [20] W. Caesarendra, P. Kosasih, A. Tieu, C. Moodie: Application of the largest Lyapunov exponent algorithm for feature extraction in low speed slew bearing condition monitoring, Mechanical Systems and Signal Processing, vol. 50, no. 51, pp. 116-138, 201510.1016/j.ymssp.2014.05.021
- [21] C. Froeschlé, E. Lega and R. Gonczi: Fast Lyapunov Indicators. Application to Asteroidal Motion, Celestial Mechanics and Dynamical Astronomy, vol. 67, no. 1, pp. 41-62, 199710.1023/A:1008276418601
- [22] A. Ekizos, A. Santuz, A. Schroll, A. Arampatzis: The Maximum Lyapunov Exponent During Walking and Running: Reliability Assessment of Different Marker-Sets, Front. Physiol., vol. 9, 201810.3389/fphys.2018.01101611740530197597
- [23] B. R. Hunt, J. A. Kennedy, T.-Y. Li, H. E. Nusse: The Theory of Chaotic Attractors, New York: Springer Science+Business Media, 200410.1007/978-0-387-21830-4
- [24] A. Fraser, H. Swinney:Independent coordinates for strange attractors from mutual information, Physical Review A, vol. 33, no. 2, pp. 1134-1140, 198610.1103/PhysRevA.33.11349896728
- [25] J. Walters-Williams, Y. Li: Estimation of mutual information: A survey, in Rough Sets and Knowledge Technology, vol. 23, Berlin, Heidelberg, Springer, pp. 389-396, 200910.1007/978-3-642-02962-2_49
- [26] N. V. Chawla, K. W. Bowyer, L. O. Hall, W. P. Kegelmeyer: SMOTE: Synthetic Minority Over-sampling Technique, Journal of Artificial Intelligence Research, vol. 16, pp. 321-357, 200210.1613/jair.953
- [27] J. Taylor: Introduction to error analysis, the study of uncertainties in physical measurements, 1997.
- [28] J. Taylor, Introduction to error analysis, the study of uncertainties in physical measurements, University Science Books, 1997
- [29] P. Schober, C. Boer, L. Schwarte, “Correlation Coefficients, Anesthesia & Analgesia, vol. 126, no. 5, p. 1763–1768, 201810.1213/ANE.000000000000286429481436