Abstract
With the development of science and technology, power network has greatly developed, and people has gradually depended on the power in daily life. However, once the fault in power network, the transmission of power will be difficult and the engineer must check the fault in large amounts of alarm data in power network immediately, which would cost so much time by human experience. To solve this problem, we do correlation analysis of alarm data based on fuzzy rule by human intelligence and then locate the root alarm data for the engineer so that they could repair the fault immediately. We do data preprocessing and feature selection firstly. Then this work introduces the Fuzzy C-means (FCM) method to do clustering, which is based on the fuzzy rule. Finally, we use Aprior algorithm to do correlation analysis in order to locate fault in power network. Experimental results show that correlation analysis based on fuzzy rule has better performance comparing to the competing algorithms.
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References
Wang, B., Zhang, S., Guo, Y.: Research on alarm correlation based on dependency search tree in electric power communication network. In: International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, pp. 2374–2378. IEEE (2008)
Zhou, L., Yang, Z., Wen, Y.: Distributed wireless video scheduling with delayed control information. IEEE Trans. Circ. Syst. Video Technol. 24(5), 889–901 (2014)
He, Y., et al.: Electric power communication network alarm data acquisition system based on CORBA northbound interface. Adv. Mater. Res. 989–994, 4175–4178 (2014)
Kondaveeti, S.R., et al.: Graphical representation of industrial alarm data. IFAC Proc. 43(13), 181–186 (2010)
Elena, B., Tania, C., Silvia, C.: IMine: index support for itemset mining. IEEE Trans. Knowl. Data Eng. 21(4), 493–506 (2009)
Hou, S.Z., Zhang, X.F.: Analysis and research for network management alarms correlation based on sequence clustering algorithm. In: Proceedings of ICICTA 2008, pp. 982–986 (2008)
Agrawal, R., Srikant, R.: Fast algorithm for mining association rules. In: Proceedings of the 20th VLDB Conference, pp. 487–499 (1994)
Cohen, E., Datar, M., Fujiwara, S., Gionis, A., Indyk, P., Motwani, R., Ullman, J.D., Yang, C.: Finding interesting associations without support pruning. IEEE Trans. Knowl. Data Eng. 13(1), 64–78 (2001)
Zhang, X., Hou, S.Z.: Alarm correlation analysis for monitoring system in power communication network. Telecommun. Electric Power Syst. (2009)
Tang, Y., Zhang, Y.: Principles and research on root alarm diagnosing in power communication network. Telecommun. Electr. Power Syst. 11, 004 (2011)
Yang, F., Shah, S.L., Xiao, D.: Correlation analysis of alarm data and alarm limit design for industrial processes. In: American Control Conference, pp. 5850–5855. IEEE (2010)
Li, T., Li, X.: Novel alarm correlation analysis system based on association rules mining in telecommunication networks. Inf. Sci. 180(16), 2960–2978 (2010)
Yang, F., et al.: Improved correlation analysis and visualization of industrial alarm data. ISA Trans. 51(4), 499–506 (2012)
Deng, H., Zhu, W., Wang, S., Sun, K., Huo, Y., Sun, L.: FCM clustering method based research on the fluctuation phenomenon in power network. In: Tan, Y., Shi, Y., Tan, K.C. (eds.) ICSI 2010. LNCS, vol. 6146, pp. 619–626. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13498-2_81
Xie, W., et al.: MultiLayer network alarm correlation analysis based on fuzzy association rule mining. School of Communication and Information Engineering
Toivonen, H.: Apriori algorithm. Encyclopedia of Machine Learning, pp. 39–40 (2011)
Acknowledgements
This work is supported by the science and technology project of Guangdong Power Grid Co., Ltd, (036000KK52170002).
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Jiang, W., Chen, Y., Liao, Y. (2018). Correlation Analysis of Alarm Data Based on Fuzzy Rule in Power Network. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11067. Springer, Cham. https://doi.org/10.1007/978-3-030-00018-9_17
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DOI: https://doi.org/10.1007/978-3-030-00018-9_17
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