面向混合异构配用电通信网的综合监测技术
Fault Detection Method of Distribution Communication Network Based on Unbalance Detection
DOI: 10.12677/CSA.2017.75051, PDF, HTML, XML, 下载: 1,299  浏览: 1,624  科研立项经费支持
作者: 柏东辉*：广东电网有限责任公司东莞供电局，广东 东莞
关键词: 配电通信网；故障检测；不平衡度检测；归一化模型；Distribution Network； Fault Detection； Unbalance Detection； Normalized Model
摘要: 配用电通信网是保障配用电网正常运行、故障快速响应、资源高效利用、业务实时实现、电力生产可持续的信息通道。为保证配电通信网的正常通信，本文研究了一种基于不平衡度检测的配电通信网故障检测方法，使用平滑变异性的归一化速率(NRSV)的方式计算不平衡度，进而进行有效且可扩展的不平衡变化检测，保证故障检测精度，提高故障检测效率。仿真表明，本方法能够实现较高精度的网络故障检测和较高的故障检测效率。
Abstract: Distribution communication network is the information channel, which protects the normal operation, fast false response, efficient use of resources, real-time business and sustainable power production of distribution network. In order to ensure the normal communication of the distribution communication network, this paper studies a fault detection method of distribution communication network based on unbalance detection, and calculates the unbalance degree by using the normalized rate of smoothed variability (NRSV). Effective and scalable unbalanced changes have been detected to ensure accuracy of fault detection and improve fault detection efficiency. Simulation results show that this method can achieve high precision network fault detection and high fault detection efficiency.
文章引用：柏东辉. 面向混合异构配用电通信网的综合监测技术[J]. 计算机科学与应用, 2017, 7(5): 421-427. https://doi.org/10.12677/CSA.2017.75051

参考文献

[1] 雷煜卿, 李建岐, 侯宝素. 面向智能电网的配用电通信网络研究[J]. 电网技术, 2011, 35(12): 14-19.
[2] Kouno, H., Furutani, M., Sagae, Y., Benjebbour, A. and Hagiwara, J. (2011) Implementation of New Silent Faults Detection Method for Base Station Equipment. NTT DOCOMO Technical Journal, 13, 12-19.
[3] Katzela, I. and Schwartz, M. (1995) Schemes for Fault Identification in Communication Networks. IEEE/ACM Transactions on Networking, 3, 753-764.
[4] Liu, D., Lung, C.H., Lambadaris, I. and Seddigh, N. (2013) Network Traffic Anomaly Detection Using Clustering Techniques and Performance Comparison. 2013 26th IEEE Canadian Conference on Electrical and Computer Engineering, Regina, 5-8 May 2013, 1-4.
[5] Thottan, M. and Ji, C. (2003) Anomaly Detection in IP Networks. IEEE Transactions on Signal Processing, 51, 2191- 2204.
[6] 王淼. 智能配用电通信网告警关联分析方法的设计与实现[D]: [硕士学位论文]. 北京:北京邮电大学, 2015.
[7] 唐金锐. 电力线路在线巡视监测及故障精确定位的研究[D]: [博士学位论文]. 武汉: 华中科技大学, 2014.
[8] 江龙才, 霍朝辉, 步冬静. 基于配电通信网的光纤网络故障监测与恢复研究[J]. 无线互联科技, 2016(10): 1-4
[9] 孙峰, 司红代, 孙晓非. 智能电网多指标综合评估体系研究[J]. 东北电力技术, 2011, 32(9): 1-7.
[10] 王智冬, 李晖, 李隽, 韩丰. 智能电网的评估指标体系[J]. 电网技术, 2009, 33(17):14-18.
[11] Bhuyan, M.H., Bhattacharyya, D.K. and Kalita, J.K. (2014) Network Anomaly Detection: Methods, Systems and Tools. IEEE Communications Surveys & Tutorials, 16, 303-336.