引用本文: | 王豫宁,魏霞,刘波,等.调度数据网厂站侧网络监测装置设计[J].电力系统保护与控制,2019,47(13):133-140.[点击复制] |
WANG Yuning,WEI Xia,LIU Bo,et al.Design of network monitoring device for power dispatching data network at power station[J].Power System Protection and Control,2019,47(13):133-140[点击复制] |
|
摘要: |
为提高调度数据网接入层厂站对网络故障和异常行为的自我判断能力,提出了一种网络监测装置的设计方案。方案基于镜像数据监听技术,采用Ping程序检测厂站内各联网设备的数据链路通断状态,使用开源Linux数据包捕获工具Tcpdump作为监听实现途径,并制定了多端点监听下基于非剥夺式的静态优先级调度算法的任务调度机制。通过分析监测结果中的源IP地址、目标IP地址、通信时间和传输数据量,判断网络内是否存在非法通信操作、数据传输隧道断开和DoS攻击等异常行为。测试结果表明,装置的设计方案是可靠且有效的,能够对网络故障和异常行为作出较为准确的判断,有助于增强厂站对自身网络运行状态信息的识别与掌控能力。 |
关键词: 电力调度数据网 厂站 安全监测 网络流量 旁路监听 |
DOI:10.7667/PSPC20191318 |
投稿时间:2018-03-31修订日期:2018-08-25 |
基金项目:新疆维吾尔自治区自然科学基金项目(2017D 01C030)“基于大数据的低压配网单相故障监测与诊断定位” |
|
Design of network monitoring device for power dispatching data network at power station |
WANG Yuning,WEI Xia,LIU Bo,TIAN Yizhi |
(College of Electrical Engineering, Xinjiang University, Urumqi 830047, China;Urumqi Vocational University, Urumqi 830002, China) |
Abstract: |
A network monitoring device is designed to improve the ability of the power station, which belongs to the access layer of power dispatching data network, to make accurate self-judgements on network faults and abnormal behaviors. Based on mirrored data monitoring technique, the device uses Ping to detect the data link on-off state of other connect-to-network devices and Tcpdump to capture data packages. In addition, a task scheduler for multiple endpoints monitoring based on non-deprivation static scheduling is designed. With the monitoring results of source and destination IP addresses, communication time and amount of transported data, the monitoring device can make judgements on the existing of abnormal situations such as illegal communication, data channel interruption and DoS attack. Testing results have verified that the device is reliable and effective, and can make accurate judgements on network faults and abnormal behaviors, which helps to enhance the ability of the power station to identify and control the working condition of its own network. This work is supported by Natural Science Foundation of Xinjiang Uygur Autonomous Region (No. 2017D01C030). “Single-phase Fault Monitoring and Diagnosis Location for Low-voltage Distribution Network based on Big Data” |
Key words: power dispatching data network power station safety monitoring network traffic bypass monitoring |