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基于无线通信和图像识别的馈线自动化现场自动测试 被引量:3

Field Automatic Test of Feeder Automation Based on Wireless Communication and Image Recognition
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摘要 为了进一步提升配电自动化系统故障处理性能的测试方法,提出了一种基于无线通信和图像识别的馈线自动化现场自动测试法。该方法需要在拟模拟故障区段上游的各个配电自动化终端二次侧,安置若干研发的移动测试装置。由测试主控平台借助于加密的私有无线通信通道,分别向每个移动测试装置下发测试方案数据,控制移动测试装置在同一时刻向被测试配电网注入拟模拟故障场景的电流、电压波形,并借助图像识别技术对测试结果进行采集及正确性判别。结合现场实例测试说明了所提出方法不仅不受待测主站厂家不同的限制,而且不要求配电主站开放权限,与配电自动化主站系统之间没有进行信息交互,从而保障了配电自动化主网的安全,实现了携带少量设备进行大规模配电网自动测试,有效地降低了对现场测试人员的技术要求以及沟通难度,提高了测试效率。 In order to improve the fault isolation and restoration test method of distribution automation system,a test method based on wireless communication and image recognition for distribution network is proposed.In this method,a number of mobile testing devices need to be installed at the secondary side of each distribution automation terminal in the upstream of the simulated fault segment.With the help of encrypted private wireless communication channels,the test scheme datais distributed to each mobile device respectively through the test master control platform,the mobile test devices are controlled to inject the current and voltage waveform of the simulated faulty scene to the tested distribution network,and with the help of image recognition technology,the test results are collected and their correctness is determined.The field test indicates that the proposed method is not subject to the different constraints of master station,nor does it require the open authority of the distribution master station,and there is no direct information interaction with the main station of the distribution automation system,sothe security of distribution automation network is guaranteed,the large-scale distribution network automatic test with a small amount of equipment is realized,the workload and difficulty of the test personnel are effectively reduced,and the test efficiency is greatly improved.
作者 刘彬 李盼
出处 《无线电通信技术》 2018年第2期202-206,共5页 Radio Communications Technology
基金 国网陕西省电力公司科技项目(5226KY15000P)
关键词 馈线自动化 无线通信 图像识别 自动 自动测试 feeder automation wireless communication image recognition auto-correct automatic test
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