摘要
传统的计划式电缆检修方法能够显著降低电缆故障率,但却存在如检修不足或过剩、盲目检修等问题。为了提升电缆检修的效率,文章以电缆大数据分析技术为基础,提出了一套电缆智能检修框架。检修框架依据电力运行单位积累的大量电缆及电缆通道状态监测、电缆检修等数据,通过循环神经网络等大数据建模关键技术,实现对电缆运行状态的动态评估和检修任务的智能安排。该技术框架能在降低检修成本的同时提升检修的实际效果,提高检修工作的智能化水平。
The traditional cable maintenance methods can significantly reduce the cable failure rate, but there are some problems, such as insufficient or over maintenance, as well as blind maintenance. In order to improve the efficiency of cable maintenance, this paper proposes a set of intelligent framework based on big data analysis technology. The framework aims to realize the dynamic evaluation of cable running state and intelligent scheduling of maintenance tasks, according to the analysis of cable and cable channel status monitoring, cable maintenance and other data accumulated by electric power operation units. The essential techniques involved are such big data modeling algorithms as recurrent neural network. The technical framework can reduce the maintenance cost and improve the actual effect of maintenance, thus to improve the intelligent level of maintenance work.
作者
杨丹
夏荣
王昱力
蒙绍新
YANG Dan;XIA Rong;WANG Yu-li;MENG Shao-xin(China Electric Power Research Institute,Wuhan 430074,Chin)
出处
《电力信息与通信技术》
2018年第7期64-68,共5页
Electric Power Information and Communication Technology
基金
中国电科院创新基金"基于电力大数据平台的电缆检修决策模型研究"(GY83-17-005)
国家电网公司总部科技项目资助"城市廊道电缆优化及运行技术"(SGTYHT/14-JS-188)
关键词
电缆检修
大数据分析
神经网络
技术框架
cable maintenance
big data analysis
neural network
technical framework
