基于B/S模式的运检业务集约数据高质量识别方法

传统的监控运维方法缺乏有效的信息整合和监视,无法实现集约数据高质量识别。为提高数字电网运检业务集约数据识别和监控能力,结合B/S模式,提出基于B/S模式的运检业务集约数据高质量识别方法。结合一体化安全生产管理系统和GIS平台,采样运检业务集约数据的大数据特征,构建运检业务集约设备在线监测模型。结合雷电定位、覆冰监测、电压监测等子系统完成运检业务集约数据的传感信息采样和融合处理。在B/S体系下融合运检业务集约数据,并对其进行集成处理。结合“云大物移智”等技术实现运检业务集约的多源数据融合、分析以及应用处理,将其通过智能网关传输至物联网平台,完成运检业务集约数据高质量识别。实验结果验证了所提方法具有更高的识别精度,提高了电网设备状态在线监测效率和运检业务信息的分析能力。

High-quality identification method of intensive data of operation and inspection service based on B/S mode

The traditional monitoring operation and maintenance method lacks effective information integration and monitoring,and can not realize high quality identification of intensive data.In order to improve the ability of identification and monitoring of intensive data in digital power grid,Combined with the B/S model,a high quality identification method of intensive data based on B/S mode is proposed.Combined with the integrated safety production management system and GIS platform,the online monitoring model of the intensive equipment of transportation and inspection is constructed by sampling the big data characteristics of the intensive data of transportation and inspection.Combined with the subsystem of lightning location,icing monitoring,voltage monitoring and so on,the sensor information sampling and fusion processing of intensive data of transportation and inspection service is completed.Under The B/S system,the intensive data of transportation and inspection are fused and integrated.Combined with technologies such as"Cloud Big mobile intelligence"to realize intensive multi-source data fusion,analysis and application processing of transportation and inspection business,it is transmitted to the Internet of Things platform through an intelligent gateway,so as to complete high quality identification of intensive data of transportation and inspection business.The experimental results verify that the proposed method has higher identification accuracy and improves the efficiency of on-line monitoring of the state of power grid equipment and the ability of analyzing the operation and inspection information.