![基于多维数据的输电设备状态评价及风险分析方法及装置](/CN/2016/1/172/images/201610862079.jpg)
基本信息:
- 专利标题: 基于多维数据的输电设备状态评价及风险分析方法及装置
- 专利标题(英):Power transmission device state evaluation and risk analysis method and device based on multidimensional data
- 申请号:CN201610862079.8 申请日:2016-09-28
- 公开(公告)号:CN106469356A 公开(公告)日:2017-03-01
- 发明人: 阮羚 , 陈孝明 , 李红云 , 马琳 , 黄俊杰 , 王毅 , 方圆 , 吴琼
- 申请人: 国家电网公司 , 国网湖北省电力公司电力科学研究院 , 北京国网富达科技发展有限责任公司
- 申请人地址: 北京市西城区西长安街86号
- 专利权人: 国家电网公司,国网湖北省电力公司电力科学研究院,北京国网富达科技发展有限责任公司
- 当前专利权人: 国家电网公司,国网湖北省电力公司电力科学研究院,北京国网富达科技发展有限责任公司
- 当前专利权人地址: 北京市西城区西长安街86号
- 代理机构: 北京三友知识产权代理有限公司
- 代理人: 王涛; 汤在彦
- 主分类号: G06Q10/06
- IPC分类号: G06Q10/06 ; G06Q50/06
The invention provides a power transmission device state evaluation and risk analysis method and device based on multidimensional data and relates to the technical field of meteorological and electric power technology application. The method comprises steps of: acquiring and storing information data of a PMS production management system, information data of a power transmission and transformation monitoring system and information data of a meteorological bureau system through multidimensional heterogeneous data access; carrying out data preprocessing on the information data of the power transmission and transformation monitoring system and generating online monitoring effective data of a power transmission circuit; determining a power transmission device evaluation index according to the information data of the PMS production management system and the online monitoring effective data of the power transmission circuit, and determining an evaluation state corresponding to the power transmission device evaluation index according to a preset state evaluation strategy; and determining a risk index of the power transmission device according to the information data of the meteorological bureau system, the asset value of the power transmission device, the asset loss value of the power transmission device and the average fault rate of the power transmission device. According to the invention, the multidimensional data is comprehensively considered.