基于数据挖掘的现场作业风险态势评估方法

为保障电网安全稳定运行,减少生产安全事故，供电企业针对大量的基建、生产运行作业开展现场安全管理，积累了海量作业管理及安全管理业务数据。为更好地应用这些数据，使其真正为供电企业作业风险预警及防控服务，在梳理供电企业现场作业全过程的数据基础上，对作业风险态势要素历史数据进行分析，识别出人、机、料、法、环境和管理等风险影响因素，从人员、设备（机械）、材料工器具、作业方法、作业环境与时间管理6个维度构建现场作业风险评估指标体系及作业安全态势指数模型，结合信息技术，开展风险态势智能评估的工具设计。

Risk Situation Assessment Method of Field Operation Based on Data Mining

In order to ensure the safe and stable operation of power grid and reduce production safety accidents, power supply companies carry out on-site safety management for a large number of infrastructure, production and operation operations, and have accumulated massive operational management and safety management business data. In order to make better use of these data and make it truly serve for early warning, prevention and control of operational risks of power supply enterprise, on the basis of combing the data of the entire process of field operations of power supply companies, the historical data of operational risk situation factors are analyzed to identify risk influencing factors such as human, machine, material, law, environment and management. The field operation risk assessment index system and operation safety situation index model are constructed from six dimensions including personnel, equipment (machinery), materials and appliances, operation methods, operation environment,  and time management. Combined with information technology, the tool design of intelligent risk situation assessment is carried out.