基于生存分析模型的电力设备故障预测方法

A failure prediction method for power equipments based on survival analysis model

本文基于某地区三年内的电力设备运行和维修数据,对设备发生故障、引起维修费用的概率进行解释,提出一种基于生存分析模型的电力设备维修成本优化方法,分析影响电力设备故障和维修的关键性影响因素。针对大量电力设备的历史运行和维修数据,观察设备从投入生产到发生故障之间的时间间隔,分析设备的众多相关数据特征对于设备故障率的影响,建立Cox比例风险分析模型,并在基准生存率的基础上得到生存率函数,对电力设备的故障率和维修成本做出预测。实验结果表明,本文构建的电力设备维修预测模型能够为电力企业维修决策提供有力的理论依据,解决了电网企业停电成本高、临检频繁、维修不足、维修过度、盲目维修等问题,具有广泛的应用和推广价值。

Based on the operation and maintenance data of power equipment in a certain area within three years,this paper explains the probability of equipment failure and maintenance costs,and proposes a method of power equipment maintenance cost optimization based on survival analysis model,and analyzes the key influencing factors of power equipment failure and maintenance.According to the historical operation and maintenance data of a large number of power equipment,the time interval between the equipment being put into production and the occurrence of failure is observed.The influence of many relevant data characteristics of the equipment on the failure rate of the equipment is analyzed.The Cox proportional risk analysis model is established,and the survival rate function is obtained on the basis of the benchmark survival rate to predict the failure rate and maintenance cost of the power equipment.The experimental results show that the power equipment maintenance prediction model constructed in this paper can provide a strong theoretical basis for the maintenance decision-making of power enterprises,and solve the problems of high power outage cost,frequent temporary inspection,insufficient maintenance,excessive maintenance,blind maintenance and so on.It has a wide range of application and promotion value.