电力设备预警评测数据集

本数据集聚焦电力一次设备（变压器、断路器、GIS、避雷器等）的早期故障预警与状态评估，覆盖油色谱、局部放电、铁芯电流、SF6压力、红外测温等多类监测参量。数据内容包括设备元数据、监测时间序列（小时/日粒度）、异常标签（预警类型、等级、时间偏移）及评测划分。适用于异常检测模型训练、预警阈值优化、多参量融合预警、剩余寿命预测及智能运检系统开发等场景。This dataset focuses on early fault warning and condition assessment for primary power equipment such as transformers, circuit breakers, GIS, surge arresters and other related devices. It covers a variety of monitoring parameters including oil chromatography, partial discharge, core current, SF6 pressure, infrared temperature measurement and more. The dataset includes equipment metadata, monitoring time series (hourly/daily granularity), anomaly labels (warning type, severity level, time offset) and evaluation splits. It is suitable for scenarios including anomaly detection model training, warning threshold optimization, multi-parameter fusion early warning, remaining life prediction and intelligent operation and maintenance system development.

搜集汇总

背景与挑战

背景概述

该数据集专注于电力一次设备（如变压器、断路器和GIS）的早期故障预警与状态评估，涵盖油色谱、局部放电和温度等多种监测参量的时间序列数据，并包含异常标签和评测划分。它适用于异常检测模型训练、预警阈值优化以及智能运检系统的开发。