使用溶气分析传感器数据和杜瓦尔多边形的电力变压器的概率预测和健康管理
Fabio Norikazu Kashiwagi1, Miguel Angelo de Carvalho Michalski1, Gilberto Francisco Martha de Souza1
1Department of Mechatronics and Mechanical Systems Engineering, Polytechnic School, University of São Paulo, Avenida Professor Mello de Moraes 2231, São Paulo 05508-030, SP, Brazil.
Sensors (Basel, Switzerland)
|November 13, 2025
概括
本研究引入了使用溶解气体分析 (DGA) 进行功率变压器健康管理的新概率框架. 它通过分析气体趋势与不确定性量化来改善早期故障检测和预测性维护.
科学领域:
- 电气工程 电气工程
- 材料科学 材料科学 材料科学
- 数据科学数据科学数据科学
背景情况:
- 电力变压器故障会导致严重的电网中断和财务损失.
- 传统的溶解气体分析 (DGA) 方法使用确定性值,忽视降解的不确定性.
- 关键电网资产的状态监测需要先进的诊断技术.
研究的目的:
- 开发一个概率框架,用于电力变压器的预测和健康管理 (PHM).
- 为了实现自动化故障类型估计和基于DGA数据的故障概率评估.
- 增强电力变压器的预测性维护策略.
主要方法:
- 自适应的自动回归集成移动平均 (ARIMA) 建模与概率的杜瓦尔图形方法的集成.
- 时间序列预测溶解气体动力学与基于残余的不确定性量化.
- 为实时故障跟踪和可靠性评估开发一个连续管道.
主要成果:
- 拟议的框架允许在不依赖标记数据集或专家规则的情况下进行概率错误推断.
- 通过案例研究证明了诊断可靠性和早期故障检测能力的提高.
- 根据电力系统组件的国际标准 (IEC,IEEE,CIGRE) 进行验证.
结论:
- 概率框架为启用传感器的电网提供了一个实用和可解释的PHM解决方案.
- 通过准确预测溶解气体趋势,可以实现增强的预测性维护策略.
- 这种方法解决了电力变压器监控中的确定性诊断方法的局限性.
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