基于IAR-BTR的SF6高压断路器运行状态评估模型
Ningfang Wang1, Yujia Wang2, Yifei Zhang1
1School of Electrical & Information Engineering, Changsha University of Science & Technology, Changsha 410114, China.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
本研究引入了一种新的模型,通过整合内部和环境因素来评估硫六化物 (SF) 高压断路器的运行状态. 该模型提高了可靠电网运行的预测准确性.
科学领域:
- 电气工程 电气工程
- 电力系统 电力系统
- 可靠性工程可靠性工程
背景情况:
- 硫六化物 (SF) 高压断路器对于电网保护至关重要,其运行状态直接影响电网可靠性.
- 越来越多的极端天气事件需要考虑内部和外部因素来准确预测这些断路器的运行状态.
- 现有的方法可能会与不完整的数据,特征失衡以及识别空间时间非静止的风险因素作斗争.
研究的目的:
- 为SF6高压断路器提出一个整合内部和环境影响的运行状态评估模型.
- 解决故障记录数据库中不完整性和特征不平衡等数据挑战.
- 识别和准确权衡影响断路器故障的时空非静止因素,特别是在低概率的季节性条件下.
主要方法:
- 实现了缺失值消除 (Drop方法) 和故障记录数据库的数据规范化.
- 采用精细的关联规则挖矿技术,根据季节性分布和时间段的重要性调整值和指标.
- 开发了分支-树干规则的定量权衡方法,并利用了DFP-Growth算法来提高计算效率.
主要成果:
- 拟议的基于分支-树干规则 (IAR-BTR) 的综合属性权衡风险模型有效地整合了内部和环境因素.
- 确定了与特定季节条件下的断路器故障有很强的空间时间非静止因素的强烈相关性.
- 在运行状况评估中实现了高准确度 (95.78%) 和精度 (97.22%),显著提高了预测性能.
结论:
- IAR-BTR模型为评估高压断路器的运行状态提供了一个强大的框架.
- 该方法通过考虑一组全面的内部和环境影响来提高预测故障的能力.
- 这一进步对于确保安全和稳定的电网运行以及防止主要电力系统故障至关重要.
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