功率变压器故障诊断方法基于多源信号融合和快速光谱相关性
Shan Guan1, Mingyu Shi2, Fuwang Wang1
1School of Mechanic Engineering, Northeast Electric Power University, Jilin, 132012, China.
Scientific reports
|February 26, 2025
概括
这项研究引入了一种新的电力变压器故障诊断方法,使用多源振动信号融合和快速光谱相关性. 与传统方法相比,先进的技术显著提高了故障识别的准确性.
科学领域:
- 电气工程 电气工程
- 信号处理 信号处理
- 人工智能的人工智能
背景情况:
- 单个传感器测量提供不完整的功率变压器故障状态描述.
- 手动经验往往决定了故障诊断的信号特征的选择,引入了主观性.
研究的目的:
- 开发一种先进的电力变压器故障诊断方法.
- 为了克服单个传感器分析和手动功能选择的局限性.
主要方法:
- 从变压器外上的多个传感器同步收集振动信号.
- 使用关联函数权重的多源信号的融合.
- 应用快速光谱相关性来生成图像样本.
- 使用转移学习进行故障分类,训练一个MobileNetV3模型.
主要成果:
- 拟议的方法实现了98.75%的整体识别准确度.
- 这比单个传感器诊断有10.52%的改进.
- 它还显示了10.86%的改善与其他经典的基于图像的诊断相比.
结论:
- 开发的方法为电力变压器故障诊断提供了强大而准确的工具.
- 多源信号融合和快速光谱相关性增强了诊断能力.
- 这种方法为使用振动信号监测变压器健康提供了一种新的解决方案.
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