基于时间频率特征预测的超高压能源设备的降解警告方法
Pinzhang Zhao1, Lihui Wang2, Jian Wei1
1Jiangsu Institute of Metrology, Nanjing 210023, China.
Sensors (Basel, Switzerland)
|September 19, 2025
概括
本研究介绍了一种改进的算法,用于分析超高压设备中的泄漏电流. 它增强了故障预测,并提供了对电阻板损坏的早期警告.
科学领域:
- 电气工程 电气工程
- 材料科学 材料科学 材料科学
- 信号处理 信号处理
背景情况:
- 在超高压设备中,电阻板的损坏构成重大风险.
- 精确监测泄漏电流对于预测设备故障至关重要.
- 现有的方法与噪音和准确的长期预测作斗争.
研究的目的:
- 为分析泄漏电流特征提出一个改进的算法.
- 为了提高DC特征未来趋势的预测准确度.
- 为了启用对闪电阻塞条件的早期短期警告.
主要方法:
- 开发了一个改进的简单的几何模式分解-波形小包 (ISGMD-WP) 算法.
- 通过改进的嵌入和蒸层,增强了I-Informer预测网络.
- 来自相邻列的综合预测,以减轻电网波动.
主要成果:
- 在强烈噪音下,ISGMD-WP算法获得了1.95的高分解能力评估指数 (EIDC).
- 在长期预测中,I-Informer网络显示了0.02538的低平均绝对误差 (MAE) 和0.03175的根平均平方误差 (RMSE).
- 综合方法使得精确的故障预测和及时警告能耗设备.
结论:
- 拟议的ISGMD-WP算法有效地隔离了泄漏电流的突出波.
- 增强的I-Informer网络准确地预测了DC特征的未来变化.
- 这项研究成功地为超高压能源设备的早期故障预警提供了一种方法.
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