使用频率响应分析和先进的数据可视化技术识别变压器线圈缺陷
Abdoallah Hosseini1, Ali Abbasi2, Ali Reza Abbasi3
1Department of Electrical Engineering, Bu.C. Islamic Azad University, Bushehr, Iran.
Scientific reports
|November 18, 2025
概括
早期检测变压器绕线故障对于电网可靠性至关重要. 本研究介绍了使用因子分析,模糊集群分析和主要组件分析的先进数据可视化技术,以简化频率响应分析的解释并提高故障诊断的准确性.
科学领域:
- 电气工程 电气工程
- 电力系统分析 分析 分析
- 诊断技术 诊断技术
背景情况:
- 变压器在电力网络中至关重要,面临的压力可能会导致微妙的绕线故障.
- 这些故障的早期检测对于防止重大故障和确保电网稳定性至关重要.
- 频响应分析 (FRA) 是一种常见的诊断工具,但其复杂的结果阻碍了解释.
研究的目的:
- 开发先进的数据可视化技术,用于解释频率响应分析 (FRA) 结果.
- 为了提高早期预测和诊断变压器上故障.
- 简化工程师和操作人员对FRA数据的解释.
主要方法:
- 使用因子分析来识别复杂的,隐藏的故障因素.
- 利用模糊集群分析来检测不确定性的组合故障条件.
- 应用主要组件分析,以减少数据的维度和增强可解释性.
- 开发了一种两阶段识别模型,用于健康/故障区分和随后的故障分类.
主要成果:
- 提出的技术有效地提取了频率响应特征,以准确识别故障.
- 实验结果表明,在诊断变压器绕线故障方面,其准确度很高.
- 这些方法成功地区分了健康和故障的变压器条件.
- 在有缺陷的条件下,故障分类能够以显著的准确度实现.
结论:
- 先进的数据可视化技术简化了用于变压器故障诊断的FRA解释.
- 开发的方法减少了对故障诊断和分类的专业专业知识的需求.
- 这种方法提供了一种更有效和更容易获得的方法来诊断变压器上故障.
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