基于超声波传感器与孤立森林的光伏系统串联电弧故障诊断方法

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摘要针对大部分光伏电站电弧故障历史数据缺乏的问题,本文在采集电弧超声信号并分析其特点后,提出一种基于超声波传感器与孤立森林的光伏系统串联电弧故障诊断方法。首先,利用S变换将发生串联电弧故障时的超声波暂态电压信号转化至时频域;接着,利用Teager能量算子放大频谱差异性,并通过时频熵提取电弧故障时频域特征;最后,基于动态阈值与孤立森林实现电弧故障诊断且无需历史数据。实验结果表明,所提方法能准确识别串联电弧故障,诊断准确率达到97.25%,且具备较强的抗干扰能力。

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	黄晨昊
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关键词 ：光伏系统, 电弧故障诊断, 超声波信号, S变换, 孤立森林

Abstract：Aiming at the problem of the lack of historical data on arc faults in most photovoltaic power stations, this paper proposes a photovoltaic system series arc fault diagnosis method based on ultrasonic sensors and isolation forest after collecting arc ultrasonic signals and analyzing their characteristics. Firstly, arc ultrasonic signals are collected and their characteristics and advantages are analyzed. Secondly, the S-transform is used to convert the transient voltage signal of the ultrasonic wave during the occurrence of series arc faults to the time-frequency domain. Then, the Teager energy operator is used to amplify the spectral differences. Subsequently, the time-frequency entropy is used to extract the time-frequency domain features of arc faults. Finally, arc faults are diagnosed based on dynamic thresholds and isolation forest without the need for historical data. Experimental results show that the proposed method can accurately identify series arc faults, with a diagnosis accuracy rate of 97.25%, and has strong anti-interference ability.

Key words： photovoltaic system arc fault diagnosis ultrasonic signal S-transform isolation forest

收稿日期: 2025-01-09

作者简介: 黄晨昊（2000—）,男,福建省宁德市人,硕士研究生,主要从事光伏系统电弧故障检测与定位方面的研究工作。

引用本文:

黄晨昊, 高伟. 基于超声波传感器与孤立森林的光伏系统串联电弧故障诊断方法[J]. 电气技术, 2025, 26(5): 10-16. HUANG Chenhao, GAO Wei. Series arc fault diagnosis method for photovoltaic system based on ultrasonic sensor and isolation forest. Electrical Engineering, 2025, 26(5): 10-16.

链接本文:

https://dqjs.cesmedia.cn/CN/Y2025/V26/I5/10

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