| 蔡佳成,高洪鑫,王智勇,徐佳宁,彭继慎.变频器负载回路串联故障电弧检测及选线方法[J].电子测量与仪器学报,2024,38(7):247-256 |
| 变频器负载回路串联故障电弧检测及选线方法 |
| Fault detection and line detection method of series arc faultin frequency converter load circuit |
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| DOI： |
| 中文关键词: 故障电弧 故障检测及选线 变分模态分解 核主成分分析 支持向量机 |
| 英文关键词:arc fault fault detection and line selection variational mode decomposition kernel principal component analysis support vector machine |
| 基金项目:国家自然科学基金（52077158）项目资助 |
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| Author | Institution |
| Cai Jiacheng | Faculty of Electrical and Control Engineering，Liaoning Technical University, Huludao 125105,China |
| Gao Hongxin | Faculty of Electrical and Control Engineering，Liaoning Technical University, Huludao 125105,China |
| Wang Zhiyong | Faculty of Electrical and Control Engineering，Liaoning Technical University, Huludao 125105,China |
| Xu Jianing | Faculty of Electrical and Control Engineering，Liaoning Technical University, Huludao 125105,China |
| Peng Jishen | Faculty of Electrical and Control Engineering，Liaoning Technical University, Huludao 125105,China |
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| 摘要点击次数: 31 |
| 全文下载次数: 260 |
| 中文摘要: |
| 串联故障电弧的高温是引发电气火灾的主要原因之一，针对工业变频器负载回路中串联故障电弧尚无有效保护手段的问题，提出了一种新的串联故障电弧检测及选线方法。首先，针对工业领域常用的三相变频器负载回路开展了不同线路中发生串联故障电弧的实验；其次，利用基于能量收敛原则改进的变分模态分解将变频器前端A相电流信号自适应分解为多个模态分量，依次将单个模态分量乘以能量系数并重构，得到多个电流信号的特征增强信号，并建立特征矩阵；再次，对特征矩阵进行分块，利用核主成分分析对每块矩阵进行降维，并对降维信号组成的矩阵进行二次降维构建故障特征向量；最后，利用鹈鹕算法优化的支持向量机对串联故障电弧进行检测及选线。结果表明：该方法仅通过分析变频器前端A相电流可以实现变频器整个回路中6条线路的串联故障电弧检测及选线，检测及选线准确率均达到98%以上。 |
| 英文摘要: |
| The high temperature of series arc fault is one of the main causes of electrical fire. Aiming at the problem that there is no effective protection method for the series arc fault in the load circuit of industrial frequency converter, a new method of fault detection and line selection for the series arc fault was proposed. First, the series arc fault experiments in different lines were carried out for the load circuit of three-phase frequency converter commonly used in industrial field. Second, the improved variational mode decomposition based on the principle of energy convergence was used to adaptively decompose the A-phase current signal at the front end of the frequency converter into multiple modal components. After multiplying the single modal component by the energy coefficient, the feature enhancement signals of multiple current signals were reconstructed, and the feature matrix was established. Third, the feature matrix was divided into blocks, and the kernel principal component analysis was used to reduce the dimension of each block matrix, and the matrix composed of the reduced dimension signal was reduced twice to construct the fault feature vector. Finally, the support vector machine optimized by the pelican optimization algorithm was used to detect the series arc fault and select the fault line. The results show that the proposed method can realize the fault detection and line selection of the series arc fault in six lines of the whole circuit of the frequency converter only by analyzing the A-phase current signal at the front end of the frequency converter, and the accuracy of fault detection and line selection is more than 98%. |
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