激光与光电子学进展, 2018, 55 (8): 080701, 网络出版: 2018-08-13  

基于暂态电流的S变换与(2D)2PCA的负荷识别 下载: 677次

Load Identification Based on S-Transform and (2D)2PCA of Transient Current
作者单位
天津大学电气自动化与信息工程学院,天津 300072
摘要
针对用户家中电器负荷识别分解问题提出了一种新的特征提取方法。对总线电流进行小波滤波处理,并根据周期差分的方法除去负荷暂态电流的背景电流,获取负荷投切后的暂态电流信号。对负荷的暂态电流进行S变换获取幅值谐波矩阵,并使用双向二维主成分分析[(2D)2PCA]对暂态电流的幅值谐波矩阵从行和列方向进行压缩以提取特征。使用支持向量机对样本特征集进行分类。对BLUED电力数据集的6种家用负荷进行识别,平均识别率为99.24%,最高达到100%。该方法与其他特征提取方法相比,对电气特性相似的负荷具有更高的识别率。
Abstract
For identification and decomposition of domestic appliance load, a new feature extraction method is proposed in this paper. First, we adopt wavelet filtering processing on the bus current and remove the background current from the load transient current by periodic difference. Then S-transform is used for the transient current after load switching to obtain an amplitude harmonic matrix. The matrix is dimensionally reduced and the corresponding features are extracted in the row and column directions by the bidirectional two-dimensional principal component analysis. Finally, the feature data is classified by the support vector machine. The experimental results indicate the proposed feature extraction method has an average recognition accuracy of 99.24% and a maximum recognition accuracy of 100% on six kinds of appliance from the BULED dataset. Especially, the proposed method can provide better performance on differentiating the loads with similar electrical characteristics.

吕卫, 蔡志强, 褚晶辉. 基于暂态电流的S变换与(2D)2PCA的负荷识别[J]. 激光与光电子学进展, 2018, 55(8): 080701. Lü Wei, Cai Zhiqiang, Chu Jinghui. Load Identification Based on S-Transform and (2D)2PCA of Transient Current[J]. Laser & Optoelectronics Progress, 2018, 55(8): 080701.

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