Power Supply Quality Analysis Using S-Transform and SVM Classifier

• 作者: Jiaqi Li M. V. Chilukuri
• 来源期刊: 电力能源(英文)
• 学科: 医学
• 关键词: POWER QUALITY DISTURBANCE S-TRANSFORM SVM
• 年，卷（期）: 2014,（4）
• 页码范围: 438-447
• 页数: 10页
• 分类号: R73

摘要

In this paper, a SVM classifier based on S-Transform is presented for power quality disturbances classification. Firstly, seven types of PQ events are created using Matlab simulation. These signals are analyzed to detect and localize PQ events via S-Transform by visual inspection. Then five significant features of the PQ disturbances are extracted from the S-Transform output. Afterwards, PQ disturbance samples with the five features are fed to SVM for training and automatic classification. Besides, particle swarm optimization is implemented to improve the performance of SVM. The results of the classification indicate that SVM classifier is an effective mechanism to detect and classify power quality disturbances.