干扰(通信)
聚类分析
分离(统计)
功率(物理)
时频分析
电子工程
计算机科学
局部放电
信号(编程语言)
算法
工程类
人工智能
物理
电压
电气工程
电信
机器学习
频道(广播)
雷达
量子力学
程序设计语言
作者
Kai Zhou,Zerui Li,Guangya Zhu,Yonglu Huang,Yuan Li
标识
DOI:10.1109/tim.2021.3054024
摘要
Frequency-tuned resonant (ACRF) test is one of the most widely used technologies for power equipment diagnosis. However, the intense interference generated by the variable-frequency power source hinders its further application in partial discharge (PD) detection. For this reason, an adaptive PD separation method based on improved clustering by fast search and find of density peaks (CFSFDP) is proposed in this article to separate PD signals and disturbances under the ACRF test. First, the characteristics of the PD signals and the interference signals generated from the ACRF test system are analyzed and compared. Then, an improved CFSFDP algorithm is proposed to realize the automatic cluster center selection and signal separation, and the working principle of the PD separation strategy based on the improved CFSFDP algorithm is introduced. Finally, the effectiveness of the proposed method is validated by performing the ACRF test on a defective cable. The experimental results show that this method can realize the separation and detection of PD signals in ACRF tests. The proposed method provides a feasible solution for performing PD detection using the ACRF test system without the restriction of the test system structure.
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