A New FXLMS Algorithm With Offline and Online Secondary-Path Modeling Scheme for Active Noise Control of Power Transformers

被引：49

作者：

Zhao, Tong ^{[1
]}

Liang, Jiabi ^{[1
]}

Zou, Liang ^{[1
]}

Zhang, Li ^{[1
]}

机构：

[1] Shandong Univ, Sch Elect Engn, Jinan 250061, Peoples R China

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2017年 / 64卷 / 08期

基金：

中国国家自然科学基金;

关键词：

Active noise control (ANC); convergence coefficient; filter-X least mean square (FXLMS); genetic algorithm (GA); power transformer noise; secondary-path (SP) online modeling; CONTROL SYSTEMS; LMS ALGORITHM; ROBUST;

D O I：

10.1109/TIE.2017.2682043

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this study, the active noise control (ANC) method was used to suppress high-decibel and low-frequency power transformer noise. An appropriate ANC system was selected based on the transformer noise characteristics and experimental condition. A new filter-X least mean square (FXLMS) adaptive ANC algorithm based on offline and online secondary-path modeling was proposed to realize faster and more stable secondary-path online modeling than that of the random white-noise FXLMS algorithm and to ensure the convergence, stability, and reduction in transformer noise control. Moreover, the genetic algorithm is adopted to optimize the convergence coefficient, while the effect of the convergence coefficient on the algorithm was analyzed using simulation and theory. In addition, the transformer noise online monitoring and active control system was designed including software and hardware, and the hardware devices were selected based on the noise feature. In the 50 000 KVA transformer noise reduction experiment, the system achieved a noise reduction of 8-15 dB and an 84.10-96.86% decrease in average sound energy density in a certain area.

引用

页码：6432 / 6442

页数：11

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