Radiated Noise Prediction for Large Power Transformer Tank

MO Juan; SU Junshou; LIU Jixuan; ZHANG Weiwei; CHEN Hualing; CAO Meigen

doi:10.13296/j.1001-1609.hva.2014.04.003

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Radiated Noise Prediction for Large Power Transformer Tank

更新时间：2025-04-26

- Radiated Noise Prediction for Large Power Transformer Tank
- High VoltageApparatus Vol. 50, Issue 4, Pages: 12-16+22(2014)
- 作者机构：
  
  1. 西安交通大学
  2. 中国电力科学研究院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2014.04.003
  CLC： TM41
- Published：2014
- 稿件说明：
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[1]莫娟,苏俊收,刘吉轩,张伟为,陈花玲,曹枚根.大型电力变压器油箱辐射噪声预估研究[J].高压电器,2014,50(04):12-16+22.

MO Juan, SU Junshou, LIU Jixuan, et al. Radiated Noise Prediction for Large Power Transformer Tank[J]. High voltageapparatus, 2014, 50(4): 12-16+22.
[1]莫娟,苏俊收,刘吉轩,张伟为,陈花玲,曹枚根.大型电力变压器油箱辐射噪声预估研究[J].高压电器,2014,50(04):12-16+22. DOI： 10.13296/j.1001-1609.hva.2014.04.003.

MO Juan, SU Junshou, LIU Jixuan, et al. Radiated Noise Prediction for Large Power Transformer Tank[J]. High voltageapparatus, 2014, 50(4): 12-16+22. DOI： 10.13296/j.1001-1609.hva.2014.04.003.

摘要

针对电力变压器噪声分析的工程需求

开展了基于间接边界元理论的大型电力变压器的油箱辐射噪声预估研究

运用LMS大型声学软件建立了变压器油箱声场计算模型

并采用实测的变压器油箱表面法向振动加速度预估了变压器油箱辐射噪声声场。通过数值仿真结果与实测结果对比分析表明

文中提出的噪声预估方法对于预估变压器油箱辐射噪声声场是有效的和可行的

通过改变变压器油箱的结构

可为电力变压器的低噪声设计提供参考依据。

Abstract

Radiated noise field prediction of large power transformer tanks is studied based on indirect boundary element theory for engineering purpose. First

an acoustic model of transformer tank is established with the acoustics software LMS

and the radiated noise field of the transformer tank is predicted by using measured acceleration data of normal vibration on the transformer tank surface. Comparison between simulation and experiment results shows that the proposed noise prediction method is effective and feasible for predicting the radiated noise field of transformer tank. This study may provide a reference for the design of low-noise power transformers.

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Related Author

MO Juan

LIU Jixuan

SU Junshou

CHEN Hualing

CAO Meigen

TIAN Lin

ZHANG Da

LIU Zhen

Related Institution

China Electric Power Research Institute of SGCC

School of Mechanical Engineering, Xi’an Jiaotong University

State Grid Hebei Electric Power Co., Ltd.

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Wuhan University

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