Ultrasonic Signal Extraction of Transformer Partial Discharge Based on Whitening Filter and RBF-KF

LI Lihua; YANG Xinzhi; BAO Peng; SHEN Zhiyong; LIU Yang

doi:10.13296/j.1001-1609.hva.2026.06.009

您当前的位置：

首页 >

文章列表页 >

Ultrasonic Signal Extraction of Transformer Partial Discharge Based on Whitening Filter and RBF-KF

Research & Analysis | 更新时间：2026-06-10

- Ultrasonic Signal Extraction of Transformer Partial Discharge Based on Whitening Filter and RBF-KF
- High Voltage Apparatus Vol. 62, Issue 6, Pages: 76-83(2026)
- 作者机构：
  
  中国长江电力股份有限公司，北京 100033
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2026.06.009
  CLC：
- Received：21 November 2025，
  
  Revised：2026-01-27，
  
  Published：16 June 2026
- 稿件说明：
移动端阅览
LI Lihua, YANG Xinzhi, BAO Peng, et al. Ultrasonic Signal Extraction of Transformer Partial Discharge Based on Whitening Filter and RBF-KF[J]. High Voltage Apparatus, 2026, 62(6): 76-83.
DOI：

LI Lihua, YANG Xinzhi, BAO Peng, et al. Ultrasonic Signal Extraction of Transformer Partial Discharge Based on Whitening Filter and RBF-KF[J]. High Voltage Apparatus, 2026, 62(6): 76-83. DOI： 10.13296/j.1001-1609.hva.2026.06.009.

摘要

局部放电（partial discharge，PD）是电力变压器出现绝缘劣化的初始迹象，局部放电信号的及时准确提取对于变压器状态监测具有重要意义。然而，受周期性窄带干扰和白噪声等的影响，传统快速傅里叶变换（fast Fourier transformation，FFT）阈值，小波降噪和奇异值分解（singular value decomposition，SVD）等方法噪声抑制性能较差，难以有效提取PD信息。提出一种基于白化滤波和径向基神经网络联合卡尔曼滤波（radial basis function neural network-Kalman filtering，RBF-KF）的变压器PD超声波信号提取方法。首先，根据周期性窄带干扰特征构建白化滤波矩阵，并利用该矩阵对染噪PD信号进行“白化”预处理，将周期性窄带干扰转化为白噪声。然后，建立卡尔曼滤波（Kalman filter，KF）模型进行白噪声抑制，同时针对KF滤波结果易发散问题，利用径向基神经网络（radial basis function neural network，RBF）对滤波误差进行动态修正，提升噪声抑制性能。基于仿真和实测数据的试验结果表明，所提方法噪声抑制性能优良，相对于传统FFT阈值、小波降噪和SVD方法提取的局部放电超声波信号波形畸变小，能量损失少，具有更高的工程应用前景。

Abstract

Partial discharge (PD) is the initial sign of insulation deterioration in power transformer. The timely and accurate extraction of partial discharge signals is of great significance for transformer status monitoring. However

due to the influence of periodic narrowband interference and white noise

the noise suppression performance of such methods as traditional fast Fourier transformation (FFT) thresholding

wavelet denoising

and singular value decomposition (SVD) methods is are weak and are difficult to effectively extract PD information. In this paper

a transformer PD ultrasonic signal extraction method based on whitening filtering and radial basis function neural network-Kalman filtering (RBF-KF) is proposed. First

a whitening filtering matrix is constructed based on the characteristics of periodic narrowband interference signals

and this matrix is then used to preprocess the noise-cotaminated PD signal through wightening

theteby converting the periodic narrowband interference into white noise.Then

the Kalman filter (KF) model is set up for white noise suppression. Meanwhile

to address the issue that KF filtering results are prone to divergence

a radial basis fucntion neutral network (RBF) is used to dynamically correct the filtering errors

thereby improving the noise suppression performance. The experimental results based on simulation and measured data indicate that the proposed method has excellent noise suppression performance. Compared to traditional FFT threshold

wavelet denoising

and SVD methods

the waveforms of the partial discharge ultrasonic signals extracted by the proposed method have less distortion

less energy loss and greater engineering application prospects.

关键词

Keywords

references

程逍,李平,郭凌旭,等.基于量测数据贝叶斯概率矩阵分解的变压器运行状态监测方法[J].电力系统及其自动化学报, 2022,34(1):100-107.

CHENG Xiao, LI Ping, GUO Lingxu, et al. Transformer operation status monitoring method based on Bayesian probabilistic matrix factorization of measured data[J]. Proceedings of the CSU-EPSA, 2022,34(1):100-107.

陈铁,陈卫东,李咸善,等.基于EMD和GCT的变压器油中溶解气体预测[J].高压电器,2022,58(4):70-79.

CHEN Tie, CHEN Weidong, LI Xianshan, et al. Dissolved gas prediction in transformer oil based on EMD and GCT[J]. High Voltage Apparatus,2022,58(4):70-79.

刘振宇,罗日成,俞乾,等.基于高阶累积量的变压器多局放源定位算法研究[J].变压器,2024,61(5):58-64.

LIU Zhenyu, LUO Richeng, YU Qian, et al.Research on multipartial discharge source location algorithm of transformer based on high-order cumulan[J]. Transformer,2024,61(5):58-64.

JAHANGIR H, AKBARI A, AZIRANI M A, et al. Turret-electrode antenna for UHF PD measurement in power transformers-part I:Introduction and design[J]. IEEE Transactions on Dielectrics and Electrical Insulation,2020,27(6):2113-2121.

LIN Jun, SU Lei, YAN Yingjie, et al.Prediction method for power transformer running stage based on LSTM - DBN network[J]. Energies,2018,11(7):1880.

谢庆,张煊宇,王春鑫,等.新一代人工智能技术在输变电设备状态评估中的应用现状及展望[J].高压电器,2022,58(11):1-16.

XIE Qing, ZHANG Xuanyu, WANG Chunxin, et al. Application status and prospect of the new generation artificial intelligence technology in the state evaluation of power transmission and transformation equipment[J]. High Voltage Apparatus,2022,58 (11):1-16.

贾骏,陶风波,杨强,等.复杂多径传播条件下变压器局部放电定位方法研究[J].中国电机工程学报,2022,42(14):5338-5347.

JIA Jun, TAO Fengbo, YANG Qiang, et al. Research on partial discharge location method of transformer under complex multipath propagation[J]. Proceedings of the CSEE,2022,42(14):5338-5347.

付文光,薛利军,郑璐,等.油纸绝缘匝间放电超声信号的发展特性和放电阶段识别方法[J].电网与清洁能源,2025,41 (12):85-93.

FU Wenguang, XUE Lijun, ZHENG Lu, et al. Development characteristics of ultrasonic signals from inter-turn discharge in oilpaper insulation and identification methods for discharge stages[J].Power System and Clean Energy,2025,41(12):85-93.

万晓琪,宋辉,罗林根,等.卷积神经网络在局部放电图像模式识别中的应用[J].电网技术,2019,43(6):2219-2226.

WAN Xiaoqi, SONG Hui, LUO Lingen, et al. Application of convolutional neural networks in pattern recognition of partial discharge image[J]. Power System Technology,2019,43(6):2219-2226.

ROY S S, CHATTERJEE S. Partial discharge detection framework employing spectral analysis of horizontal visibility graph[J]. IEEE Sensors Journal,2021,21(4):4819-4826.

尚海昆,张冉喆,黄涛,等.基于CEEMDAN-TQWT方法的变压器局部放电信号降噪[J].电力科学与技术学报,2024,39(1):272-284.

SHANG Haikun, ZHANG Ranzhe, HUANG Tao, et al. Partial discharge signal denoising based onCEEMDAN-TQWTmethod for power transformers[J].Journal of Electric Power Science and Technology,2024,39(1):272-284.

樊高辉,刘尚合,刘卫东,等. FFT谱最小熵解卷积滤波抑制放电信号中的周期性窄带干扰[J].高电压技术,2017,43(4):1378-1385.

FAN Gaohui, LIU Shanghe, LIU Weidong, et al. Suppression of the periodic narrow - band noise in discharge signal by FFT spectrum minimum entropy deconvolution filtering[J]. High Voltage Engineering,2017,43(4):1378-1385.

叶兆平,曾静岚,于利颖,等.地线外置式局部放电射频信号检测方法及其应用[J].高压电器,2022,58(10):188-195.

YE Zhaoping, ZENG Jinglan, YU Liying, et al. Detection method and application of external partial discharge radio frequency signals of grounding wire[J]. High Voltage Apparatus,2022,58 (10):188-195.

倪鹤立,姚维强,傅晨钊,等.电力设备局部放电技术标准现状述评[J].高压电器,2022,58(3):1-15.

NI Heli, YAO Weiqiang, FU Chenzhao, et al. Review on status of technical standards of partial discharge in electrical equipment[J]. High Voltage Apparatus,2022,58(3):1-15.

程万胜,岳伦,付振贺,等.基于小波变换的变压器局放信号超声直达波提取[J].电测与仪表,2013,50(9):46-50.

CHENG Wansheng, YUE Lun, FU Zhenhe, et al. Ultrasonic direct wave extraction of transformer partial discharge signal based on wavelet transform[J]. Electrical Measurement & Instrumentation, 2013,50(9):46-50.

吴杰.基于改进小波变换和随机森林的GIS局部放电故障识别系统[J].电子设计工程,2025,33(13):138-143.

WU Jie. GIS partial discharge fault identification system based on improved wavelet transform and random forest[J].Electronic Design Engineering,2025,33(13):138-143.

钱定冬,宋柯,谢虎波,等.基于GCC-MSSA的变压器局放超声内部定位方法[J].电子测量技术,2023,46(3):134-141.

QIAN Dingdong, SONG Ke, XIE Hubo, et al. Transformer partial discharge ultrasound internal positioning method based on GCC-MSSA[J]. Electronic Measurement Technology ,2023 ,46(3):134-141.

施胜丹,黄金军,朱霄珣,等.基于声纹SDP-CNN的变压器局部放电模式识别[J].电力信息与通信技术,2022,20(10):105-112.

SHI Shengdan, HUANG Jinjun, ZHU Xiaoxun, et al. Partial discharge pattern recognition on transformer based on voiceprint SDP-CNN[J]. Electric Power Information and Communication Technology,2022,20(10):105-112.

孙抗,李万建,张静.含窄带噪声和白噪声的复杂染噪局部放电信号提取及应用[J].电子科技大学学报,2021,50(1):14-23.

SUN Kang, LI Wanjian, ZHANG Jing. Denoising of complex noisy partial discharge pulses with narrowband interference and white noise[J]. Journal of University of Electronic Science and Technology of China,2021,50(1):14-23.

张重远,岳浩天,王博闻,等.基于相似矩阵盲源分离与卷积神经网络的局部放电超声信号深度学习模式识别方法[J].电网技术,2019,43(6):1900-1906.

ZHANG Chongyuan, YUE Haotian, WANG Bowen, et al. Pattern recognition of partial discharge ultrasonic signal based on similar matrix BSS and deep learning CNN[J]. Power System Technology, 2019,43(6):1900-1906.

LUO Yuanlin, LI Zhaohui, WANG Hong. A review of online partial discharge measurement of large generators[J]. Energies,2017,10 (11):1-32.

谢敏,周凯,何珉,等.史坦无偏估计自适应奇异值分解在局放信号白噪声抑制中的应用[J].电网技术,2018,42(12):4153-4159.

XIE Min, ZHOU Kai, HE Min, et al. Application of adaptive singular value decomposition based on stein unbiased risk estimation in partial discharge signal white noise suppression[J]. Power System Technology,2018,42(12):4153-4159.

徐永干,姜杰,唐昆明,等.基于Hankel矩阵和奇异值分解的局部放电窄带干扰抑制方法[J].电网技术,2020,44(7):2762-2769.

XU Yonggan, JIANG Jie, TANG Kunming, et al. A method of suppressing narrow-band interference in partial discharge based on hankel matrix and singular value decomposition[J]. Power System Technology,2020,44(7):2762-2769.

杨晓丽,黄宏光,舒勤,等.基于SVD和低秩RBF神经网络的局部放电信号提取方法[J].高电压技术,2021,47(10):3608-3616.

YANG Xiaoli, HUANG Hongguang, SHU Qin, et al. Partial discharge signal extraction method based on SVD and low rank RBF neural network[J]. High Voltage Engineering,2021,47(10):3608-3616.

尚彦鬓,宋红为,杨照光,等.基于二阶RC模型的锂电池充放电特性分析[J].高压电器,2023,59(7):87-94.

SHANG Yanbin, SONG Hongwei, YANG Zhaoguang, et al. Charge and discharge characteristics analysis of lithium battery based on second-order RC model[J]. High Voltage Apparatus,2023,59(7):87-94.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

EEMD Partial Discharge De-noising Method Based on Correlation Coefficients

The Method of Eliminating White Noise at On - line detection of Partial Discharge by Wavelet Analysis

A New Neural Network for Fault Diagnosis of Partial Discharge in Power Transformers

Test Equipment of UHV Transformer’s AC Withstand Voltage and Partial Discharge Tests

Simulation Study on Influence of Array Number of Square Planar Array Sensor to PD Direction Finding Accuracy

Related Author

PENG Weiwen

LIU Weijie

XU Jiahao

ZHENG Zhenfeng

LIN Yongyi

HUANG Linghui

杨永明

孙才新

Related Institution

Quanzhou Power Supply Company,Fujian Electric Power Corporation

Shanghang Power Supply Company,Fujian Electric Power Corporation

重庆大学

重庆大学 400044

College of Automation,Northwestern Polytechnic University

⁰