作者：陈晓娟, 申雅茹, 陈东阳

作者单位：东北电力大学信息工程学院, 吉林 吉林 132012

关键词：模拟电路;爆裂噪声;EMD;小波模极大值

摘要：

该文应用一种新型的非线性非稳态信号处理方法希尔伯特黄变换(hibert huang tramsform,HHT)进行逆变器中低频噪声-爆裂噪声的检测与定位,该方法利用经验模态分解(empirical mode decomposition,EMD)将待测信号分解为各基本模态分量(intrinsic mode function,IMF),然后对所得IMF进行自适应阈值去噪。经希尔伯特变换(hilbert transform,HT)后,其瞬时振幅与瞬时频率即可清晰表现出爆裂噪声特点与准确突变位置与时长。通过与小波去噪和小波模极大值去噪检测进行对比分析可得,该方法可以同时从时频两方面对信号进行分析,能够实现对故障信号的准确检测与定位。

Research on the application of HHT in burst noise detection

CHEN Xiaojuan, SHEN Yaru, CHEN Dongyang

College of Information Engineering, Northeast Dianli University, Jilin 132012, China

Abstract: HHT (hibert-huang tromsform) method is used in this paper for low frequency noise in the inverter circuit-burst noise detection and location, the method using empirical mode decomposition (EMD) decomposed signal into the basic modal component under test the intrinsic mode function(IMF), and then use adaptive threshold de-noising to the IMF. By the hilbert transform(HT), the instantaneous amplitude and instantaneous frequency can clear performance burst noise characteristics and mutation position and length accurately. With the wavelet denoising and wavelet modulus maxima de-noising detection were analyzed. The simulation analysis show that, the method can simultaneously from two aspects of time and frequency analysis of signals, can realize the accurate detection and location of the fault signal.

Keywords: analog circuit;burst noise;EMD;wavelet modulus maxima

2015, 41(8): 79-82  收稿日期: 2014-11-19;收到修改稿日期: 2014-12-11

基金项目: 国家自然科学基金(61271115)

作者简介: 陈晓娟(1970-),女,吉林长春市人,教授,博士,研究方向为模拟电路故障诊断及电力线通信。

参考文献

[1] 李天云,赵妍,季小慧,等. HHT方法在电力系统故障信号分析中的应用[J]. 电工技术学报,2005,20(6):87-91.
[2] 李文帆,刘志刚,孙婉璐,等. 基于HHT的电能质量检测新方法[J]. 电力系统保护与控制,2011,25(17):52-56.
[3] 杨宇,于德介,程军圣. 基于EMD的奇异值分解技术在滚动轴承故障诊断中的应用[J]. 振动与冲击,2005,
24(2):12-15.
[4] 行鸿彦,黄敏松. 基于Hilbert-Huang变换的QRS波检测算法研究[J]. 仪器仪表学报,2009,30(7):1469-1475.
[5] Huang N E,Shen S P. Hilbert-huang transform and its applications[J]. Interdisciplinary Mathematical Sciences,2005,8(6):1067-1074.
[6] Huang N E, Zheng S, Long S R, et al. The empiri-cal mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society A:Mathematical,Physical and Engineering Sciences,1998,2(1971):330-335.
[7] Huang N E. Review of empirical mode decomposition[J]. Proceedings of SPIE the in Ternational Society for Optical Engineering,2001,4(13):321-325.
[8] 许童羽,甄红芳,曹英丽,等. 电压扰动定位中小波与HHT性能分析[J]. 沈阳农业大学学报,2013,44(1):112-114.