摘要
由于局部放电(PD)信号与含有的混合干扰(白噪和窄带)在能量分布频段上存在明显差异,根据小波包变换各节点分解系数能够有效反映被分析信号能量变化的特点,建立一种以反映PD信号分解系数中噪声能量为判据的浮阈值量化算法,使得最优基下各节点阈值随相应节点分解系数中信号噪声强度的变化而变化,自适应地决定各节点最佳阈值选择,以实现对PD信号分解系数更精细划分。通过对含有混合干扰的仿真与实测PD信号的小波包最优分解,分别用传统全局阈值量化算法与笔者建立的浮阈值量化算法进行了干扰抑制效果的对比,结果表明:后者具有更强的抑制混合干扰的能力,且混合干扰抑制前后PD信号波形相似度更高。
Due to the obvious difference of energy distribution frequencies from partial discharge（PD） signal and its mixing interferences（white-noise and narrow-brand）,we uses the characteristic that node decomposition coefficients of wavelet packet transform can effectively show the energy change of signals to build up a floating threshold quantization algorithm（FTQA） varying with the noise energy of PD decomposition coefficients.It makes the node thresholds under the optimal base various with the noise strength in decomposition coefficients to self-adaptively reality the choice of optimal threshold to finely partition PD decomposition coefficients.For simulated and real PD signals with mixing interferences,the conditional global threshold quantization algorithm（GTQA） and the proposed floating threshold quantization algorithm are employed to suppress the mixing interferences in PD signals and compared,and the results show that the proposed algorithm has the stronger suppression ability to mixing interference on PD signal and keeps perfect PD waveform via suppression.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2012年第7期54-60,共7页
Journal of Chongqing University
基金
国家重点基础研究发展计划项目(973项目)(2009CB724506)
国家自然科学基金资助项目(5177181)
关键词
局部放电
混合干扰
小波包变换
浮阈值量化算法
干扰抑制
partial discharge
mixing interferences
wavelet packet transform
floating threshold quantization algorithm（FTQA）
interference suppression
