摘要
为解决烟机振动信号受到噪声干扰这一问题,研究基于小波包阈值降噪的原理和方法,给出了小波包阈值降噪的步骤,阐述了Birgé-Massart惩罚函数确定阈值的原则和软阈值的量化处理,分析了阈值、信噪比和均方误差随惩罚因子的变化规律.并将基于小波包惩罚函数的软阈值降噪与Rigrsure、Heursure、Sqtwolog、Minimax4种阈值降噪方法进行了比较.结果表明基于惩罚函数的小波包软阈值方法能有效降低噪声.基于该方法的烟机振动信号降噪在保留信号突变部分的同时,具有良好的光滑性.
To solve the problem of vibration signals acquired from flue gas turbine interfered by noise,the principle and method of wavelet packet-based penalty function soft-threshold denoising are analyzed and its procedure of de-noising is provided.The rule of Birgé-Massart penalty function to determine threshold is clarified and soft-threshold quantization processing is made.Then,the value changes of threshold,SNR and mean square error with the penalty factor are observed and compared with Rigrsure,Heursure,Sqtwolog,Minimax soft-threshold de-noising methods.The results show that the penalty function soft-threshold method can effectively reduce the noise.The de-noised vibration signals of flue gas turbine based on this method can retain mutant part of the signal ,while it still has good smoothness.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2010年第8期906-909,914,共5页
Transactions of Beijing Institute of Technology
基金
国家自然科学基金资助项目(50975020)
北京市人才强教深化计划项目(PHR20090518)
关键词
降噪
振动信号
小波包
软阈值
惩罚函数
de-noising
vibration signals
wavelet packet
soft threshold
penalty function
