基于改进MCKD方法的声发射信号降噪  

De-noising Method of Acoustic Emission Signal Based on Improved MCKD

作　　者：张晓涛[1] 唐力伟[1] 王平[1] 邓士杰[1] 

机构地区：[1]军械工程学院火炮工程系,河北石家庄050003

出　　处：《机械设计与研究》2015年第1期70-73,77,共5页Machine Design And Research

基　　金：国家自然科学基金资助项目(50775219);军队科研资助项目:[2011]107

摘　　要：针对强噪声环境中故障声发射信号提取的难题,在最小熵解卷积MED(Minimum Entropy Deconvolution)和最大峭度解卷积MCKD(Maximum correlated kurtosis deconvolution)的基础上,提出一种基于双向循环重构滤波准则的改进MCKD降噪方法。双向重构准则能够充分利用数据中的冲击成分,具有较强的抗冲击幅值变化干扰能力,改进MCKD方法通过滤波器迭代提取有用信号达到降噪目的。通过仿真信号和轴承故障声发射实验信号的研究表明:改进MCKD方法能有效提取原始信号中的有用故障信息,其降噪性能优于MED方法和MCKD方法。Aiming at the problem of extracting a useful acoustic emission signal of fault, an improved MCKD method was presented by two-way loop restructuring rule based on MED and MCKD method. The two-way loop restructuring rule fully used impact component of original data, and has strong anti-amplitude changing capacity. The improved MCKD method obtained de-noising signal by iterative updating filter coefficients. The result of simulation and testing data showed that the improved MCKD can effectively extract the useful fault, and the noise reduction performance was better than MED and MCKD method.

关 键 词：声发射 循环重构 最小熵解卷积 降噪 故障诊断 

分 类 号：TH133.33[机械工程—机械制造及自动化] TN911.72[电子电信—通信与信息系统]