摘要
常用的信号处理方法分析了信号按照频谱分布关系的组成结构,而未揭示各个信号组成成分与发生源之间相对应的因果联系。降噪源分离(Denoising source separation,DSS)技术在仅知观测信号的条件下,按照统计特征将复杂信号分解为若干分量,而这些分量反映了观测信号的发生源,为设备状态监测与振动噪声主动控制提供了直接依据。研究DSS基本理论以及基于不同准则的降噪函数,并通过典型机械信号的仿真试验定量比较基于能量函数、斜度函数、峭度函数以及正切函数四类降噪函数的分离性能。分析结果表明,基于正切降噪函数的源分离方法从非线性耦合信号中提取的分量与源信号时域相关系数高于0.89,因而更适合于提取机械设备非线性耦合信息。将基于正切降噪函数的源分离方法应用于某型号军舰的机械设备运行信息特征提取中,定量分析结果表明,该方法很好地从舱壁混合振动信号中提取出了各台设备的运行特征信息。
Signal processing methods are commonly used to analyze the structure of signals according to the criteria of spectral distribution.However,the causal relationship between components and sources are not revealed.Under the condition that only observed signals are known,the mixed signals can be separated into several components by denoising source separation（DSS） method according to statistical feature.The sources of observed signals are revealed by these independent components,thus it provides a direct reference to condition monitoring and active control of vibration and noise.The basic theory of DSS and denoising functions based on different criterion are studied,and the separation performance of four types of denoising function such as energy function,slope function,kurtosis function and tangent function are quantitatively compared by means of simulation of typical mechanical signals.The results show that the correlation coefficients between independent components,which are separated from nonlinear mixed signals by DSS based on tangent function,and related sources are more than 0.89.Thus the algorithm based on tangent function is more suitable for extracting nonlinear coupling information of mechanical equipment.The DSS method based on tangent function is used to extract running information feature of a warship,and the quantitative analysis results show that the running information of each equipment is well extracted from mixed vibration signals of the bulkhead.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2010年第13期128-134,共7页
Journal of Mechanical Engineering
基金
国家自然科学基金(50875197)
教育部留学回国人员科研启动基金资助项目
关键词
降噪源分离
降噪函数
非线性耦合
特征提取
状态监测
振动噪声
主动控制
Denoising source separation Denoising function Nonlinear coupling Feature extraction Condition monitoring Vibration and noise Active control
