基于信号特征的复合字典多原子匹配算法研究

在经典匹配追踪算法的基础上,提出基于信号特征的复合字典多原子匹配的改进算法,并应用于轴承故障诊断领域。针对滚动轴承损伤性故障振动信号特点,构造高频段冲击时频特征原子库与低频段Fourier特征原子库相结合的复合字典。研究复合字典多原子匹配的稀疏分解及重构算法以用于提取故障特征,并在重构算法中引入阈值降噪原理。滚动轴承故障试验信号和工程信号分析结果证明,在冲击性故障特征提取效果上,基于信号特征的复合字典多原子匹配优于单原子匹配,并且硬阈值降噪处理效果优于无阈值处理效果。

Research on the Composite Dictionary Multi-atoms Matching Algorithm Based on the Signal Character

Based on the classical matching pursuit algorithm,the composite dictionary multi-atoms matching algorithm based on structural characteristics of signal is proposed,and applied to bearing fault diagnosis field.For the structural characteristics of the roller bearing fault signals,a composite dictionary combining the impulse time-frequency dictionary and the Fourier dictionary is constituted.Sparse decomposition and reconstruction algorithm of composite dictionary multi-atoms matching pursuit is researched and used to extracting fault features,and the threshold de-noising is introduced in the reconstruction algorithm.The analysis results of roller bearing fault experiment signals and engineering signals indicate that the impact failure characteristic extraction effect of composite dictionary multi-atoms matching algorithm based on structural characteristics is superior to single-atom matching algorithm,and hard threshold is superior to that without threshold.