时频流形自适应稀疏重构的遥测振动信号特征增强方法

Telemetry vibration signal feature enhancement method based on timefrequency manifold adaptive sparse reconstruction

针对遥测振动信号非线性、非平稳性、瞬态冲击性等特点,提出一种基于时频流形自适应稀疏重构的遥测振动信号特征增强方法,对振动信号进行相空间重构提取其时频流形;以时频流形为基础,采用KSVD算法自适应构建过完备字典,并从中找到最匹配的时频原子,根据得到的原子与相空间展开信号的时频分布,依次匹配计算获得其重构的稀疏系数;利用稀疏系数和时频原子对相空间中各维信号的时频分布进行重构,通过时频分布的逆运算和相空间还原得到特征增强信号。仿真和实测信号处理结果验证了算法的有效性。

Aiming at the characteristics of nonlinearity,non-stationary and transient impact of telemetry vibration signal,a telemetry vibration signal feature enhancement method based on time-frequency manifold adaptive sparse reconstruction was proposed.The phase space reconstruction of the vibration signal was performed to extract its time-frequency manifold.Based on the time-frequency manifold,the KSVD algorithm was used to adaptively construct an over-complete dictionary and find the best matching time-frequency atoms.According to the selected atoms,the time-frequency distribution of each dimension signal in phase space was sequentially matched to calculate the reconstructed sparse coefficient.The time-frequency distribution of each dimension signal in phase space was reconstructed by using sparse coefficient and time-frequency atoms,and the feature enhancement signal was acquired by inverse operation of time-frequency distribution and phase space reduction.Simulation and measured signal processing results verified the effectiveness of the method.