摘要
提出了一种基于奇异值差分谱单边极大值的降噪方法,实现了对旋转设备故障信号信噪比的提高。首先通过相空间重构Hankel矩阵的方法对原始振动信号进行处理,再进行奇异值分解,最后采用奇异值差分谱单边极大值原则确定所含的较大峰值降噪阶数。通过数值仿真和实际轴承故障数据的应用分析,表明了该方法可以有效地提高信号的信噪比,为后期的故障特征信号提取创造有利条件。
A new effective method for denoising based on difference spectrum unilateral maxima of singular values was presented to improve the signal-to-noise ratio of a rotating equipment fault signal.Firstly,the phase space reconstruction of Hankel matrix was used to process the original vibration signal,and then the trajectory attractor matrix was decomposed by using Singular Value Decomposition.Finally,according to the difference spectrum unilateral maxima principle of singular values to determine the reconstruction order rank of singular values.Numerical simulation and the practical bearing fault data analysis were done.The results showed that the proposed method can be used to effectively improve the signal-to-noise ratio of a signal,and it is helpful for later fault characteristic signal extraction.
出处
《振动与冲击》
EI
CSCD
北大核心
2014年第12期176-180,共5页
Journal of Vibration and Shock
基金
国家自然科学基金项目资助(51176028)
关键词
降噪
奇异值分解
HANKEL矩阵
单边极大值原则
noise reduction
singular value decomposition （SVD）
Hankel matrix
unilateral maxima principle
