局部波动特征分解(LOD)方法是一种新的自适应时频分析方法。该方法通过采用微分、坐标域变换、分段线性变换三种运算,可以高效地将信号自适应分解为一系列的单一波动分量(MOC),非常适合于处理多分量信号。然而,由于分段线性变换的使用,虽可以显著提高算法的计算效率,但会使MOC分量缺乏光滑性,从而导致失真。对此,将样条曲线形状可调可控的有理样条函数引入LOD方法替代分段线性变换,提出了基于有理样条函数的局部波动特征分解(RS-LOD)方法。在详细阐述RS-LOD分解原理的基础上,通过仿真信号将RS-LOD、LOD和经验模态分解(EMD)进行了对比分析,结果表明RS-LOD方法可以明显改善原LOD方法中MOC分量光滑度差的问题。此外,针对旋转机械故障振动信号的多分量调制特点,将RS-LOD方法应用于旋转机械的故障特征提取,对滚动轴承和齿轮箱故障振动信号的分析结果表明,RS-LOD方法可以有效地提取旋转机械振动信号的故障特征。
Abstract
The local oscillatory-characteristic decomposition (LOD) method is a new adaptive time-frequency analysis method.By adopting three operations of differentiation, coordination domain transform and piecewise linear transformation, the method can efficiently decompose a signal into a series of Mono-oscillation component (MOC), which is very suitable for processing multi-component signals.Although the computational efficiency of the algorithm can be significantly improved by the use of piecewise linear transformation, the MOC component lacks smoothness resulting in distortion.For this problem, the rational spline function that spline shape can be adjusted and control is introduced into the LOD method instead of piecewise linear transformation, and the rational spline-local oscillatory-characteristic decomposition (RS-LOD) method was proposed.Based on the detailed description of the principle of RS-LOD decomposition, the RS-LOD, LOD and the empirical mode decomposition (EMD) were compared and analyzed by simulation signals.The results show that the RS-LOD method can significantly improve the problem of poor smoothness of the MOC component in the original LOD method.In addition, the RS-LOD method was applied to the fault feature extraction of rotating machinery for the multi-component modulation characteristics of rotating machinery fault vibration signals.The analysis results of rolling bearing and gearbox fault vibration signals show that the RS-LOD method can effectively extract the fault feature of rotation mechanical vibration signals.
关键词
局部波动特征分解(LOD) /
有理样条函数 /
旋转机械 /
振动信号 /
故障特征提取
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Key words
local oscillatory-characteristic decomposition(LOD) /
rational spline function /
rotating machinery /
vibration signal /
fault feature extraction
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脚注
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