基于稀疏分解的轴承双冲击特征提取

Extraction of Twin Impulses Based on Sparse Decomposition

旋转机械的轴承部件出现裂纹或凹坑时,会产生稀疏的双冲击信号,在故障早期时,双冲击信号会发生混叠现象。在稀疏分解过程中,传统的高斯最大原则无法准确提取故障信号原子。笔者通过分析冲击类故障双冲击信号的特点,研究双冲击混叠时时频因子与双冲击间隔之间的关系,构造冲击信号最优邻域,并提出一种邻域正交匹配追踪算法。在每次迭代中选取内积最大原子周围的部分原子组成子框架,计算振动信号在当前框架下的表示,再进一步计算残差信号,并进行下次迭代,直至满足迭代终止条件。通过仿真试验和故障实例分析发现,该方法能避免过匹配现象,并准确提取双冲击成分,从而计算出双冲击信号的时间间隔,对故障程度进行判定。

When a bearing appears cracked or pitted,twin impulse signals can be generated that overlap at initial faults.It was difficult to extract the atoms that best match the twin impulses based on the common maximum gaussianity criterion through traditional sparse decomposition.First,the relationship between time-frequency factors and the distance of twin impulses was discussed,according to which the optimal neighborhood could be constructed and a new method of the neighbor orthogonal matching pursuit could be introduced.In each iteration of this method,a sub-frame was constructed,consisting of the atoms neighboring the atom that had the maximum inner product with the residual signal.Next,the representation in this sub-frame was obtained,and the next residual signal was computed.The next iteration was made until the termination condition was met.The simulation and fault proved the effectiveness of this method in extracting the twin impulses and identifying the type of fault.