基于LMD和灰色关联度的故障诊断方法研究

针对高压隔膜泵单向阀故障振动信号的非平稳特性,提出基于局部均值分解法(LMD)和灰色关联度理论相结合的故障诊断方法。首先,利用LMD将高压隔膜泵单向阀不同运行状态下的振动信号分解成多个乘积函数。然后,计算所有乘积函数的互相关系数,并从中选择互相关程度高的乘积函数来提取相应的特征向量。最后,引入灰色关联度理论,构建单向阀故障诊断识别模型,并与基于经验模态分解法(EMD)以及基于混合特征建模、单一特征建模得到的结果进行了对比分析。实验表明,所提出的方法可以较好地分解单向阀故障信号,并有效地识别了小样本条件下的单向阀故障信号。

Research on fault diagnosis method based on LMD and grey correlation degree

Aiming at the nonstationary characteristics of the fault vibration signal of high pressure diaphragm pump check valve,a fault diagnosis method based on local meandecomposition(LMD)and grey correlation theory is proposed.Firstly,LMD is used to decompose the vibration signals of the check valve of high pressure diaphragm pump under different operating conditions into multiple product functions.Then the cross-correlation coefficients of all product functions are calculated,and the product functions with high cross-correlation degree are selected to extract the corresponding feature vectors.Finally,the grey correlation theory is introduced to construct the fault diagnosis and identification model of one-way valve,and the results are compared with those obtained by empirical mode decomposition(EMD),mixed feature modeling and single feature modeling.The experimental results show that the proposed method can decompose the fault signal of one-way valve well,and effectively identify the fault signal of one-way valve under the condition of small samples.