基于EMD和CICA的单通道盲源分离方法用于齿轮箱混合故障诊断研究

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振动与冲击 ›› 2019, Vol. 38 ›› Issue (8) : 225-231.

论文

郝如江，安雪君，史云林

作者信息 +

Single-channel blind source separation based on EMD and CICA and its application to gearbox multi-fault diagnosis

HAO Rujiang， AN Xuejun， SHI Yunlin

Author information +

文章历史 +

摘要

针对传统的独立分量分析难以解决齿轮箱混合故障诊断中存在的欠定盲分离问题，提出了基于EMD和CICA（约束独立分量分析）的单通道盲源分离方法。通过单通道加速度传感器采集齿轮箱混合故障信号，对其进行EMD分解以实现降噪及单通道扩展，采用基于白噪声统计特性和峭度值结合的方法选取有效的IMF分量，将其作为盲源分离的输入信号，然后通过CICA方法提取目标振动信号，识别故障特征。通过对齿轮箱轴承与齿轮混合故障的仿真及实验研究，验证了该方法的有效性和可行性。

Abstract

Considering that the traditional independent component analysis is too difficult to solve the problems of underdetermined blind source separation (BSS) in gearbox multi-fault diagnosis, a single-channel blind source separation method based on empirical mode decomposition (EMD) and constrained independent component analysis (CICA) was proposed.Gearbox multi-fault signal was collected by a single-channel acceleration sensor, and it was decomposed by the EMD method to achieve noise reduction and single channel expansion.By virtue of the characteristics of white noise and kurtosis value, the effective IMF components were selected, which was treated as input signals for the BBS.The target vibration signal was extracted by the CICA method to identify the fault feature.A case study on gearbox bearing and gear multi-fault simulations and experiments verifies the effectiveness and feasibility of the proposed method.

导出引用

郝如江，安雪君，史云林. 基于EMD和CICA的单通道盲源分离方法用于齿轮箱混合故障诊断研究[J]. 振动与冲击, 2019, 38(8): 225-231

HAO Rujiang， AN Xuejun， SHI Yunlin. Single-channel blind source separation based on EMD and CICA and its application to gearbox multi-fault diagnosis[J]. Journal of Vibration and Shock, 2019, 38(8): 225-231

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