基于CEEMDAN-ICA的干气密封振动信号降噪方法

干气密封运行过程中的振动信号特征信息微弱并受外界强噪声干扰,其振动信号难以真实反映干气密封摩擦学特性。针对上述问题以及振动信号难以从噪声中分离的问题,提出一种基于CEEMDAN（自适应噪声的完全集合经验模态分析）与ICA（独立成分分析）相结合的信号降噪方法。首先对试验采集的干气密封运行时的加速度信号进行CEEMDAN分解得到IMF分量,然后通过ICA变换得到对应独立成分分量并计算其模糊熵值,将模糊熵值不符合条件的分量进行置零,并把符合条件的分量进行重构得到降噪后信号。利用干气密封加速度实验信号进行算法分析验证,证实了该方法相较于其他传统降噪方法更加有效,为干气密封故障诊断提供了一种新的途径。

Noise Reduction Method of Dry Gas Seal Vibration Signal Based on CEEMDAN-ICA

Due to the weak characteristic information of vibration signal and strong external noise interference,the vibration signal during the operation of dry gas seal is difficult to reflect the tribological characteristics of dry gas seal.Aimed at the above problems and the difficulty of separating vibration signal from noise,a signal denoising method based on the combination of CEEMDAN (complete ensemble empirical mode analysis with adaptive noise) and ICA (independent component analysis) was proposed.The acceleration signal of dry gas seal collected by experiments was first decomposed by CEEMDAN to get IMF component.The corresponding independent component was obtained by ICA transformation and its fuzzy entropy value was calculated.The component whose fuzzy entropy value did not meet the condition was set to zero,and the component which met the condition was reconstructed to get the denoising signal.The algorithm was analyzed and verified by using the dry gas seal acceleration test signal.It is proves that the method proposed is more effective than other traditional noise reduction methods,which provides a new way for fault diagnosis of dry gas seal in the future.