基于瞬态声测法和核独立分量分析的齿轮箱轴承故障诊断

Fault Diagnosis of Gearbox Bearings Based on Transient Acoustic Method and KICA

针对轴承故障信号在传输过程中发生非线性畸变、混叠等特点,将核独立分量分析(KICA)技术引入到了轴承故障诊断中,并结合EMD这种先进的自适应的信号分解方法,提出了基于KICA算法的阶次EMD方法,将其应用于轴承故障诊断中,对齿轮箱的瞬态声信号进行分析处理,试验结果和对比研究表明,该算法可有效地增强信号的信噪比,使故障特征更加明显,提高了故障诊断的准确度。

According to the nonlinear distortion and mixed feature of bearing fault signals in the transmission process, the order EMD method based on KICA algorithm is proposed by introducing KICA and combining EMD into the bearing fault diagnosis, and the transient acoustic signal of gearbox is analyzed. The experiment results and comparative research show that this arithmetic is able to enhance the signal SNR effectively, making the fault characteristic more distinct and greatly improving the accuracy of fault diagnosis.