Application of Hilbert-Huang transform to the fault diagnosis of a gear system

In this research, Hilbert-Huang transform (HHT) is investigated for gear fault detection. As the HHT exists some deficiency, new techniques have been applied to improve it. In the process of empirical mode decomposition (EMD), a new Intrinsic Mode Functions (IMFs) selection criterion is put forward with the help from correlation between the original signal and the IMF components. Then, applying Hilbert transform to the envelope signal, we can get the local Hilbert marginal spectrum from which the faults in a gear system can be diagnosed. Similar analyses with Fourier transform are presented for comparison. The results indicate the superiority of HHT for fault diagnosis.