Abstract: A gear transmission system is a complex non-stationary and nonlinear
time-varying coupling system. When faults occur on gear system, it is difficult
to extract the fault feature. This paper researches the threshold principle in
the process of using the wavelet transform to de-noise the system, and combines
EMD (empirical mode decomposition) with wavelet threshold de-noising to solve
the problem. The wavelet threshold de-noising is acts on the high-frequency IMF
(Intrinsic Mode Function) component of the signal, and does overcome the defect
by simply highlighting the fault feature. On this basis, the pre-processed
signal is analyzed by the method of time-frequency analysis to extract the
feature of the signal. The result shows that the SNR (signal-noise ratio) of
the signal was largely improved, and the fault feature of the signal can
therefore be effectively extracted. Combined with time-frequency analyses in
the different running conditions (300 rpm, 900 rpm), various faults such as
tooth root crack, tooth wear and multi-fault can be identified effectively.
Based on this theory and combining the merits of MATLAB and
VC++, a multi-functional gear fault diagnosis software
system is successfully exploited.
