Order Tracking Using Variational Mode Decomposition to Detect Gear Faults under Speed Fluctuations



Published Sep 22, 2019
Madhurjya Dev Choudhury Liu Hong Jaspreet Singh Dhupia


Fault detection in gearboxes plays a significant role in ensuring their reliability. Vibration signals collected during gearbox operation contain a wealth of valuable condition information that can be exploited for fault detection. However, in an industrial environment machine operating speed always fluctuates around its nominal value, which causes smearing of the gearbox vibration spectrum. Considering operating speed fluctuation and multi-component nature of measured gearbox vibration signals, an order-tracking method combining the variational mode decomposition (VMD) and the fast dynamic time warping (FDTW) is proposed in this paper. Firstly, the multi-component vibration signal is decomposed into several intrinsic mode functions (IMFs) using VMD in order to extract a signal component with higher signal-to-noise ratio (SNR). Then, the sensitive fault information carrying IMF is exploited to estimate the instantaneous speed profile in order to construct the shaft rotational vibration signal. The measured vibration signal is then resampled based on the optimal warping path obtained by FDTW, which performs an “elastic” stretching and compression along the time axis of the extracted shaft vibration signal with respect to a sinusoidal reference signal of constant shaft rotational frequency. Finally, the gear fault is detected by constructing the order spectrum of the resampled vibration signal. The effectiveness of the proposed algorithm is demonstrated using simulation results.

How to Cite

Choudhury, M. D., Hong, L., & Dhupia, J. S. (2019). Order Tracking Using Variational Mode Decomposition to Detect Gear Faults under Speed Fluctuations. Annual Conference of the PHM Society, 11(1). https://doi.org/10.36001/phmconf.2019.v11i1.787
Abstract 232 | PDF Downloads 357



Gear fault, Variational Mode Decomposition, Fast Dynamic Time Warping, Fault Detection

Technical Papers