A Comparative Analysis Between EMD- and VMD-Based Tacho-Less Order Tracking Techniques for Fault Detection in Gears

Abstract

Vibration signals collected from gearboxes in an industrial environment are characterized by inherent machine speed fluctuation and complex multicomponents, which make it difficult to extract reliable fault information. The presence of speed fluctuation smears the vibration spectrum of the gearbox. Under such conditions, order tracking (OT) technique is adopted, which performs signal resampling using additional speed information of the operating shaft. Thus, OT is dependent on the availability of shaft speed information, which is generally measured using a tachometer. This study proposes a tacho-less method to accurately estimate the shaft speed information in the presence of speed fluctuations by the use of adaptive mode decomposition (AMD) methods, like empirical mode decomposition (EMD) and variational mode decomposition (VMD). The extracted shaft speed information is then used to perform OT for gear fault detection in the presence of speed fluctuation. A comparison has also been conducted to evaluate the effectiveness of extracting shaft speed information by using both VMD and EMD. The analysis results show that speed information can be better extracted using VMD as compared to EMD. The effectiveness of the proposed algorithm is demonstrated using a MATLAB-based simulation analysis.