A Bayesian Optimized Multi Harmonics Index Approach for Fault Diagnosis of Gearboxes
The project aims to design and develop an algorithm that can diagnose faults in planetary and fixed-axis gearboxes. Common faults in gearboxes are often masked by the Gear Meshing Frequency, making them difficult to detect via classical spectral analysis. A multi-harmonic index approach based on an adaptive combined envelope spectrum is selected as the foundational algorithm due to its robustness to noise in bearing analysis and its cyclostationary capabilities. Moreover, a Bayesian algorithm is proposed to select the ideal frequency band, improving the time complexity as compared to other optimization algorithms.
Voir la description complète du projetXihui (Larry) Liang
University of Technology Sydney
Engineering
Education
University of Manitoba
Globalink Research Award
