semantic_scholarJournal of Applied Fluid Mechanics
Prediction of Bearing Wear in High-speed Aviation Fuel Pump Using a VMD-CNN-LSTM Model
X. Wang, W. Liu, P. Ma, L. Chai, G. Guo
TL;DR: The integration of noise-resistant decomposition of VMD with the ability of CNN to learn spatial features and dynamic sequence modeling of LSTM significantly enhances the precision and dependability of sliding-bearing wear forecasts.
The high-speed aviation fuel pump is a crucial component of the aircraft fuel system, and the condition of its sliding bearings has a direct impact on the reliability of aero-engines and the overall flight safety. This study presents a novel predictive framework designed to accur…