Iterative HOEO Fusion Strategy: A Promising Tool for Enhancing Bearing Fault Feature

Rolling element bearings are widely used in rotating machinery, and their failure is a major cause of mechanical breakdowns and accidents. Therefore, the diagnosis of early faults in rolling element bearings is crucial for ensuring the safe and normal operation of rotating machinery. However, in practical engineering, due to the interference of strong background noise and suboptimal working conditions, the fault-related transients in the collected vibration signals are often contaminated by noise, making fault diagnosis challenging. Although energy operators and their variants, such as higher order energy operators, have been applied in bearing fault feature detection for their parameter independence and simplicity, their performance is limited by the small number of available energy operators. Moreover, they fail to reflect the nonlinearity of mechanical dynamic systems, which affects noise reduction, leading to the fault-related transients they enhance still being affected by strong