Rotating machinery reliability assessment based on improved extreme learning machine and hippopotamus optimization algorithm

incessant operational cycle of machinery exerts significant strain on these parts, culminating in progressive degradation.Therefore, it is imperative to routinely monitor and assess their performance.The early identification of wear or potential faults can avert catastrophic failures, thereby ensuring efficient operation and extending the lifespan of the equipment.Appropriate maintenance strategies should be employed to mitigate these risks and preserve the integrity of these essential components.State-of-the-art approach, including the IELM in conjunction with the HOA, offer innovative strategies to enhance