Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …

If the incipient fault (IF) point is not corrected, it may imply a poor prognostic framework, a
false value of remaining useful life (RUL), and unexpected catastrophic failure. The use of …

Power-machinery systems are widely used in various industries, including manufacturing,
energy production, transportation, and infrastructure. However, unexpected failures of these …

Data imbalance and large data probability distribution discrepancies are major factors that
reduce the accuracy of remaining useful life (RUL) prediction of high-reliability rotating …

Transfer learning has been extensively used to build bearings remaining useful life
prediction models under multi-operating conditions. However, most models only consider …

Accurate cost prediction of healthcare resources is challenging as diverse factors affect the
overall prediction. The cost of healthcare providers is increasing exponentially as different …

As high-alloy steel, 8Cr4Mo4V steel has been widely used in the field of high-speed
aerospace bearings in recent years because of its excellent thermal strength, thermal …

Remaining useful life (RUL) prediction is recently a hot spot in industrial big data analysis
research. It aims at obtaining the health status of the equipment in advance and making …

The prediction of rolling bearing lifespan is of significant importance in industrial production.
However, the scarcity of high-quality, full lifecycle data has been a major constraint in …

针对不同工况下多组件设备退化数据分布存在差异导致设备的寿命预测模型精度下降的问题,
本文提出一种能适应于不同工况的域特征融合网络(DFF-Net). 首先, 把不同工况的退化数据输入 …