Early Fault Detection via Multiple Feature Fusion and Ensemble Learning

Early fault detection (EFD) of rotating machines is important to decrease the maintenance cost and improve the mechanical system stability. One of the key points of EFD is developing a generic and robust model for different equipment. Most existing EFD methods focus on learning fault representation by one type of feature. However, a combination of multiple features can capture a more comprehensive representation. In this article, we propose an …