BBTác giả: Luo, B.; Người hướng dẫn: -; Người tham gia: Wang, H.; Liu, H.; Li, B.; Peng, F. (2019)
In modern digital manufacturing, nearly 79.6% of the downtime of a machine tool is caused by its mechanical
failures. Predictive maintenance (PdM) is a useful way to minimize the machine downtime and the associated costs. One of the challenges with PdM is early fault detection under time-varying operational conditions, which means mining sensitive fault features from condition signals in long-term running. However, fault features are often weakened and disturbed by the time-varying harmonics and noise during a machining process. Existing analysis methods of these complex and diverse data are inefficient and time-consuming. This paper proposes a novel method for early fault detection u... 
