Bearing prognostics is an important aspect in condition-based maintenance (CBM), and a key step to successful prognostic methods is the ability to quantify the fault severity of the bearing. Previous studies have resulted in some severity assessment methods based on certain types of signals, such as vibration, acoustic emission (AE) and instantaneous angular speed (IAS), however, their performances were not compared, especially in terms of their ability to track the severity of naturally growing spalls. In this paper, four measurement approaches were tested on the same rig for bearing run-to-failure experiments, and their signals were analysed individually and compared. It was found that IAS and radial load (a proxy for displacement) required less processing to provide a reliable assessment of bearing fault severity, acceleration required sophisticated techniques to extract spall-size estimates, whereas AE could not track fault evolution accurately.

轴承预测是状态维护 (CBM) 的一个重要方面，成功预测方法的关键步骤是能够量化轴承的故障严重程度。以前的研究已经产生了一些基于某些类型信号的严重性评估方法，例如振动、声发射 (AE) 和瞬时角速度 (IAS)，但是，它们的性能没有进行比较，特别是在它们跟踪信号的能力方面。自然生长的剥落的严重程度。在本文中，四种测量方法在相同的台架上进行了轴承运行到故障实验，并对它们的信号进行了单独分析和比较。发现 IAS 和径向载荷（位移的代表）需要较少的处理来提供轴承故障严重性的可靠评估，