Factory-Based Vibration Data for Bearing-Fault Detection

The importance of preventing failures in bearings has led to a large amount research being conducted find methods for fault diagnostics and prognostics. Many these solutions, such as deep learning methods, require significant data perform well. This is reason why publicly available are important, there currently exist several open datasets that contain different conditions faults. However, one challenge almost all come from laboratory setting, where might differ those found an industrial environment the intended be used. also means may characteristics important take into account. Therefore, this study describes completely new dataset bearing faults pulp mill. analysis shows vary significantly terms development, rotation speed, amplitude vibration signal. It suggests built need consider no historical examples target domain external events can occur not related any condition bearing.