  Increasing the capabilities of sensors and computer algorithms produces a
need for structural support that would solve recurring problems. Autonomous
tribotronic systems self-regulate based on feedback acquired from interacting
surfaces in relative motion. This paper describes a software framework for
tribotronic systems. An example of such an application is a rolling element
bearing (REB) installation with a vibration sensor. The presented plug-in
framework offers functionalities for vibration data management, feature
extraction, fault detection, and remaining useful life (RUL) estimation. The
framework was tested using bearing vibration data acquired from NASA's
prognostics data repository, and the evaluation included a run-through from
feature extraction to fault detection to remaining useful life estimation. The
plug-in implementations are easy to update and new implementations are easily
deployable, even in run-time. The proposed software framework improves the
performance, efficiency, and reliability of a tribotronic system. In addition,
the framework facilitates the evaluation of the configuration complexity of the
plug-in implementation.
