Software Framework for Tribotronic Systems
This is an incremental framework for improving performance, efficiency, and reliability in tribotronic systems like rolling element bearings.
The paper presents a software framework for tribotronic systems that self-regulate based on feedback from interacting surfaces, tested on bearing vibration data from NASA's repository to handle data management, feature extraction, fault detection, and remaining useful life estimation.
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.