Real Time Tribology Failure Detection System

Successful operation of many precision machinery used in tracking systems satellites, telescopes and other space instruments require very stringent position accuracy - in the range of microns. Theses enormously expensive systems must be designed to operate reliably with little or no maintenance and long service-life duration. This presents a formidable challenge to the designer since there is a severe paucity of available information on enabling methods that would ensure proper functioning of these systems. We aim at using signal processing methods to determine features of the bearing conditions with its protective coatings from its fresh installation to the end of its life. The proposed work will provide appropriate correlation between friction, coating thickness, material properties, and performance. In particular, we perform laboratory experiments using a universal microtribometer equipped with a computerized data acquisition system. Friction force and acoustic emission signals will be measured with respect to the bearing condition. A set of feature cluster trends will be used to analyze the signals in real time and to discriminate the bearing conditions, and predict bearing life. The failure detection is made possible through statistical hypothesis tests between the normal and actual feature cluster trends estimated in real-time.