SUMMARY
Unscheduled maintenance in a production line due to breakdowns is highly detrimental. The ability to predict impending failure andanticipate it is a high value proposition. Such a prediction can be achieved by monitoring components that are known to fail often inmechanical systems, such as bearings. Prior research has led to the development of bearing monitoring approaches widely used today.However, one of the main challenges is the fact that there is often incomplete information about the systems. This thesis will focus onapproaches that can be employed to detect bearing defects and incipient bearing failure in the presence of incomplete and inaccuratesystem knowledge.