Dynamic modelling and fault analysis of wear evolution in rolling bearings: Dissertation

The rolling element bearing is one of the most critical components that determines the health of the machine and its remaining lifetime in modern production machinery. Robust condition monitoring tools are needed to guarantee the healthy state of rolling element bearings during the operation. The condition of the monitoring tools indicates the upcoming failures which provides more time for maintenance planning by monitoring the deterioration i.e. wear evolution rather than just detecting the defects. Several methods for diagnosis and prognosis that are commonly used in practise have challenge to track the wear fault over the whole lifetime of the bearing. The measurements in the field are influenced by several factors that might be ignored or de-limited in the experimental laboratory tests where those advanced diagnosis and prognosis methods are usually validated. Moreover, those advanced methods are verified with the help of simulation models that are based on specific definitions of fault and not on considering the fault development process during the lifetime of the component.Therefore, in this thesis a new dynamic model was developed to represent the evolution of the wear fault and to analyse the fault features of a rolling bearing under the entire wear evolution process. The results show the extracted defect features and how they change over the entire wear evolution process. The results show how the topographical and tribological changes due to the wear evolution process might influence the bearing dynamics over the entire lifetime of the bearing and the effectiveness of the fault detection process.