Abstract
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.
Original language | English |
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Qualification | Doctor Degree |
Awarding Institution |
|
Supervisors/Advisors |
|
Award date | 26 May 2016 |
Place of Publication | Espoo |
Publisher | |
Print ISBNs | 978-951-38-8416-1 |
Electronic ISBNs | 978-951-38-8417-8 |
Publication status | Published - 2016 |
MoE publication type | G5 Doctoral dissertation (article) |
Keywords
- dynamic modelling
- Wear evolution
- condition monitoring
- fault development
- fault analysis
- rolling bearings