This research proposes a methodology to estimate
the reliability of gearbox using life data analysis and predict the
Lifetime Use Estimation (LUE). Life data analysis involves
collection of historical field replacements of gearbox and
perform statistical analysis such as Weibull analysis to estimate
the reliability. Remaining useful life is estimated by using
Cumulative damage model and data-driven methods. The first
approach is based on the physics of failure models of
degradation and the second approach is based on the
operational, environmental & loads data provided by the design
team which is translated into a mathematical model that
represent the behavior of the degradation. Data-driven method is
used in this research, where the different performance data from
components are exploited to model the degradation's behavior.
LUE is used to make key business decisions such as planning of
spares, service cost and increase availability of wind turbine.
Gearbox is the heart of the wind turbine and it is made up of
several stages of helical/planetary gears. Performance data is
acquired separately for each of these stages and LUE is
calculated individually. The individual LUE is then rolled up to
estimate the overall Lifetime Use Estimation of gearbox. This
will identify the weak link which is going to fail first and the
failure mode which is driving the primary failure can be
identified. Finally, corrective measures can be planned
accordingly. The cumulated damage and LUE are estimated by
using Inverse power law damage model along with Miner’s rule.
Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox
