TY - GEN
T1 - Speed Estimation in Geared Wind Turbines Using the Maximum Correlation Coefficient
AU - Skrimpas, Georgios Alexandros
AU - Marhadi, Kun S.
AU - Jensen, Bogi Bech
AU - Sweeney, Christian Walsted
AU - Mijatovic, Nenad
AU - Holbøll, Joachim
PY - 2015
Y1 - 2015
N2 - Valid speed signal is essential for proper condition monitoring
of modern variable speed wind turbines. Traditionally,
a tachometer mounted on the high speed shaft provides reference
for tracking speed dependant frequency components,
such as generator speed harmonics and gearbox tooth mesh
frequencies. The health assessment of drive train components
is limited to broadband measurements when the speed signal
is invalid. This condition results in reduced fault detection capabilities
and consequently decreased lead time. In this work,
a new speed estimation algorithm is presented in order to
overcome the above mentioned issues. The high speed stage
shaft angular velocity is calculated based on the maximum
correlation coefficient between the 1
st gear mesh frequency
of the last gearbox stage and a pure sinus tone of known frequency
and phase. The proposed algorithm utilizes vibration
signals from two accelerometers for cross-referencing purposes.
The method is tested in three drive train configurations,
where 720 sets of vibration signals of 10.24s length,
sampled at 25.6kHz are analysed. Consistent speed estimation
reaches approximately 98% when two vibration sources
are utilized, whereas it is lower when only one source is taken
into account. No apparent patterns arise between speed variation
levels or power production and the number of invalid
outputs, showing the independence of the method from operational
parameters.
AB - Valid speed signal is essential for proper condition monitoring
of modern variable speed wind turbines. Traditionally,
a tachometer mounted on the high speed shaft provides reference
for tracking speed dependant frequency components,
such as generator speed harmonics and gearbox tooth mesh
frequencies. The health assessment of drive train components
is limited to broadband measurements when the speed signal
is invalid. This condition results in reduced fault detection capabilities
and consequently decreased lead time. In this work,
a new speed estimation algorithm is presented in order to
overcome the above mentioned issues. The high speed stage
shaft angular velocity is calculated based on the maximum
correlation coefficient between the 1
st gear mesh frequency
of the last gearbox stage and a pure sinus tone of known frequency
and phase. The proposed algorithm utilizes vibration
signals from two accelerometers for cross-referencing purposes.
The method is tested in three drive train configurations,
where 720 sets of vibration signals of 10.24s length,
sampled at 25.6kHz are analysed. Consistent speed estimation
reaches approximately 98% when two vibration sources
are utilized, whereas it is lower when only one source is taken
into account. No apparent patterns arise between speed variation
levels or power production and the number of invalid
outputs, showing the independence of the method from operational
parameters.
M3 - Article in proceedings
T3 - Annual Conference of the PHM Society
BT - Proceedings of the Annual conference of the prognostics and health management society 2015
T2 - Annual conference of the prognostics and health management society 2015
Y2 - 19 October 2015 through 24 October 2015
ER -