Open AccessEffective and accurate approaches for wind turbine gearbox condition monitoring
Author(s) -
Luo Huageng,
Hatch Charles,
Kalb Matthew,
Hanna Jesse,
Weiss Adam,
Sheng Shuangwen
Publication year - 2014
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.1595
Subject(s) - drivetrain , turbine , vibration , sampling (signal processing) , condition monitoring , rotor (electric) , computer science , acceleration , wind power , accelerometer , wind speed , automotive engineering , matlab , engineering , marine engineering , torque , mechanical engineering , acoustics , electrical engineering , physics , filter (signal processing) , classical mechanics , meteorology , computer vision , thermodynamics , operating system
This paper presents effective and accurate approaches in vibration‐based wind turbine drivetrain component condition monitoring. Detailed spectral analysis and acceleration enveloping techniques were used to effectively extract the gear and bearing damage features. Synchronous analysis was used to accurately detect specific damage features during constantly varying operational conditions. A typical wind turbine gearbox amplifies shaft speed two orders of magnitude from the rotor to the generator. To account for all necessary vibration signatures, synchronous sampling must be carried out for multiple revolutions and at a relatively high rate. The synchronous sampling used in this paper was carried out in the digital domain after both the keyphasor and the vibration signals were digitized at high sampling rate and high sampling resolution analog‐to‐digital conversion. Sometimes, the shaft speed is provided in a speed time history format, as in the case of the National Renewable Energy Laboratory (NREL) Round Robin project. To carry out synchronous sampling using the speed time history, a unique synthesized synchronous sampling technique was adopted. The approach presented in this paper was realized using MATLAB (MathWorks, Natick, MA) codes and then validated with a wind turbine field case. It was also applied to the NREL wind turbine drivetrain condition monitoring Round Robin project. The identified damage results using the techniques discussed were compared with post‐test inspection results with good correlation. Copyright © 2013 John Wiley & Sons, Ltd.