Abstract
Wind turbine blade bearings are pivotal components to pitch blades, which optimize electrical energy output and stop wind turbines for protection. Blade bearing failure can cause the turbine to lose control or even break down. However, due to the very slow rotation speeds (often less than 5 r/min) and limited rotation angles (less than 100 $\rm ^{o}$ ), blade bearings can only produce weak and limited operating condition data, which makes condition monitoring and fault diagnosis very challenging, in particular for naturally damaged conditions. In this article, a naturally damaged large-scale blade bearing, which was in operation on a real wind farm for over 15 years, is investigated. An iterative nonlinear filter is proposed to remove heavy noise and extract weak fault vibration features. Then, the morphological transform-based envelope method is applied to diagnose the bearing fault in the frequency domain. The diagnostic results show that the proposed method can be an effective tool for diagnosing very slow speed blade bearings and is superior to some conventional bearing fault diagnosis methods.
Highlights
W IND energy is acknowledged as a sustainable and reliable energy source, which has drawn extensive attention all over the world [1]
We aim to evaluate the effectiveness of the iterative nonlinear filter (INF) and morphological analysis on a widely used small-scale bearing with a seeded inner race fault from the SpectraQuest Machinery Fault Simulator test rig [28]
The test wind turbine blade bearing was manufactured by Rollix, and was operational on a wind farm for over 15 years
Summary
W IND energy is acknowledged as a sustainable and reliable energy source, which has drawn extensive attention all over the world [1]. The single wind turbine capacity has been increased to over 10 MW. In order to optimize energy yield, modern wind turbine blades can be controlled at desired angles, while keeping the main shaft speeds within operating limits via the pitch systems. The blade bearing, termed pitch bearing, is one of the critical components in the wind turbine. Manuscript received May 13, 2019; revised August 15, 2019 and September 20, 2019; accepted October 13, 2019. Date of publication October 30, 2019; date of current version June 3, 2020.
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