Browse by author
Lookup NU author(s): Dr Wenxian YangORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
Condition monitoring (CM) has been recognized as one of the most promising and widely applicable approaches to increase the availability and reduce the operation and maintenance (O&M) costs of wind turbines (WTs). However, up to date the potential of CM in the wind industry has not been fully exploited due to manifold reasons including (1) the lack of cost-effective and universal strategies that can deal with the CM issues from various concepts of WTs and (2) the lack of efficient and robust algorithms that can accurately process and interpret CM signals collected from WTs. In addition, WTs are subject to constantly varying loads due to unstable wind. In order to mitigate the complex loads and maximize the output power, modern megawatt-scale WTs are variable-speed and pitch control machines. Consequently, the CM signals collected from WTs are non-stationary over time and difficult to process accurately using conventional signal processing methods. Thus, there is an urgent need of advanced CM strategies and dedicated signal processing techniques for WTs. Here a novel WT drivetrain CM strategy and the associated signal processing method, namely, wavelet-transform-based energy tracking technique (WETT), are elaborated in this chapter. The WETT utilizes readily available generator power signal to evaluate the health condition of the whole WT drivetrain system through extracting and assessing the energy of WT power signals at fault characteristic frequencies. The WETT is verified through applying it to detecting the electrical and mechanical faults emulated on a WT drivetrain test rig. Experiment has shown that the WETT can correctly identify the simulated faults and is therefore a successful tool for WT drivetrain CM.
Author(s): Yang W, Wei K, Peng Z, Hu W
Editor(s): Hu W
Publication type: Book Chapter
Publication status: Published
Book Title: Advanced Wind Turbine Technology
Print publication date: 01/06/2018
Online publication date: 08/05/2018
Acceptance date: 28/03/2018
Publisher: Springer International Publishing
Place Published: Cham
Library holdings: Search Newcastle University Library for this item