We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.

Durham Research Online
You are in:

Reliability assessment of the hydraulic system of wind turbines based on load-sharing using survival signature.

Li, Y. and Coolen, F.P.A. and Zhu, C. and Tan, J. (2020) 'Reliability assessment of the hydraulic system of wind turbines based on load-sharing using survival signature.', Renewable energy., 153 . pp. 766-776.


The hydraulic system is one of the most critical subsystems of wind turbines. It is used to reset the aerodynamic brakes. Because of this, the reliability of the hydraulic system is important to the functioning of the entire wind turbine. To realistically assess the reliability of the hydraulic system, we propose in this article the load-sharing based reliability model using survival signature to conduct system reliability assessment. In addition, due to the uncertainty of the failure rates, it is difficult to conduct accurate reliability analysis. The Markov-based fuzzy dynamic fault tree analysis method is developed to solve this issue for reliability modeling considering dynamic failure characteristics. Following this, we explore the reliability importance and the reliability sensitivity of redundant components. The relative importance of the components with respect to the system reliability is evaluated and ranked. Then the reliability sensitivity with respect to the distribution parameters of redundant components is studied. The results of the reliability sensitivity analysis investigate the effects of the distribution parameters on the entire system's reliability. The effectiveness and feasibility of the proposed methodology are demonstrated by the successful application on the hydraulic system of wind turbines.

Item Type:Article
Full text:(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
Download PDF
Publisher Web site:
Publisher statement:© 2020 This manuscript version is made available under the CC-BY-NC-ND 4.0 license
Date accepted:05 February 2020
Date deposited:06 February 2020
Date of first online publication:10 February 2020
Date first made open access:10 February 2021

Save or Share this output

Look up in GoogleScholar