Data-driven design of robust fault detection system for wind turbines
Data-driven design of robust fault detection system for wind turbines
复制标题
风力发电机鲁棒故障检测系统的数据驱动设计
DOI：
10.1016/j.mechatronics.2013.11.009
复制
发表时间：
2014-06-01
期刊：
影响因子：
3.3
通讯作者：
Karimi, Hamid Reza
中科院分区：
文献类型：
--
作者：
Yin, Shen;Wang, Guang;Karimi, Hamid Reza
本文提出了一种基于数据驱动的故障检测方法，并将其应用于风力涡轮机基准测试。风力涡轮机故障检测的主要挑战在于其非线性、未知干扰以及显著的测量噪声。为了克服这些困难，数据驱动的故障检测方案，提出了直接从现有的过程数据构建强大的残差生成器。提出了一个性能指标和优化准则，以实现与干扰有关的残差信号的鲁棒性。对于残差的估计，给出了一种合适的估计方法以及一种合适的决策逻辑，以做出正确的最终决策。最后通过对风力机涡轮机基准模型的仿真验证了该方法的有效性。(C)2013爱思唯尔有限公司保留所有权利。
In this paper, a robust data-driven fault detection approach is proposed with application to a wind turbine benchmark. The main challenges of the wind turbine fault detection lie in its nonlinearity, unknown disturbances as well as significant measurement noise. To overcome these difficulties, a data-driven fault detection scheme is proposed with robust residual generators directly constructed from available process data. A performance index and an optimization criterion are proposed to achieve the robustness of the residual signals related to the disturbances. For the residual evaluation, a proper evaluation approach as well as a suitable decision logic is given to make a correct final decision. The effectiveness of the proposed approach is finally illustrated by simulations on the wind turbine benchmark model. (C) 2013 Elsevier Ltd. All rights reserved.