Data Fusion Based on an Iterative Learning Algorithm for Fault Detection in Wind Turbine Pitch Control Systems

被引：1

作者：

Acho, Leonardo ^{[1
]}

Pujol-Vazquez, Gisela ^{[1
]}

机构：

[1] Univ Politecn Catalunya BarcelonaTech ESEIAAT, Dept Math, Terrassa 08222, Spain

来源：

SENSORS | 2021年 / 21卷 / 24期

关键词：

data fusion; iterative learning; fault detection; pitch system; wind turbines;

D O I：

10.3390/s21248437

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

In this article, we propose a recent iterative learning algorithm for sensor data fusion to detect pitch actuator failures in wind turbines. The development of this proposed approach is based on iterative learning control and Lyapunov's theories. Numerical experiments were carried out to support our main contribution. These experiments consist of using a well-known wind turbine hydraulic pitch actuator model with some common faults, such as high oil content in the air, hydraulic leaks, and pump wear.

引用

页数：12

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