Maintenance Management in Wind Turbines by Monitoring the Bearing Temperature

被引：2

作者：

Peco Chacon, Ana Maria ^{[1
]}

Zhang, Long ^{[2
]}

Garcia Marquez, Fausto Pedro ^{[1
]}

机构：

[1] Univ Castilla La Mancha, Ingenium Res Grp, Ciudad Real 13071, Spain

[2] Univ Manchester, Sch Elect & Elect Engn, Manchester, Lancs, England

来源：

PROCEEDINGS OF THE THIRTEENTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT, VOL 1 | 2020年 / 1001卷

关键词：

Renewable energy; Wind turbine; Curve power; SCADA; Fault detection; ICE DETECTION; SCADA; IDENTIFICATION; PREDICTION; DIAGNOSIS; SIGNALS; TIME;

D O I：

10.1007/978-3-030-21248-3_50

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Wind turbines are increasing in number, size and market share. It is determined whether they are efficient through operating and maintenance costs. Therefore, one of the main objectives of the wind turbines is to increase the service life of the components by applying different methodologies for fault detection. The gearbox is a critical component since it causes the most downtime and failure rate of the wind turbines. The Supervisory Control and Data Acquisition system offers the measurement of several variables, and by a correct analysis it is possible to detect the faults before they occur. This paper analyses the temperature curve of bearing versus wind speed as significant variables of a gearbox failure for fault detection.

引用

页码：678 / 687

页数：10

共 33 条

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