ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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S&M2146 Research Paper of Special Issue

Design and Development of Condition Monitoring System for Wind Turbines Based on Generator Output Voltages

Rong-Mao Lee, Shih-Hsuan Hu, Cheng-Chi Wang, Tsung-Chia Chen, and Jui-Hung Liu

(Received February 3, 2019; Accepted December 23, 2019)

Keywords: wind turbine, condition monitoring, rotor imbalance, signal processing

As wind energy assumes greater importance in remote and offshore locations, an effective and reliable condition monitoring system (CMS) has become necessary for wind turbines (WTs). Conventional CMSs used in the power generation industry have been applied to WTs commercially. However, the operating environment of a WT is much different from that of a power plant. Moreover, current CMSs require the deployment of various sensors and computationally intensive analysis techniques. An empirical and low-cost CMS against shaft imbalance faults and generator circuit faults is proposed in this work. The diagnostic process of CMS is merely based on generator outputs. Since the air gap between the rotor and the stator of a generator is limited by rigid bearings, diagnosis rules for shaft imbalance faults are formulated on the basis of experimental results with the aid of a specially designed WT simulation platform. Once a test at a specified speed has been performed, the error limits of the diagnosis for generator outputs can be determined. The proposed fault recognition procedure is practical and easy to conduct. The efficacy of the proposed CMS against four types of fault, namely, low-speed shaft imbalance, high-speed shaft imbalance, and short circuit and open circuit of a generator, has been validated practically on the WT simulation platform.

Corresponding author: Rong-Mao Lee




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