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Lookup NU author(s): Dr Wenxian YangORCiD,
Dr Wenye Tian
This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2015.
For re-use rights please refer to the publisher's terms and conditions.
Incipient defects occurring in long wind turbine (WT) blades are difficult to detect using the existing condition monitoring (CM) techniques. To tackle this issue, a new WT blade CM method is studied in this paper with the aid of the concept of the transmissibility of Frequency Response Functions (FRFs). Different from the existing CM techniques that judge the health condition of a blade by interpreting individual CM signals, the proposed method jointly utilizes the CM signals measured by a number of neighboring sensors. This offers the proposed technique a unique capability of both damage detection and location. The proposed technique has been experimentally verified by using the real CM data collected during the fatigue and static tests of a full scale WT blade. Experiment has shown that the new technique is effective not only in damage detection but in damage location when either Fiber Bragg Grating (FBG) strain gauges or accelerometers are used for data acquisition.
Author(s): Yang W, Lang Z, Tian W
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Industrial Electronics
Print publication date: 01/10/2015
Online publication date: 02/04/2015
Acceptance date: 07/03/2015
Date deposited: 23/08/2016
ISSN (print): 0278-0046
ISSN (electronic): 1557-9948
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