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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/20237

Title: Wind turbine blades fault detection based on principal component analysis
Authors: Abdelnasser, Abouhnik
Ghalib R., Ibrahim
Mohammed sh-eldin
A. Albarbar
???metadata.dc.contributor.url???: abouhnik@yahoo.com
Keywords: Principal Components Analysis (PCA);Crack;Residual Matrix
Issue Date: 27-Feb-2012
Publisher: Universiti Malaysia Perlis (UniMAP)
???metadata.dc.publisher.department???: Pusat Pengajian Kejuruteraan Mekatronik
Series/Report no.: Proceedings of the International Conference on Applications and Design in Mechanical Engineering 2012 (ICADME 2012)
Abstract: This paper presents a new approach to detect faults in wind turbine blades. This approach is based on Principal Component Analysis (PCA) of the vibration signal. The residual matrix signals for healthy and faulty system were compared by applying the crest factor. It contains information extracted from the PCA and the faults were found from the comparisons. The experimental work was carried out using three bladed wind turbine. The cracks were simulated on the blade with diameters (3 mm, 6 mm, 9 mm and 12 mm), all had a consistent depth 3 mm. The tests were carried out for two rotation speeds; 250 and 360 rpm. The results showed that PCA of vibration based condition monitoring is a promising technique because it contains information on all the components of the wind turbine contained in the vibration signal. The crest factor was calculated for the PCA residual matrix. The novel approach successfully differentiated the signals from healthy system and system containing cracks in a turbine blade.
Description: International Conference on Applications and Design in Mechanical Engineering 2012 (ICADME 2012) organized by School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), 27th - 28th Februari 2012 at Bayview Beach Resort, Penang, Malaysia.
URI: http://hdl.handle.net/123456789/20237
Appears in Collections:Conference Papers

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