
Proceedings Paper
Acoustic emission monitoring of wind turbine bladesFormat | Member Price | Non-Member Price |
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Paper Abstract
Damage to wind turbine blades can, if left uncorrected, evolve into catastrophic failures resulting in high costs and
significant losses for the operator. Detection of damage, especially in real time, has the potential to mitigate the losses
associated with such catastrophic failure. To address this need various forms of online monitoring are being investigated,
including acoustic emission detection. In this paper, pencil lead breaks are used as a standard reference source and tests
are performed on unidirectional glass-fiber-reinforced-polymer plates. The mechanical pencil break is used to simulate an
acoustic emission (AE) that generates elastic waves in the plate. Piezoelectric sensors and a data acquisition system are
used to detect and record the signals. The expected dispersion curves generated for Lamb waves in plates are calculated,
and the Gabor wavelet transform is used to provide dispersion curves based on experimental data. AE sources using an
aluminum plate are used as a reference case for the experimental system and data processing validation. The analysis of
the composite material provides information concerning the wave speed, modes, and attenuation of the waveform, which
can be used to estimate maximum AE event – receiver separation, in a particular geometry and materials combination. The
foundational data provided in this paper help to guide improvements in online structural health monitoring of wind turbine
blades using acoustic emission.
Paper Details
Date Published: 27 March 2015
PDF: 15 pages
Proc. SPIE 9439, Smart Materials and Nondestructive Evaluation for Energy Systems 2015, 94390C (27 March 2015); doi: 10.1117/12.2084527
Published in SPIE Proceedings Vol. 9439:
Smart Materials and Nondestructive Evaluation for Energy Systems 2015
Norbert G. Meyendorf, Editor(s)
PDF: 15 pages
Proc. SPIE 9439, Smart Materials and Nondestructive Evaluation for Energy Systems 2015, 94390C (27 March 2015); doi: 10.1117/12.2084527
Show Author Affiliations
Jeremy Van Dam, Iowa State Univ. (United States)
Leonard J. Bond, Iowa State Univ. (United States)
Published in SPIE Proceedings Vol. 9439:
Smart Materials and Nondestructive Evaluation for Energy Systems 2015
Norbert G. Meyendorf, Editor(s)
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