Campus Units
Civil, Construction and Environmental Engineering, Electrical and Computer Engineering, Mechanical Engineering, Center for Nondestructive Evaluation (CNDE)
Document Type
Conference Proceeding
Conference
SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring
Publication Version
Published Version
Publication Date
4-12-2017
Journal or Book Title
Proceedings of SPIE
Volume
10168
Issue
1016815
First Page
1016815-1
Last Page
1016815-12
Research Focus Area
Structural Engineering
DOI
10.1117/12.2261531
Conference Title
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
Conference Date
March 25-29, 2017
City
Portland, OR
Abstract
Damage detection of wind turbine blades is difficult due to their large sizes and complex geometries. Additionally, economic restraints limit the viability of high-cost monitoring methods. While it is possible to monitor certain global signatures through modal analysis, obtaining useful measurements over a blade's surface using off-the-shelf sensing technologies is difficult and typically not economical. A solution is to deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel large-area electronic sensor measuring strain over very large surfaces. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a hybrid dense sensor network of soft elastomeric capacitors to detect, localize, and quantify damage, and resistive strain gauges to augment such dense sensor network with high accuracy data at key locations. The proposed hybrid dense sensor network is installed inside a wind turbine blade model and tested in a wind tunnel to simulate an operational environment. Damage in the form of changing boundary conditions is introduced into the monitored section of the blade. Results demonstrate the ability of the hybrid dense sensor network, and associated algorithms, to detect, localize, and quantify damage.
Copyright Owner
Society of Photo-Optical Instrumentation Engineers (SPIE)
Copyright Date
2017
Language
en
File Format
application/pdf
Recommended Citation
Downey, Austin; Laflamme, Simon; Ubertini, Filippo; and Sarkar, Partha, "Experimental damage detection of wind turbine blade using thin film sensor array" (2017). Civil, Construction and Environmental Engineering Conference Presentations and Proceedings. 57.
https://lib.dr.iastate.edu/ccee_conf/57
Included in
Civil Engineering Commons, Structural Engineering Commons, VLSI and Circuits, Embedded and Hardware Systems Commons
Comments
This proceeding is published as Austin Downey, Simon Laflamme, Filippo Ubertini, Partha Sarkar, "Experimental damage detection of wind turbine blade using thin film sensor array", Proc. SPIE 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017, 1016815 (12 April 2017); doi: 10.1117/12.2261531. Posted with permission.