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.

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.

Copyright Owner

Society of Photo-Optical Instrumentation Engineers (SPIE)

Language

en

File Format

application/pdf

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