Research Article Damage Identification of Wind Turbine Blades Using Piezoelectric Transducers Seong-Won Choi, 1 Kevin M. Farinholt, 2 Stuart G. Taylor, 2 Abraham Light-Marquez, 2 and Gyuhae Park 1,2 1 School of Mechanical Systems Engineering, Chonnam National University, Gwangju 500-757, Republic of Korea 2 Engineering Institute, MS T001, Los Alamos National Laboratory, Los Alamos, NM 87545, USA Correspondence should be addressed to Gyuhae Park; gpark@chonnam.ac.kr Received 14 February 2013; Accepted 14 June 2013; Published 7 April 2014 Academic Editor: Jung-Ryul Lee Copyright © 2014 Seong-Won Choi et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Tis paper presents the experimental results of active-sensing structural health monitoring (SHM) techniques, which utilize piezoelectric transducers as sensors and actuators, for determining the structural integrity of wind turbine blades. Specifcally, Lamb wave propagations and frequency response functions at high frequency ranges are used to estimate the condition of wind turbine blades. For experiments, a 1m section of a CX-100 blade is used. Te goal of this study is to assess and compare the performance of each method in identifying incipient damage with a consideration given to feld deployability. Overall, these methods yielded a sufcient damage detection capability to warrant further investigation. Tis paper also summarizes the SHM results of a full-scale fatigue test of a 9 m CX-100 blade using piezoelectric active sensors. Tis paper outlines considerations needed to design such SHM systems, experimental procedures and results, and additional issues that can be used as guidelines for future investigations. 1. Introduction Wind turbines are becoming a larger source of renewable energy in the world. Te US government projects that 20% of the US electrical supply could be produced via wind power by 2030 [1]. To achieve this goal, the turbine manufacturers have been increasing the size of the turbine blades, ofen made of composite materials, to maximize power output. As a result of severe wind loadings and the material level faws in composite structures, blade failure has been a more common occurrence in the wind industry. Monitoring the structural health of the turbine blades is particularly important as they account for 15–20% of the total turbine cost. In addition, blade damage is the most expensive type of damage to repair and can cause serious secondary damage to the wind turbine system due to rotating imbalance created during blade failure. Terefore, it is imperative that a structural health monitoring (SHM) system be incorporated into the design of the wind turbines in order to monitor faws before they lead to a catastrophic failure. Tere has been a considerable research efort focused on applying SHM techniques on wind turbine blades [2, 3]. However, most of these studies focus on a single technique for damage detection; consequently very little work has been done to compare the results of multiple active-sensing techniques. Tus, the goal of this study is to assess the relative performance of high-frequency SHM techniques, namely, Lamb wave propagation and frequency response functions (FRFs), as a way to nondestructively monitor the health of a wind turbine blade with piezoelectric active sensors. In conjunction, consideration is given to employing multiple techniques together as a means of increasing the efectiveness of SHM for detecting and locating damage. Tis combination method is possible because of the multifunctional nature of the piezoelectric active sensors. In this paper, an array of piezoelectric sensors on a 1 m section of a 9 m CX-100 blade is used for simulated damage detection under the labora- tory setting. Once the damage detection performance was characterized, the piezoelectric active-sensing techniques are applied to SHM of a full-scale 9 m CX-100 blade, where the Hindawi Publishing Corporation Shock and Vibration Volume 2014, Article ID 430854, 9 pages http://dx.doi.org/10.1155/2014/430854