Department: Structural Engineering
Faculty Advisor(s): Francesco Lanza di Scalea

Primary Student
Name: Arun Manohar
Email: armanoha@ucsd.edu
Phone: 858-692-9168
Grad Year: 2012

Wind energy is an attractive power source because it is plentiful and renewable. It is clean and it produces no greenhouse gas emissions. A recent report from the American Wind Energy Association ranks Wind as the primary source of Renewable Energy in the U.S., accounting for 42% of the installed renewable power. The U.S. Department of Energy has set the ambitious target of wind producing 20% of the U.S. electric supply by 2030. Wind turbine blades are primarily composite structures. These structures suffer from structural fatigue, that can cause malfunctioning and even catastrophic collapse, and that initiates as small defects (flaws). The bulk of the defects in wind turbine blades occur during the manufacturing phase; the rest are due to stresses caused by the aerodynamic loads and aging. The presence of defects severely affects performance and strength of the wind turbines and reduces the cost effectiveness of the system. Early damage detection is critical to avoid reduced energy efficiency and expensive repairs. A new method to detect defects and monitor the health of wind turbine blades - before installation and during service is proposed using Advanced Infrared Thermography. An infrared nondestructive technique is an ideal candidate for this application due to its non-contact nature and wide-area inspection capability. The anticipated equipment cost of a portable setup would amount to $20,000 which is marginal compared to the cost of the Wind Turbines. Because Infrared Thermography is basically a vision-based system (in the IR range), it will be possible to consider different fields of view/zoom and inspect a large area of the blade at once. Preliminary results obtained on a 9m real-world Wind Turbine that is housed in the UCSD Powell lab look promising. The blade contains over 41 documented defects of different types at known locations. The method could also be used for health monitoring and defect detection in the Aerospace industry and other sectors where high performance composites are preferred.

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