Honors College Thesis

Bird and bat interaction vision-based detection system for wind turbines

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  • Bird and bat collisions with wind turbine blades are an occurrence which are extremely variable in frequency. With the expansion of wind farms, determining the true quantity of collisions and the species involved is imperative for preventing ecological damage. Explored in this thesis is a blade mounted camera for wirelessly transmitting a video stream to provide an optimal viewing location for capturing avian and bat strikes. An early version of computer vision software for detecting avian flybys and collisions was developed, along with initial design and testing of a blade-tip tracking program. Object recognition using a cascading classifier, and a backup tracking system provides a potential method for determining bird presence and the likelihood of collision. The ability of the program to remove repeating false-positive instances and strengthen the detection system in the process, provides a strong platform for avian detection from a blade mounted camera. Hardware validation was conducted to ensure the selected components will function as needed. A 3D printed on-blade enclosure was designed as a housing for the camera, transmitter, and power supply. Key Words: Bird, Bat, Detection, Tracking, Wind Turbine, Wind Farm
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