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Senior Capstone Project Raven: Study of an Autonomous System Design for Power Line Inspection Based on the Quanser QDrone Platform

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Conference

ASEE 2021 Gulf-Southwest Annual Conference

Location

Waco, Texas

Publication Date

March 24, 2021

Start Date

March 24, 2021

End Date

March 26, 2021

Page Count

15

Permanent URL

https://peer.asee.org/36400

Download Count

39

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Paper Authors

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Jovany Avila University of the Incarnate Word

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Jovany Avila is an undergrad at the University of the Incantate Word studying Mechatronic Engineering, graduating in December 2020. He works in the Autonomous Vehicle Systems (AVS) Lab as the lead Unmanned Aerial System (UAS) researcher and pilot. He is responsible for producing an indoor model of an autonomous UAS to conduct powerline and utilities pole inspections for real world applications. His future interests are to continue his studies in dynamic control systems and data analytics.

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Tristan Brouwer University of the Incarnate Word

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Tristan Brouwer is an undergrad at the University of the Incantate Word (UIW) studying Mechanical Engineering, graduating in December 2020. He has done internships with Precision Drilling Cooperation where he learnt about rig layouts as well as how to use Inventor. He has been a part of the UIW Men’s soccer team throughout his time there, in addition he is a member of the honors program. He is planning to continue his education at UIW pursuing a master’s in Finance.

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Nick Julian Castillo IV

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Okan Caglayan University of the Incarnate Word

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Okan Caglayan is an associate professor in the Department of Engineering at the University of the Incarnate Word (UIW). He received his Ph.D. degree in Electrical Engineering from the University of Texas at San Antonio. The scope of his research ranges from developing new techniques in the areas of digital signal processing with pattern recognition applications to building innovative Internet of Things (IoT) and big data analytics frameworks to be implemented in real-time. Prior to joining UIW, Dr. Caglayan worked as an engineering consultant in the Applied Power Division at Southwest Research Institute. In addition, he was a lecturer in the Department of Physics and Astronomy at the University of Texas at San Antonio teaching Engineering Physics with emphasis on electromagnetism, mechanics and optical science.

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Michael Frye University of the Incarnate Word

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Michael T. Frye, Ph.D. is an Associate Professor of Engineering in the Department of Engineering at the University of the Incarnate Word, in San Antonio, TX. He is an Electrical Engineer who specialized in the field of nonlinear control theory with applications to autonomous air vehicles. Dr. Frye’s research interest is in discovering new and efficient techniques that mitigates the effects of uncertainty in complex nonlinear dynamics; such as seen in autonomous vehicle systems. Dr. Frye is the PI and Laboratory Director for the Autonomous Vehicle Systems Lab sponsored by the Air Force Office of Scientific Research.

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Abstract

This paper presents a senior capstone research experience in developing an autonomous system using the Quanser QDrone to perform above-ground autonomous power line inspections. The power line infrastructure is exposed to various extreme weather conditions that create an operational concern for the utility companies. Frequent inspections ensure the safe operation of a power transmission grid. There are mainly two methods of inspections, i.e. ground and air. The ground inspections are often slow and difficult due to the rough terrain, utility pole height and inaccessible remote areas. The aerial inspections are accomplished by deploying helicopters that are expensive to operate, maintain, and repair. Lightweight, portable and easy to deploy and use in even hard-to-reach locations, the Unmanned Aerial Vehicles (UAV) are being widely adopted by energy and utility companies for power line inspections due to their safety and cost-effective inspection processes. UAV inspections of utility tower structures and power lines reduce corrective maintenance costs and improve asset life, while avoiding hazardous manhours. Detailed visual imagery captured by drones allows for easier, safer, and faster identification and analysis of structural defects, hotspots, and other anomalies. The objectives of this Senior Capstone were twofold: 1) To develop an autonomous UAV system to detect and track power lines and utility poles to perform fault inspections of their electrical and material components; 2) To investigate the regulations for autonomous aerial vehicle operations. The proposed algorithm used a state machine to make decisions for searching, identifying or flying along utility poles and power lines. The proposed system was implemented using Mathworks MATLAB and Simulink with Quarc, a third party toolbox designed by Quanser, enabling real time applications with the QDrone. Project Raven was funded by the Autonomous Vehicle System (AVS) Laboratory under the supervision of Dr. Michael Frye, PI and Director of the AVS Lab at the University of the Incarnate Word located in San Antonio, Texas. This project provided the senior engineering students an invaluable opportunity to apply their existing technical knowledge, improve their time management, communication skills, and work as a team on a real-world problem.

Avila, J., & Brouwer, T., & Castillo, N. J., & Caglayan, O., & Frye, M. (2021, March), Senior Capstone Project Raven: Study of an Autonomous System Design for Power Line Inspection Based on the Quanser QDrone Platform Paper presented at ASEE 2021 Gulf-Southwest Annual Conference, Waco, Texas. https://peer.asee.org/36400

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