Abstract
The inspection of power transmission and distribution systems is performed visually by foot patrolling and helicopter methods. These methods have various disadvantages such as time-consuming, high operating cost, safety issues, and improper results. To overcome this issue, power utility companies are searching for the alternatives like Unmanned Aerial Systems (UAS) or drones. UAS are safe, cost effective, and requires less time for power transmission line inspection compared to the regular methods. In this manuscript, a decisive flight path planning for UAS to visually inspect a power transmission line and towers is explained. The objective of this paper is to maximize the performance of three functions such as coverage of transmission tower, quality of captured image, and flight time. Second, proposing an automated inspection strategy for UAS to follow the overhead power transmission lines. These objectives are achieved by formulating a cost function, to convert the path planning into a safe operation for UAS. The results of Particle Swarm Optimization (PSO) and Simulated Annealing (SA) are compared to find the best path for UAS. The experimental finding shows that PSO algorithm has higher efficiency and effectiveness compared to the SA algorithm and benefits the UAS with a safe flight path for the inspection of power transmission towers.
ACKNOWLEDGMENTS
The authors would like to thank the project “Quad-copter application for live inspection of power transmission lines” (Ref no: T-32) funded by ICPS-DST, India, for supporting this research.
CREDIT AUTHORSHIP CONTRIBUTION STATEMENT
MD. Faiyaz Ahmed: Visualization, Conceptualization, Writing-original draft, Methodology.
J. C. Mohanta: Investigation, Analysis, editing, and Supervision.
Alok Sanyal: Review & editing.
Pankaj Singh Yadav: Review & editing.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
M. D. Faiyaz Ahmed
MD Faiyaz Ahmed received the MTech degree in automation from Jawaharlal Nehru Technological University, Hyderabad (JNTUH), India, in 2018. He was a senior research fellow in the Mechanical Engineering Department, specializing in Robotics at Motilal Nehru National Institute of Technology Allahabad. Currently, he is working as an assistant professor in the Department of Mechanical Engineering (Robotics and Automation) at Vignan's Foundation for Science, Technology & Research, Guntur, India. His current research interests include unmanned aerial vehicles (UAV), path planning, Neural Networks (NN), and additive manufacturing. Email: [email protected]
J. C. Mohanta
J C Mohanta is presently working as professor in Department of Mechanical Engineering of Motilal Nehru National Institute of Technology Allahabad. Initially, he served as engineering officer in Mechanical Engineering Division of Central Power Research Institute, Bangalore. He has 15 years of research and teaching experience. He is a member of The Institution of Engineers (India) and many national and international societies. Presently, he is engaged in research work focusing on navigational behavior of mobile robots and unmanned aerial vehicles (UAV) using various AI techniques. Corresponding author. Email: [email protected]
Alok Sanyal
Alok Sanyal received the MTech degree in mechanical engineering from Motilal Nehru National Institute of Technology Allahabad (MNNIT) Prayagraj, Uttar Pradesh, India, in 2017. Now he is a research scholar in Department of Mechanical Engineering, MNNIT Allahabad. His current research interests include solar tracking systems, path planning and fuzzy logic. Email: [email protected]
Pankaj Singh Yadav
Pankaj Singh Yadav received the MTech degree in mechanical engineering from Motilal Nehru National Institute of Technology Allahabad (MNNIT) Prayagraj, Uttar Pradesh, India, in 2019. Now he is a research scholar in Department of Mechanical Engineering, MNNIT Allahabad. His current research interests include mecanum wheel-chair design, path planning, and motion control. Email: [email protected]