Foreign object detection for wireless power transfer system using YOLO-Fastest

• Main Author: Xie, Penghui
• Other Authors: Tang Yi
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Electrical and electronic engineering::Electric power; Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
• Online Access: https://hdl.handle.net/10356/155420
• Institution: Nanyang Technological University

With the rapid development of wireless power transmission technology, safety requirements during use are getting higher and higher. Due to the coupling air gap in its structure, foreign objects will inevitably be involved during work. The intervention of metal and biological foreign objects causes the system to deviate from the standard operating point and even cause safety accidents. Therefore, foreign object detection (FOD) technology has received widespread attention. This article first introduces the relevant standards of the current foreign object detection technology for wireless power transmission systems. Secondly, it divides the emerging foreign object detection technologies into three categories: auxiliary coil foreign object detection technology, system parameter foreign object detection technology, and sensor foreign object detection technology. Then, the machine vision method was introduced based on deep learning and finally deployed on the Raspberry Pi platform with limited computing power. Finally, it further points out the problems that need to be solved urgently in foreign object detection technology and provides direction for the future research of foreign object detection technology.