@inproceedings{534e47ad04334d65ba70d6281f0b42c3,
title = "Experimental Investigation on the Propeller Imbalance Detection via On-Rotor Sensing Vibration for Industrial Drone",
abstract = "Reliability and condition monitoring of mechanical components of industrial drones are crucial for their safe operation. The propeller-motor system is the most critical part of the industrial drone. Among that, detecting the imbalance fault of the propeller is challenging. However, it seriously affects the operation performance by additional vibration due to the imbalance fault and even causes a catastrophic accident. This paper proposes an On-Rotor Sensing (ORS) monitoring method for propeller imbalance fault detection, which uses a cost-efficient MEMS accelerometer mounted in the center of the motor-propeller system to obtain the vibration signal directly for analysis. The experimental results show that this method can identify the slight imbalance fault by approximately 0.25% of the propeller weight. This monitoring method has an economy and robustness for large industrial drones. It also has the potential to detect the other early faults of industrial drones.",
keywords = "Condition monitoring, Fault detection, Industrial drone, On-Rotor Sensing vibration, Propeller imbalance",
author = "Yubin Lin and Chun Li and Shiqing Huang and Dawei Shi and Rongfeng Deng and Guojin Feng and Fengshou Gu",
note = "Funding Information: Acknowledgement. This work was supported by the Special Projects in Key Areas of the Guangdong Provincial Education Department (NO. 2022ZDZX3044), the Special Innovation Project of Guangdong Provincial Education Department (NO. 2022KTSCX199), and the Young Innovative Talents Project of Guangdong Provincial Education Department (NO. 2022KQNCX154). Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference of The Efficiency and Performance Engineering Network 2022, TEPEN 2022 ; Conference date: 18-08-2022 Through 21-08-2022",
year = "2023",
month = mar,
day = "4",
doi = "10.1007/978-3-031-26193-0_94",
language = "English",
isbn = "9783031261923",
volume = "129",
series = "Mechanisms and Machine Science",
publisher = "Springer, Cham",
pages = "1079--1087",
editor = "Hao Zhang and Yongjian Ji and Tongtong Liu and Xiuquan Sun and Ball, {Andrew David}",
booktitle = "Proceedings of TEPEN 2022",
address = "Switzerland",
}