Damage identification of multirotor UAV propellers via unsteady coupling association
Year: 2024
Type: article
Abstract: To ensure the operational safety of unmanned aerial vehicles (UAVs) and to reduce maintenance costs, real-time monitoring of their system statuses is essential. However, research on multirotor propeller fault diagnosis is limited, and no standardized methodology exists for classifying and evaluating propeller faults. This study proposes a propeller fault diagnosis method based on pressure coupling of pressure pulsation and vibration signals on the arms of multirotors. Aerodynamic models of three types of damaged propellers were established, and the pressure pulsation phenomenon caused by rotating propellers on the arms was investigated using computational fluid dynamics (CFD) methods. Subsequently, a propeller damage identification sensing system was developed, and a propeller damage identification model based on a Long Short-Term Memory (LSTM) network was constructed. The model achieved an accuracy of 96.75%, providing a new approach for improving the accuracy of propeller fault monitoring in multirotors.
Source: Measurement
Authors: Zihao Jiang, Ruitao Ma, Fanghao Lu, Hang Zhu, Yubin Lan, Xinyu Xue, Songchao Zhang, Chundu Wu
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,650
OpenAlex ID: W4405106931