Real-Time UAV Fault Detection and Classification Using Measurement Data from the PADRE Database-Reference-Cited by-同舟云学术

Real-Time UAV Fault Detection and Classification Using Measurement Data from the PADRE Database

Published:2024-01-08 Issue: Volume: Page:
ISSN:
Container-title:2024 IEEE/SICE International Symposium on System Integration (SII)
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Author:

Puchalski Radosław¹,Giernacki Wojciech¹,Ha Quang²

Affiliation:

1. Institute of Robotics and Machine Intelligence, University of Technology,Faculty of Control, Robotics and Electrical Engineering of Poznan,Poznan,Poland

2. School of Electrical and Data Engineering, University of Technology Sydney,Faculty of Engineering and Information Technology,Ultimo,NSW,Australia,2007

Funder

Poznan University of Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10417130/10417144/10417427.pdf?arnumber=10417427

Reference26 articles.

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3. Robust manoeuvring of quadrotor under full state constraints;Ganguly,2022

4. Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

5. Integrated fault-tolerant control of a quadcopter UAV with incipient actuator faults;Kantue;International Journal of Applied Mathematics and Computer Science,2022

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. UAV propeller fault diagnosis using deep learning of non-traditional χ2-selected Taguchi method-tested Lempel–Ziv complexity and Teager–Kaiser energy features;Scientific Reports;2024-08-10

2. PADRE – A Repository for Research on Fault Detection and Isolation of Unmanned Aerial Vehicle Propellers;Journal of Intelligent & Robotic Systems;2024-05-15