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CLC number: TP18; V279

On-line Access: 2021-07-20

Received: 2020-04-04

Revision Accepted: 2020-06-09

Crosschecked: 2021-03-17

Cited: 0

Clicked: 2745

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Alisson V. Brito

https://orcid.org/0000-0001-5215-443X

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Frontiers of Information Technology & Electronic Engineering  2021 Vol.22 No.7 P.1002-1009

http://doi.org/10.1631/FITEE.2000149


Motor speed estimation and failure detection of a small UAV using density of maxima


Author(s):  Jefferson S. Souza, Moises C. Bezerril, Mateus A. Silva, Frank C. Veras, Abel Lima-Filho, Jorge Gabriel Ramos, Alisson V. Brito

Affiliation(s):  Laboratory of System Engineering and Robotics, Federal University of Paraiba, Joao Pessoa, Brazil; more

Corresponding email(s):   alissonbrito@ci.ufpb.br

Key Words:  Unmanned aerial vehicle (UAV), Speed identification, Failure detection, Chaos


Jefferson S. Souza, Moises C. Bezerril, Mateus A. Silva, Frank C. Veras, Abel Lima-Filho, Jorge Gabriel Ramos, Alisson V. Brito. Motor speed estimation and failure detection of a small UAV using density of maxima[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(7): 1002-1009.

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author="Jefferson S. Souza, Moises C. Bezerril, Mateus A. Silva, Frank C. Veras, Abel Lima-Filho, Jorge Gabriel Ramos, Alisson V. Brito",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="22",
number="7",
pages="1002-1009",
year="2021",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000149"
}

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%A Moises C. Bezerril
%A Mateus A. Silva
%A Frank C. Veras
%A Abel Lima-Filho
%A Jorge Gabriel Ramos
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A1 - Abel Lima-Filho
A1 - Jorge Gabriel Ramos
A1 - Alisson V. Brito
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DOI - 10.1631/FITEE.2000149


Abstract: 
This work presents the application of the technique named signal analysis based on chaos using density of maxima to analyze brushless direct current motors. It uses a correlation coefficient estimated from the density of maxima of the current signal. This study demonstrates in experiments the speed estimation of a brushless motor on a testbench and failure detection in a small flying drone. The experimental results demonstrate that it is possible to estimate the speed in 97.8% of the cases and to detect failure in 82.75% of the analyzed cases.

基于最大密度的小型无人机电机速度估计与故障检测

Jefferson S. SOUZA1,Moises C. BEZERRIL1,Mateus A. SILVA1,Frank C. VERAS2
Abel LIMA-FILHO3,Jorge Gabriel RAMOS4,Alisson V. BRITO1
1帕拉伊巴联邦大学系统工程与机器人技术实验室,巴西若昂佩索阿
2皮奥伊联邦大学信息系统系,巴西皮库斯
3帕拉伊巴联邦大学机械工程系,巴西若昂佩索阿
4帕拉伊巴联邦大学物理系,巴西若昂佩索阿
摘要:介绍了基于混沌的最大密度信号分析技术在无刷直流电机分析中的应用。利用了从电流信号最大密度估计得出的相关系数。通过实验实现了无刷电机在试验台上的速度估计以及在小型无人机上的故障检测。实验结果表明,在97.8%的案例中可估计电机速度,在82.75%的分析案例中可检测故障。

关键词:无人机;速度识别;故障检测;混沌

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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