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

Jefferson S. SOUZA; Moises C. BEZERRIL; Mateus A. SILVA; Frank C. VERAS; Abel LIMA-FILHO; Jorge Gabriel RAMOS; Alisson V. BRITO

doi:10.1631/FITEE.2000149

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

Regular Papers | Updated：2022-06-06

- Motor speed estimation and failure detection of a small UAV using density of maxima
  Enhanced Publication
- 基于最大密度的小型无人机电机速度估计与故障检测
- Frontiers of Information Technology & Electronic Engineering Vol. 22, Issue 7, Pages: 1002-1009(2021)
- Affiliations：
  
  Laboratory of System Engineering and Robotics, Federal University of Paraiba, Joao Pessoa, Brazil
  Department of Information Systems, Federal University of Piaui, Picos, Brazil
  Department of Mechanical Engineering, Federal University of Paraiba, Joao Pessoa, Brazil
  Department of Physics, Federal University of Paraiba, Joao Pessoa, Brazil
- Author bio：
  
  Alisson V. BRITO, E-mail: alissonbrito@ci.ufpb.br
- Funds：
- DOI：10.1631/FITEE.2000149
  CLC：
- Published：2021-07，
  
  Received：04 April 2020，
  
  Revised：17 March 2021，
- Accepted：
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JEFFERSON S. SOUZA, MOISES C. BEZERRIL, MATEUS A. SILVA, et al. 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.
DOI：

JEFFERSON S. SOUZA, MOISES C. BEZERRIL, MATEUS A. SILVA, et al. 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. DOI： 10.1631/FITEE.2000149.

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。

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.

关键词

无人机速度识别故障检测混沌

Keywords

Unmanned aerial vehicle (UAV)Speed identificationFailure detectionChaos

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