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. 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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基于最大密度的小型无人机电机速度估计与故障检测

常规文章 | Updated：2022-06-06

- 基于最大密度的小型无人机电机速度估计与故障检测
- Motor speed estimation and failure detection of a small UAV using density of maxima
- 信息与电子工程前沿（英文） 2021年22卷第7期页码：1002-1009
- 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：
  
  Project supported by the Higher Education Improvement Coordination (CAPES) and the National Council for the Scientific and Technological Development (CNPq), Brazil
- DOI：10.1631/FITEE.2000149
  中图分类号：
- 收稿：2020-04-04，
  
  修回：2021-;3-17，
  
  纸质出版：2021-07
- Accepted：
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Jefferson S. SOUZA, Moises C. BEZERRIL, Mateus A. SILVA, 等. 基于最大密度的小型无人机电机速度估计与故障检测[J]. 信息与电子工程前沿（英文）, 2021,22(7):1002-1009.

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.
Jefferson S. SOUZA, Moises C. BEZERRIL, Mateus A. SILVA, 等. 基于最大密度的小型无人机电机速度估计与故障检测[J]. 信息与电子工程前沿（英文）, 2021,22(7):1002-1009. DOI： 10.1631/FITEE.2000149.

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.

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references

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