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使用信号处理和机器学习进行无人机故障诊断的协议

Luttfi A Al-Haddad¹, Alaa Abdulhady Jaber², Nibras M Mahdi²

¹Training and Workshops Center, University of Technology- Iraq, Baghdad 10066, Iraq.

|October 2, 2024

概括

本研究介绍了使用信号处理和人工智能对无人机 (UAV) 的故障诊断协议. 该方法可以通过振动分析和机器学习在各种无人机模型中准确检测故障.

科学领域:

航空航天工程航空航天工程
人工智能的人工智能
信号处理信号处理

背景情况:

无人机的安全运行需要强大的故障诊断系统.
现有的方法可能缺乏实时故障识别的全面方法.

研究的目的:

提出用于无人机故障诊断的标准化协议.
利用信号处理和人工智能来提高故障检测的准确性.

主要方法:

使用三轴加速度计收集基于振动的信号数据.
预处理数据并提取相关特征.
应用机器学习算法 (深度神经网络,SVM,k-NN) 进行故障分类.

主要成果:

开发的协议显示了准确的故障检测能力.
该方法可适应各种无人机平台.

结论:

拟议的协议为无人机故障诊断提供了一个可靠的框架.
信号处理和AI的整合提高了无人机的安全性和运营完整性.

关键词:

计算机科学计算机科学能源的能量是能量的能量.环境科学环境科学

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