基于的发动机故障检测方法:一篇评论
Sarahi Aguayo-Tapia1, Gerardo Avalos-Almazan1, Jose de Jesus Rangel-Magdaleno1
1Digital Systems Group, National Institute of Astrophysics, Optics and Electronics, Puebla 72840, Mexico.
Entropy (Basel, Switzerland)
|April 26, 2024
概括
值分析有助于通过测量信号障碍来检测运动故障. 这种方法对于工业机械的完整性至关重要,防止损坏和运行停机时间.
科学领域:
- 信号处理 信号处理
- 机器学习 机器学习
- 工业监控 工业监控 工业监控
背景情况:
- 度量化信号的复杂性,对于各种系统的异常检测有用.
- 在工业环境中,早期检测电机故障至关重要,以防止损坏并确保运行连续性.
研究的目的:
- 探索基于的方法来检测电机故障.
- 将理论上的概念与实际的工业需求相结合.
- 审查用于运动故障诊断的的最新进展.
主要方法:
- 使用度测量评估信号复杂性 (振动,定位器电流).
- 从复杂的信号特征生成特征向量.
- 利用人工智能分类器进行故障识别.
主要成果:
- 值方法有效地描述了用于故障检测的电机信号.
- 最近的文献显示,在过去十年中,基于的故障诊断取得了显著进展.
- 该方法有助于区分健康和故障的运动运行状态.
结论:
- 积理论为工业应用中电机故障检测提供了一个强大的框架.
- 集成基于的信号分析可以提高机器完整性和预测性维护.
- 这项研究有助于信号处理,人工智能和工业控制系统的进步.
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