在使用香农 entropy 的 DC 电机/发电机中用于火花检测的电流和流浪流组合分析
Jorge E Salas-Robles1, Vicente Biot-Monterde2, Jose A Antonino-Daviu2
1Escuela Técnica Superior de Ingeniera Aeroespacial y Diseño Industrial, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain.
Entropy (Basel, Switzerland)
|September 27, 2024
概括
这项研究引入了一种新方法,通过分析电信号中的香农来监测刷直流电机的健康状况. 这种预测性维护工具可以检测火花,防止故障并提高电动汽车的可靠性.
科学领域:
- 电气工程和应用物理学
- 机械工程和三角学.
- 信号处理和机器状态监控
背景情况:
- 刷式直流电机 (DCM) 在汽车应用中至关重要,如电动汽车 (EV),因为它们的性能特性.
- 在DCM中过早故障,通常是由刷切换器火花引起的,导致经济损失相当大,运行可靠性降低.
- 有效的状态监控对于预测性维护和缓解关键电机系统故障至关重要.
研究的目的:
- 开发和验证用于分析DCM信号中香农的时间和频率演变的新方法.
- 为了研究火花现象,信号和刷直流电机的故障严重程度之间的关系.
- 建立一个预测性维护框架,用于早期检测和评估DCM中的换算质量.
主要方法:
- 采用了两种信号处理方法:用于间接分析的短时间里埃转换 (STFT) 和用于直接分析的S转换.
- 为了计算信号复杂性和信息含量,我们计算了农对于具电流和流浪流量信号.
- 使用实验数据将火花活动与和频谱特征变化相关联.
主要成果:
- 增加的火花活动显著提高了系统,特别是由于分析信号中明显的低频波.
- 两种STFT和S-Transform方法都有效地捕捉了与火花相关的的时间和光谱演变.
- 观察到火花强度,度和信号的增加之间存在明显的相关性.
结论:
- 提出的基于的分析提供了一种可靠的方法来检测和量化刷直流电机中的火花.
- 这种技术可以开发故障严重性指标 (关键性能指标 - - 关键性能指标) 以实时监控状态.
- 这些发现支持该方法作为预测性维护工具的实施,以提高DCM的可靠性并防止昂贵的故障.
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