基于电机电流信号分析,识别连接轴转子系统的冲击负荷
Kun Zhang1,2, Zhaojian Yang1, Qingbao Bao2
1College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
Sensors (Basel, Switzerland)
|November 9, 2024
概括
本研究引入了一种新的方法,用于识别使用电机电流信号对滚动设备旋转系统的冲击负荷. 这种方法为传统的振动传感器提供了切实可行的替代方案,提高了操作安全性和设备寿命.
科学领域:
- 机械工程 机械工程
- 电气工程 电气工程
- 信号处理 信号处理
背景情况:
- 冲击负载显著降低了滚动设备旋转系统的性能和安全性,导致潜在的故障.
- 传统的冲击负载检测方法通常依赖于振动传感器,这些传感器在滚动环境中很难安装.
研究的目的:
- 提出和验证一种新的方法,使用电机电流信息识别连接轴转子系统的冲击负荷.
- 证明使用电机电流信号作为振动传感器用于冲击负载检测的可行替代品的可行性.
主要方法:
- 用快速里埃转换 (FFT) 分析了电机电流信号,以获得频域信息.
- 使用单值分解 (SVD) 通过删除功率频率组件来消除信号.
- 波段包分解 (WPD) 用于提取能量特征向量.
- 学习矢量量化 (LVQ) 神经网络被用于定性冲击负载识别.
主要成果:
- 拟议的方法成功地识别了连接轴旋转系统上的冲击负载.
- 电机电流信号的使用在识别负载响应方面被证明是有效的.
- LVQ神经网络实现了对冲击负载的良好识别准确性.
结论:
- 基于电机电流的方法是可行和适用的解决方案,用于滚动设备中的冲击负载识别.
- 这种技术克服了与车场传统振动传感器相关的安装挑战.
- 这些发现有助于改善滚动设备的运行安全和维护策略.
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