用于基于光谱振幅调制和波段值去除的低速轴承故障诊断的特征提取
Xiaojia Zu1, Wenhao Sun2, Yuncheng Guo1
1School of Marine Engineering Equipment, Zhejiang Ocean University, Zhoushan 316022, China.
Sensors (Basel, Switzerland)
|June 27, 2025
概括
这项研究引入了一种用于在低速环境中诊断轴承故障的新方法. 它使用波波变频和光谱振幅调制来有效地检测强噪声中的弱故障特征.
科学领域:
- 机械工程 机械工程
- 信号处理 信号处理
- 状态监控 状态监控
背景情况:
- 在低速条件下提取轴承故障特征是具有挑战性的,因为信号较弱和环境噪声较大.
- 传统的光谱振幅调制方法对噪声非常敏感,这限制了它们的有效性.
研究的目的:
- 提出一个强大的低速轴承故障诊断方法.
- 在杂的环境中克服传统方法的局限性.
- 为了增强弱断层特征的提取.
主要方法:
- 波段值消噪应用于原始信号以减少背景噪声.
- 在denoised信号上的光谱振幅调制以增强轴承故障冲动.
- 封面光谱的规范化,以清晰可视化故障频率.
主要成果:
- 拟议的方法有效地减少了低速信号中的噪声干扰.
- 弱轴承故障特征即使在强噪声的情况下也能成功地提取出来.
- 模拟和实验信号分析证实了该方法的有效性.
结论:
- 开发的方法为低速轴承故障诊断提供了可靠的方法.
- 它通过提高信号清晰度显著提高检测故障的能力.
- 这种技术为在具有挑战性的低速应用中进行条件监测提供了实用解决方案.
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