使用振动测量进行轴承故障检测的增强的TK技术.
Megha Malusare1, Manzar Mahmud2, Wilson Wang1
1Department of Mechanical and Mechatronics Engineering, Lakehead University, Thunder Bay, ON P7B 5E1, Canada.
Sensors (Basel, Switzerland)
|November 13, 2025
概括
这项研究引入了一种增强的Teager-Kaiser (eTK) 技术,用于可靠的轴承故障检测和诊断. 该方法使用经验模式分解和eTK无声过器来改进振动信号分析,以便早期识别故障.
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:
- 滚动元件轴承是旋转机械中的关键部件.
- 有效的轴承故障检测对于防止性能下降和降低维护成本至关重要.
- 现有的故障检测方法在可靠性方面面临挑战.
研究的目的:
- 提出一种增强的Teager-Kaiser (eTK) 技术,以改善轴承故障检测和诊断.
- 提高轴承状况监测的准确性和可靠性.
主要方法:
- 利用振动信号进行轴承故障分析.
- 采用经验模式分解 (EMD) 来识别代表性的内在模式函数 (IMF).
- 开发了一种eTK无声过器,以提高IMF选定的特征的信号噪声比.
- 应用分析信号频谱分析用于特征识别.
主要成果:
- 拟议的eTK技术在轴承故障检测和诊断方面表现出有效性.
- 结合EMD和eTK无效改进了从振动信号中识别故障相关的特征.
- 实验验证证了该技术在各种轴承条件下的能力.
结论:
- 增强的Teager-Kaiser (eTK) 技术为轴承故障检测提供了一种新有效的方法.
- 该方法成功地解决了可靠的轴承状况监测方面的挑战.
- 拟议的技术有可能在工业机械维护方面得到实际应用.
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