使用CEEMDAN-PE-SPWVD的铁路铁路波纹的识别方法
Jianhua Liu1, Kexin Zhang1, Zhongmei Wang1
1College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China.
Sensors (Basel, Switzerland)
|January 8, 2025
概括
本研究引入了一种使用CEEMDAN,PE和SPWVD检测铁路波纹的新方法. 该技术能够准确地识别波纹.
科学领域:
- 机械工程 机械工程
- 信号处理 信号处理
- 铁路工程 铁路工程是指铁路工程.
背景情况:
- 铁路波纹会引起车辆轨道系统的振动和损坏.
- 准确识别波纹对于维护和安全至关重要.
- 现有的方法在确定波纹特性时可能缺乏精度.
研究的目的:
- 提出一种用于识别铁路波纹的新方法.
- 为了准确确定铁路波纹的位置,波长和深度.
- 用模拟和现实世界的数据验证拟议的方法.
主要方法:
- 使用完整的集体实证模式分解与自适应噪声 (CEEMDAN) 进行信号分解.
- 采用变 (PE) 来过内在模式函数 (IMFs).
- 应用光滑伪维格纳-维尔分布 (SPWVD) 用于时间频率分析和波纹深度估计.
主要成果:
- 通过CEEMDAN-PE-SPWVD方法,成功地确定了铁路波纹波长和深度.
- 时间频率分析显示,不同地点的波纹严重程度存在差异.
- 使用模拟和测量数据的验证证实了算法的可靠性.
结论:
- 拟议的方法提供了一种可靠的方法来检测和表征铁路波纹.
- 这种技术可以帮助积极维护,并提高铁路基础设施的安全性.
- 进一步的研究可以探索实时实施和与监控系统的集成.
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