通过VMD和MODWPT消除旋转机械的振动信号的方法
Xiaolong Zhou1, Xiangkun Wang1, Haotian Wang1
1Mechanical Engineering College, Beihua University, Jilin City 132021, China.
本研究介绍了使用最大重叠离散波束包转换 (MODWPT) 和变化模式分解 (VMD) 的旋转机械振动信号的改进无声化技术. 该方法有效过噪声,提高了故障特征提取的准确性.
科学领域:
- 机械工程 机械工程
- 信号处理 信号处理
- 振动分析 振动分析
背景情况:
- 来自旋转机械的振动信号经常被噪声污染,阻碍了准确的特征提取.
- 传统的线性过方法不足以消除这些复杂的信号.
研究的目的:
- 开发用于旋转机械的增强信号消噪方法.
- 为了提高故障特征提取从噪音振动信号的精度.
主要方法:
- 拟议的方法结合了最大重叠的离散波段数据包转换 (MODWPT) 和变化模式分解 (VMD).
- VMD将信号分解为内在模式函数 (IMF),使用复合加权 (CWE) 删除幻象组件.
- MODWPT用于分解和去除高频噪声,然后使用差异度 (DID) 进行特征提取.
主要成果:
- 改进的方法成功地重建了信号的内在特征,并消除了高频组件.
- 对波形值否定 (WTD),实证模式分解重建否定 (EMD-RD) 和集体实证模式分解波形值否定 (EEMD-WTD) 的比较分析显示出优异的性能.
- 实现了信号特征信息的准确提取,同时有效过噪声组件.
结论:
- 组合的MODWPT和VMD方法提供了一个强大的解决方案,用于消除旋转机械的振动信号.
- 这种技术显著提高了旋转机械故障诊断的可靠性.
- 该方法在分析模拟和现实世界轮故障信号方面表现出有效性.
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