基于ICEEMDAN-PE-SVD的水电机组振动信号的剥离方法的研究
Fangqing Zhang1,2, Jiang Guo1,2, Fang Yuan1,2
1Intelligent Power Equipment Technology Research Center, Wuhan University, Wuhan 430072, China.
Sensors (Basel, Switzerland)
|July 29, 2023
概括
结合ICEEMDAN,PE和SVD的新方法有效地消除了水力发电机组的振动信号,提高了故障诊断的准确性. 这种方法显著提高了信号与噪声的比率,并减少了与现有方法相比的错误.
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:
- 振动监测对于水电机组的故障诊断至关重要.
- 噪音干扰显著挑战从振动信号中精确的特征提取.
- 在复杂的工业环境中,现有的排污方法往往不足.
研究的目的:
- 开发一种新且有效的消除水力发电机组振动信号噪声的方法.
- 通过提高信号质量来提高故障诊断的准确性.
- 在具有挑战性的运行条件下提供可靠的降噪解决方案.
主要方法:
- 提出了一种混合无声化技术,将改进的互补集合实证模式分解与自适应噪声 (ICEEMDAN),顺序 (PE) 和单数值分解 (SVD) 整合在一起.
- 采用ICEEMDAN将信号分解为内在模式函数 (IMF),然后使用基于PE的IMF选择初始denoising.
- 根据单数值分析和能量分布,将SVD应用于部分无声化信号以减少二次噪声.
主要成果:
- 拟议的ICEEMDAN-PE-SVD方法与波段值,SVD,CEEMDAN-PE和ICEEMDAN-PE相比显示出更高的消噪性能.
- 在信号与噪声比 (SNR) 中取得了显著的改进,收益高达8.9871dB.
- 导致根平均平方误差 (RMSE) 显著降低,高达0.2093.
结论:
- 新的ICEEMDAN-PE-SVD方法提供了一种强大而有效的方法,用于消除水力发电机组的振动信号.
- 这种技术通过提高信号清晰度,显著提高了故障诊断的可靠性.
- 介绍了在关键基础设施监控中的振动信号处理的有价值的新方法.
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