基于CEEMDAN-ICA算法的爆炸振动信号的否定
1Shaanxi Provincial Land Engineering Construction Group Northwest Branch, Yulin, 714000, Shaanxi, China. Dazzlingbai@163.com.
Scientific reports
|November 28, 2023
概括
这项研究引入了一种新的CEEMDAN-ICA方法,可以有效地消除爆炸振动信号,提高准确性并保留关键数据以进行更好的分析.
科学领域:
- 地质物理学 地质物理学
- 信号处理 信号处理
- 振动分析 振动分析
背景情况:
- 爆炸振动信号经常被建筑环境和设备的噪音污染.
- 有效的信号预处理对于精确分析爆炸振动至关重要.
研究的目的:
- 提出和评估一种新的无声化方法,用于爆发振动信号.
- 为了有效地减轻噪声组件,并保留有效的信号信息.
主要方法:
- 使用CEEMDAN (互补组合实证模式分解) 来将信号分解为内在模式函数 (IMF).
- 应用ICA (独立组件分析) 来估计和提取独立组件.
- 使用ICA组件的排列来重建信号,以消除噪音.
主要成果:
- 与传统算法相比,CEEMDAN-ICA提出的方法表现出了优越的无色化性能.
- 该算法有效地减少了噪音,同时保持了原始爆炸振动信号的完整性.
- 模拟证实了CEEMDAN-ICA方法的可行性和效率.
结论:
- 采用CEEMDAN-ICA方法,在消除爆炸振动信号方面取得了重大进展.
- 这种技术为后续地质物理学和工程信号分析提供了可靠的新方法.
- 精确的除尘对于理解复杂的喷射动态至关重要.
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