一种基于PCA-VSS-NLMS算法的Φ-OTDR振动信号的SNR增强方法
Xiaojuan Chen1, Haoyu Yu1, Jingyao Xu2
1School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun 130000, China.
Sensors (Basel, Switzerland)
|July 13, 2024
概括
一种新的主要组件分析可变阶段大小规范最小平均平方 (PCA-VSS-NLMS) 方法显著提高了相位敏感光学时域反射仪 (Φ-OTDR) 系统中的振动信号清晰度. 这种先进的无声化技术可以在没有硬件更改的情况下改善信号噪声比 (SNR),从而使更好的远距离振动检测成为可能.
科学领域:
- 光学工程是指光学工程.
- 信号处理 信号处理
- 光纤传感传感器是指光纤传感器.
背景情况:
- 阶段敏感的光学时域反射计 (Φ-OTDR) 系统对于远距离振动检测至关重要.
- 改善 Φ-OTDR 中的振动信号的信号噪声比 (SNR) 对于准确的分析至关重要.
- 现有的无声化方法可能在有效增强 Φ-OTDR 系统的 SNR 方面存在局限性.
研究的目的:
- 为了提出和验证一种新型的无声化方法,主要组件分析可变阶段大小规范最小平均平方 (PCA-VSS-NLMS),用于 Φ-OTDR 系统.
- 为了提高 Φ-OTDR.检测到的振动信号的信号噪声比 (SNR).
- 为改善远距离振动信号检测和识别提供有效和独立于硬件的解决方案.
主要方法:
- 构建了PCA-VSS-NLMS算法的数学原理,允许动态调整输入信号以实现最佳过.
- 通过模拟来验证算法的有效性,将其与波纹消噪 (WD),维纳过,变化模式分解 (VMD) 和可变步骤大小规范最小平均平方 (VSS-NLMS) 进行比较.
- 在 Φ-OTDR 系统中实现了 PCA-VSS-NLMS 算法,以测量带有诱导振动干扰的 11.22 公里的光纤.
主要成果:
- 模拟表明PCA-VSS-NLMS将SNR从-1.23dB提高到30.68dB,超过了其他测试的算法.
- 实验结果显示,在0.07秒的100Hz振动信号中,SNR从8.77dB提高到26.17dB (增加17.40dB).
- 该方法成功地提高了 Φ-OTDR 系统中位置信息的 SNR.
结论:
- PCA-VSS-NLMS算法是 Φ-OTDR 系统中消除振动信号的高效方法.
- 这种技术可以显著提高SNR,而不需要对现有硬件进行修改.
- PCA-VSS-NLMS提供了一种有前途的新方法来检测和识别远距离的振动信号.
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