使用BiL-DCAE的波面传感器的基于深度学习的噪声振动信号
Yun Pan1, Quan Luo1, Yiyou Fan1
1Key Laboratory of Vibration Signal Capture and Intelligent Processing, School of Electronic Engineering, Yili Normal University, 448 Jiefang Road, Yining 835000, China.
Sensors (Basel, Switzerland)
|August 28, 2025
概括
这项研究引入了一种新的BiLSTM无声卷积自编码器 (BiL-DCAE),以改善地震波检测. 这种方法有效地降低了噪音,提高了信号质量和地球物理勘探的准确性.
科学领域:
- 地质学
- 信号处理
- 光学传感器
背景情况:
- 使用波面传感器进行激光遥感对于地质探索至关重要.
- 环境因素如光线和振动带来不可预测的噪音,降低信号质量和检测准确性.
研究的目的:
- 开发一种强大的方法来消除和增强地质探测中的地震振动信号.
- 为了减轻复杂,不可预测的噪音对基于激光的地震波探测的影响.
主要方法:
- 通过单点振动检测实验收集大量数据.
- 分析了信号幅度和点心偏移之间的关系.
- 使用BiLSTM无声卷积自编码器 (BiL-DCAE) 来抑制噪声和增强信号.
主要成果:
- 在振动信号中成功抑制不规则和复杂的噪声.
- 实现了平均信号噪声比提高13.90dB.
- 降低了95.93%的噪声功率,显著提高了检测准确度.
结论:
- BiL-DCAE模型有效地消除和增强地震振动信号.
- 这种方法大大提高了激光遥感在地质勘探中的精度.
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