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相关概念视频

Downsampling01:20

Downsampling

133
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
133

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采矿风速传感器数据的降噪方法基于CEEMDAN-wavelet值值.

Yu Wang1,2, Jian Liu3,4, Dong Wang1,5

  • 1College of Safety Science and Engineering, Liaoning Technical University, Huludao, 125105, Liaoning, China.

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|October 22, 2024
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概括

这项研究引入了一种用于矿山风速传感器的新型无声化方法,该方法结合了自适应的完整集合实证模式分解 (CEEMDAN) 和波形值. 该方法有效地抑制了流脉冲噪声,提高了智能通风系统中风速测量的准确性.

关键词:
在CEEMDAN,你会发现.数据 降低噪声我的智能通风系统我的风速传感器是我的风速传感器.波形值的门是什么

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科学领域:

  • 采矿工程 采矿工程 采矿工程
  • 信号处理 信号处理
  • 传感器技术 传感器技术

背景情况:

  • 矿山风速传感器对于智能通风系统至关重要.
  • 动荡的空气流脉冲导致地下道中的风速测量不准确.
  • 现有的无声化方法可能无法完全解决风速信号的非静止性.

研究的目的:

  • 为采矿风速信号开发一种先进的消噪技术.
  • 在智能采矿环境中提高风速测量的准确性.
  • 为了应对流脉冲噪声带来的挑战.

主要方法:

  • 适应性完整集体实证模式分解 (CEEMDAN) 用于信号分解.
  • 连续平均平方误差标准用于识别噪音组件.
  • 波段值无声化适用于高频内在模式函数 (IMFs).
  • 从处理和低频IMF中重建无声信号.

主要成果:

  • 拟议的CEEMDAN-wavelet值方法显著减少风速信号中的噪声.
  • 无声化技术实现了更高的信号噪声比率 (SNR) 和更低的根平均平方误差 (RMSE).
  • 对比分析显示,其性能优于传统的EMD-wavelet和EEMD-wavelet方法.

结论:

  • 这种新的联合无雾化方法为矿山风速传感器数据提供了更高的准确性.
  • 这种方法提供了一种可靠的新技术,用于在采矿中处理流脉冲信号.
  • 这些发现有助于开发更强大的智能矿山通风系统.