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基于改进压缩感知技术的Φ-OTDR系统研究 被引量:1

Phase sensitive OTDR system based on improved compressed sensing technology
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摘要 研究了一种基于改进压缩感知技术的相敏光学时域反射计(phase-sensitive optical time domain reflectometer,Φ-OTDR)系统。对于压缩感知技术,信号稀疏度K直接影响信号恢复的质量。为了提高信号恢复的质量,应该获得更接近原始信号的真实稀疏性度K。因此,提出了一种基于硬阈值的信号稀疏度K的计算方法,同时,采用结合收缩阈值的重构方法,尽可能保留信号的有效成分。实验结果表明,振动频率为1 kHz的正弦振动信号在5.6 km的距离处被成功地重建。与常用的硬阈值压缩传感技术、移动平均去噪技术和Sym8小波去噪技术相比,所提出的压缩感知技术的信噪比分别提高了3.55、13.2和8.02 dB。 A phase sensitive optical time domain reflectometer(Φ-OTDR)system based on improved compressed sensing technology is studied.For compressed sensing technology,signal sparsity K directly affects the quality of signal recovery.In order to improve the quality of signal recovery,K value that is closer to the real sparsity of the original signal should be obtained.Therefore,a method of calculating signal sparsity K based on hard threshold is proposed in this paper.At the same time,the reconstruction method combined with contraction threshold is used to preserve the effective components of the signal as much as possible.The experimental results show that the sinusoidal vibration signal with vibration frequency of 1kHz is reconstructed successfully at a distance of 5.6km.Compared with the common hard threshold compression sensing technology,moving average denoising technology and Sym8 wavelet denoising technology,the SNR of compressed sensing technology in this paper is improved by 3.55,13.2and 8.02dB,respectively.
作者 程亚楠 万生鹏 吕纬龙 张治胜 万东辉 喻俊松 Cheng Ya′nan;Wan Shengpeng;Lv Weilong;Zhang Zhisheng;Wan Donghui;Yu Junsong(Jiangxi Engineering Laboratory for Optoelectronics Testing Technology,Nanchang Hangkong University,Nanchang 330063,China;National Engineering Laboratory for Nondestructive Testing and Optoelectric Sensing Technology and Application,Nanchang Hangkong University,Nanchang 330063,China)
出处 《国外电子测量技术》 北大核心 2023年第3期82-87,共6页 Foreign Electronic Measurement Technology
关键词 相位敏感光时域反射计 压缩感知 稀疏度 光纤传感器 信号重构 phase sensitive optical time domain reflectometer compressed sensing sparsity optical fiber sensor signal reconstruction
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