| 王仕昊,高妍,张红娟,靳宝全.小波域噪声估计的分块自适应降噪方法提升Φ-OTDR信噪比研究[J].电子测量与仪器学报,2024,38(6):104-111 |
| 小波域噪声估计的分块自适应降噪方法提升Φ-OTDR信噪比研究 |
| Improving signal-to-noise ratio in Φ-OTDR through block adaptive denoisingmethod in wavelet domain noise estimation |
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| DOI： |
| 中文关键词: 相位敏感光时域反射计 降噪算法 信噪比 连续小波变换 噪声估计 自适应 |
| 英文关键词:Φ-OTDR denoising method SNR CWT noise estimation adaptive |
| 基金项目:国家自然科学基金(62375197)、山西省重点研发计划项目(202102130501021)、中央引导地方科技发展资金项目(YDZJSX20231B004)、山西省基础研究计划(202103021222010)、山西省科技创新团队项目(201805D131003)资助 |
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| Author | Institution |
| Wang Shihao | College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China |
| Gao Yan | College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China |
| Zhang Hongjuan | College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China |
| Jin Baoquan | Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and
Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, China |
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| 中文摘要: |
| 相位敏感光时域反射计(Φ-OTDR)以激光器为探测光源进行光纤沿线振动信号的检测,但激光器的自发辐射现象会导致光场相位发生波动,直接影响相位解调信号的信噪比。针对此问题,提出了一种小波域噪声估计的分块自适应降噪方法。分析了激光器自发辐射导致的相位噪声特征，通过连续小波变换提取系统相位噪声在不同分解尺度下的噪声水平,结合无偏似然估计调整小波系数的分块长度和阈值,实现对不同输入信号的自适应降噪。实验证明,与未经本算法处理相比,在光纤4.5 km处,单频信号的信噪比从40.01 dB提升至54.60 dB,系统的应变分辨率从66.15 pε/√Hz优化至11.69 pε/√Hz;线性扫频信号的信噪比从18.31 dB提升至26.40 dB。与其他同领域的降噪算法相比,单频信号均方根误差低至0.009 6,信噪比增益达到14.59 dB;线性扫频信号的均方根误差低至0.080 9,信噪比增益达到8.09 dB。研究表明,该方法在保留有效信号的同时,抑制了相位噪声,提高了相位还原的精度。 |
| 英文摘要: |
| Phase-sensitive optical time-domain reflectometer (Φ-OTDR) utilizes a laser as the detection light source for detecting vibration signals along the optical fiber. However, the spontaneous emission of the laser can lead to phase fluctuations in the optical field, directly impacting the signal-to-noise ratio (SNR) of the phase demodulated signal. To tackle this issue, a block adaptive denoising method in wavelet domain noise estimation is proposed. The characteristics of phase noise caused by laser spontaneous emission has been analyzed. The phase noise levels at different decomposition scales are extracted using continuous wavelet transform (CWT). By combining with unbiased risk estimation to adjust the block length and threshold of the wavelet coefficients, adaptive denoising for different input signals is achieved. Experimental results demonstrate that compared to untreated signals, at 4.5 km of optical fiber, the SNR of single-frequency signals improves from 40.01 dB to 54.60 dB, and the system’s strain resolution optimizes from 66.15 pε/√Hz to 11.69 pε/√Hz. The SNR of linear swept-frequency signals improves from 18.31 dB to 26.40 dB. In comparison with other denoising algorithms, for single-frequency signals, root mean square error (RMSE) reduces to 0.009 6 with an SNR gain of 14.59 dB; for linear swept-frequency signals, RMSE decreases to 0.080 9 with an SNR gain of 8.09 dB. The study demonstrates that this method suppresses phase noise while preserving effective signals, thereby improving the accuracy of phase recovery. |
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