A Dual-Adaptive Denoising Algorithm for Brillouin Optical Time Domain Analysis Sensor

A dual-adaptive denoising algorithm based on complementary ensemble empirical mode decomposition (CEEMD) and particle swarm optimization (PSO) is proposed to improve the signal-to-noise ratio (SNR) of Brillouin optical time domain analysis (BOTDA) sensor. Here, CEEMD is employed to decompose the mea...

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Veröffentlicht in:	IEEE sensors journal 2021-10, Vol.21 (20), p.22712-22719
Hauptverfasser:	Zhang, Qian, Wang, Tao, Zhao, Jieru, Liu, Jingyang, Wang, Yahui, Zhang, Jianzhong, Qiao, Lijun, Zhang, Mingjiang
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive algorithms Algorithms Centroids Demodulation Empirical analysis Frequency shift Noise levels Noise reduction Optical fiber amplifiers Optical fiber filters Optical fiber sensor Optical fiber sensors Optical fibers Particle swarm optimization Sensors Signal processing algorithms Signal to noise ratio stimulated Brillouin scattering Time domain analysis
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