Optimized VMD algorithm for signal noise reduction based on TDLAS

被引：11

作者：

Qi, Gengyu ^{[1
]}

Zhao, Zhanmin ^{[1
]}

Zhang, Ru ^{[1
]}

Wang, Junfen ^{[1
]}

Li, Mingliang ^{[1
]}

Shi, Xuemei ^{[1
]}

Wang, Han ^{[1
]}

机构：

[1] Hebei GEO Univ, Intelligent Sensor Network Engn Res Ctr Hebei Prov, Shijiazhuang, Peoples R China

来源：

JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER | 2024年 / 312卷

关键词：

TDLAS; VMD; Simulation; Adaptive K selection; LMS; Noise reduction; MODE DECOMPOSITION; CO2;

D O I：

10.1016/j.jqsrt.2023.108807

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Currently, traditional variational modal decomposition (VMD) algorithm requires manual selection of the number of decomposition layers K according to the decomposition results, which increases the complexity of the system. What's more, the noise reduction effect of traditional VMD algorithm needs to be further improved for low frequency signal. A kind of optimized VMD algorithm was proposed, which could select the value of K adaptively. The simulated signal containing noise of TDLAS was processed using optimized VMD algorithm, and further denoised by the least mean square (LMS) algorithm. The result shown that the proposed algorithm not only improved reconstruction effect for absorption signal, but also enhanced the measurement accuracy of TDLAS compared with regular noise reduction algorithms.

引用

页数：6

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