Research on TDLAS methane detection signal denoising based on improved VMD algorithms
Aims:A Northern Goshawk Optimization(NGO)improved Variational Mode Decomposition(VMD)denoising algorithm was proposed to suppress noise in methane detection systems based on Tunable Semiconductor Laser Absorption Spectroscopy(TDLAS).Methods:Firstly,the second harmonic signal was simulated using MATLAB.Then,the VMD algorithm and the NGO VMD algorithm were used to denoise the second harmonic signal;and the performance of the two methods was compared using the signal-to-noise ratio(SNR),the root mean square error(RMSE),and the correlation coefficient(PCC).Results:The signal-to-noise ratio of the reconstructed signal using the NGO VMD algorithm increased by about 2 times compared to the original signal,with a 97％reduction in the root mean square error and a high correlation coefficient of 0.997.Conclusions:The proposed NGO VMD algorithm has significant advantages over traditional VMD algorithms in various indicators,thus improving the signal-to-noise ratio of the TDLAS methane detection system.Methods:A northern goshawk optimization(NGO)improved VMD denoising algorithm was proposed.First,the second harmonic signal was simulated based on MATLAB.Then the second harmonic signal was denoised using the VMD algorithm and the NGO-VMD algorithm respectively;and the performance of the two methods was compared with the signal-to-noise ratio(SNR),the root-mean-square deviation(RMSE)and correlation coefficient(PCC).Results:The signal-to-noise ratio of the reconstructed signal using the NGO-VMD algorithm was approximately twice that of the original signal.The Root-mean-square deviation was reduced by 97％;and the correlation coefficient was as high as 0.997.Conclusions:The proposed NGO-VMD algorithm has significant advantages over the traditional VMD algorithms in various indicators and improves the signal-to-noise ratio of TDLAS methane detection systems.
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