Optimized VMD Algorithm for Noise Reduction of Absorption Spectra of CO2
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Abstract:
The end tidal carbon dioxide (EtCO2) is crucial for monitoring patients' respiratory function, which reflects the status of lung ventilation and gas exchange. Therefore, achieving accurate measurements of EtCO2 holds significant importance in clinical practice. The measurements of EtCO2 based on wavelength modulation-direct absorption spectroscopy (WM-DAS) had great advantages and the noise reduction of spectrum was very important. An optimized variational mode decomposition (VMD) algorithm improved by the dung beetle optimization?algorithm?and wavelet packet denoising algorithm was proposed to enhance the measurement accuracy of EtCO2 concentration. The dung beetle optimization?algorithm was used to obtain the optimal number of decomposition mode layers K and secondary penalty factor α. The optimal parameters were used to decompose the original transmitted light intensity signal with noise, and a series of intrinsic mode functions (IMFs) were obtained. Pearson correlation coefficient (R) was used to select the pure signal and the noisy signal, and the noisy signal was denoised by wavelet packet denoising algorithm. The transmitted light intensity signal was reconstructed by the signal processed by wavelet packet denoising algorithm and the pure signal. The results showed that the proposed algorithm could effectively remove the noise of signal of transmitted light intensity and improve the accuracy of concentration measurements of EtCO2.
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Project Supported:
the Key Research and Development Program of Hebei Province
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