Noise Reduction of Wavelength-Modulated Signal Based on Wavelet and Empirical Mode Decomposition

Wavelength modulation signal (WMS) based on tunable diode laser absorption spectroscopy (TDLAS) is an effective trace gas detection technology. It offers several advantages such as high selectivity, high precision, and high sensitivity, as well as real-time online monitoring. In the field measurement process, background noise and optical fringes significantly reduce the system's measurement accuracy, affecting the concentration measurement results. To effectively eliminate the effect of these noise on the measurement and improve the signal to noise ratio (SNR) of the system, this study proposes a digital filtering denoising method based on wavelet transform combined with empirical mode decomposition (EMD). The NH, with low mass concentration was measured experimentally, and the wavelet transform filtering, EMD filtering, and wavelet transform combined with the EMD filtering were used to reduce noise in the obtained harmonic signals. The experimental results show that the wavelet transform combined with the EMD filtering has the best noise reduction effect compared to the other two methods. The SNR of the wavelet transform combined with the EMD filtering increases from 28.4 dB to 446 dB for NH3 with a mass concentration of 11.38 mg/m(3). Thus, the proposed method significantly improves the system's measurement accuracy.