Sensitivity improvement of quartz-enhanced photoacoustic spectroscopy using the stochastic resonance method
Yingchao Xie, Hao Xiong, Shiling Feng, Ning Pan, Chuan Li, Yixuan Liu, Ye Zhang, Ligang Shao, Gaopeng Lu, Kun Liu, Guishi Wang
Abstract
Quartz-enhanced photoacoustic spectroscopy (QEPAS) is a promising technique for trace gas sensing, offering advantages such as compact size and high sensitivity. However, noise remains a critical factor limiting detection sensitivity. In this study, a novel approach was proposed to leverage noise for the enhancement of weak QEPAS signals. The method employs stochastic resonance (SR), which counterintuitively utilizes noise to amplify weak spectral signals, thereby significantly improving the signal-to-noise ratio of the QEPAS sensor. The effectiveness of this approach was demonstrated through methane (CH₄) detection using QEPAS. Experimental results indicate that the SR algorithm enhances the output signal by a factor of 3 and reduces the minimum detection limit (MDL) from 329 ppb to 85 ppb compared to conventional QEPAS. The proposed SR-enhanced algorithm presents a promising strategy for further improving QEPAS sensor performance in trace gas detection.