Noise analysis of respirable dust by photoacoustic spectroscopy

Abstract

In response to the demand for high sensitivity and stability during respiratory dust detection, photoacoustic spectroscopy is proposed for real-time monitoring of respiratory dust. The influence of the background noise generated by the inlet flow and the small suction pump on the experiment was analyzed, and noise reduction was carried out by physical methods such as adding a sound insulation layer to the small suction pump, as well as the Kalman filtering method was added to the LabVIEW software to further reduce the influence of noise. To carry out the detection of respirable dust in the ambient atmosphere. The detection under 0.2 μm filter membrane can filter out the effect of environmental dust, and the collection efficiency of 5 μm diameter dust is 50%; therefore, 5 and 0.2 μm filter membranes were added at the air inlet for respiratory dust detection, and two groups of experiments were carried out by using 5 and 0.2 μm filter membranes to obtain the change curve of the respiratory dust by the differential method. Through experimental validation, it is shown that the detection system can further improve the detection accuracy and stability of respiratory dust with the processing of physical noise reduction and Kalman filtering and can meet the monitoring of respiratory dust in the environmental atmosphere.