To enable the detection of carbon monoxide (CO) in automobile exhaust, this study designs and implements a CO detection system based on photoacoustic spectroscopy. By optimizing the excitation light source, photoacoustic cell, signal processing unit, and data acquisition module, the key challenges of sensitivity, stability, and signal-to-noise ratio in real-time monitoring are effectively addressed. Experimental results demonstrate that the system performs excellently within the concentration range of 120 ppm to 1200 ppm, with a maximum relative error not exceeding 1.8%. These results verify the system's high sensitivity and accuracy. The system shows significant potential for widespread application, providing reliable data support for automobile exhaust monitoring.
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Yuanhan Chen (2024) studied this question.
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