A Novel Carbon Monoxide Detection System Based on Infrared Absorption Used in Mine

At present carbon monoxide detection system has the general problems of low detecting precision, easily poisoning and aging, short service life, narrow measurement range and bed anti-jamming ability. Considering the complexity of the circumstance and the diversity of the interference factors in mine, dual light sources and four detectors system is introduced into the new optical structure and most of the interference factors such as power source anti-jamming, mismatch of the detectors, gas cell material´s absorption, and dust´s influence and etc can be compensated. In addition, an infrared carbon monoxide (CO) sensor´s mathematical model is built by adopting radial basic function´s (RBF) neural network model, so as to dispel the influence of temperature, pressure and humidity. A momentum factor´s gradient descending method can be applied to adjust the parameters of RBF neural network. The experimental results have shown that the whole system has a high precision, a strong capacity of anti-jamming, a wide measurement range, a good selectivity, and an online detecting ability