A method of zero self-modification and temperature compensation for indoor air quality etection based on a software model

It is very difficult to apply non-dispersive infrared sensor to detect the indoor air quality and maintain very low zero and temperature drift over long periods. Frequently manual zero setting and calibration are required. To solve the issues of zero and temperature drift of non-dispersive infrared sensor, a software model based on zero gas intensity, reference channels intensity, standard temperature, environmental temperature, temperature drift coefficient, etc. has been established to automatically modify and compensate the zero and temperature drift existing in the long-term continuous operation of the infrared sensor. The test result and long-term application indicate the detection precision of the instrument is less than 5%F.S in various changing environmental conditions. The average detection precision of carbon dioxide has been improved from 9.26% before comprehensive processing to 1.23% after processing, while the average detection precision of methane has been improved from 10.61% before comprehensive processing to 0.70% after processing. As a result, the disadvantages existing in many gas detectors including poor stability and short calibration cycle have been overcome, thus effectively improving the detection precision and stability of the instrument and reducing the maintenance cost.