Self-correction of Methane Sensor Based on GM(1,1) Model of Grey Forecasting Theory

摘要

The GM(1,1) model of grey forecasting theory has not yet been applied to the self-correction of sensors, because it has a serious defect in forecasting random serials with big fluctuation. However, though the measured data of a methane sensor are disorderly and unsystematic, the measured error of the sensor can be regarded as a random serial with small fluctuation. So, in combination with single-chip microcomputer technique, the GM(1,1) model of grey forecasting theory can be used to realize the self-correction of methane sensors. Test with the KJ-1 methane sensor has proven that the fitting degree between the forecast methane density and the actual density is satisfying.