The Compensation Algorithm Based on Bayes Theory of Multi Point Measurement Fusion for Methane Concentration

摘要

The accuracy of laser gas detection is influenced by temperature and other environmental factors. A compensation algorithm based on Bayes theory for measuring the concentration of methane sensor (CABTMCMS) is proposed. Based on several implementation tests, the corresponding supplementary theorems are presented and proved. The algorithm considers the methane concentration and the change of ambient temperature, tested for methane gas spectral absorption peak in the vicinity of the data, and the corresponding temperature, respectively, using the a priori probability of multi-point testing methane concentration data and the corresponding environmental temperature data, the dates are completed fusion, then, compensated the methane concentration test minimum error is reduced to 1%.