Application for methane gas detection and measurement using adaptive time synchronous moving average

Abstract

Methane is a potent greenhouse gas originating from both natural and anthropogenic sources. Detecting and quantifying methane emissions is crucial for environmental protection and industrial safety. This paper presents a software application designed for methane gas detection and concentration estimation based on an adaptive time synchronous moving average (ATSMA) algorithm. The software integrates signal classification, preprocessing, and estimation of methane concentration using absorption pulse parameters. The proposed ATSMA algorithm enhances signal periodicity while effectively reducing noise, leveraging the zero–crossing rate (ZCR) property to optimize averaging cycles. The processing workflow involves multiple steps, including initialization, gas classification, ATSMA filtering, multiband decomposition and absorption pulse estimation. The graphical interface provides signal visualization in both time and frequency domains, displaying key methane parameters such as spectral harmonic ratios and absorption pulse characteristics.