Sub-ppm NDIR [formula omitted] gas sensor using ICEEMDAN-SG joint denoising algorithm

Abstract

Due to the excellent insulation and arc extinguishing properties of SF6 gas, it is widely used in power equipment such as gas insulated switchgear or gas circuit breaker. Therefore, detection of SF6 gas leakage with high sensitivity is necessary. Non dispersive infrared (NDIR) technology have advantages such as miniaturization, low power consumption, simple structure, low cost, and non-destructive testing, making it suitable for building large-scale sensor networks. However, NDIR sensors are susceptible to noise coming from the emitter, the detector and the circuits, which receives little research attention. In this study, we propose a new denoising method by combining improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) with Savitzky-Golay (S-G) to the noise suppression, which achieves a 7 dB signal-to-noise ratio improvement over the traditional wavelet threshold denoising, making the detection limit of the sensing system reach the level below 1 ppm.