A near‐infrared trace hydrogen sulfide sensor based on CEEMDAN and PSO‐LSSVM

Abstract

AbstractA distribution feedback laser sensor for high precision and high sensitivity detection of the hydrogen sulfide in associated gas from oil fields is developed in this paper. Tunable diode laser absorption spectroscopy and wavelength modulation spectroscopy and were utilized for the H2S concentration detection in the oilfield. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm is used to remove the noise from the spectral signal. Particle swarm optimization‐least squares support vector machine (PSO‐LSSVM) model is applied for concentration prediction. The root mean square error of long‐term stability is 0.323. Allan–Werle deviation analysis shows that the theoretical limit of detection is 71 parts per billion while the optimal integration time reaches 96 s. The sensor is of great significance for real‐time detection of hydrogen sulfide concentration in associated gas in oil fields.