Abstract: Dissolved gases analysis (DGA) is considered as one of the most reliable methods in transformer fault diagnosis technology. In this paper, based on density functional theory, the adsorption performance of SnP₃ monolayer modified by transition metal Pd to six kinds of characteristic gases (H₂, CO, C₂H₂, C₂H₄, CH₄ and C₂H₆) dissolved in oil is calculated. The most structurally stable Pd-doped SnP₃ (Pd-SnP₃) monolayer model is obtained as the basis for subsequent DFT calculations by modeling and computational analysis of different doping sites. Then, based on the model, a large number of adsorption structures are constructed and geometrically optimized. By comparing the adsorption energy and other parameters, the most stable adsorption structure of the SnP₃ monolayer for the six characteristic gases is obtained. Furthermore, the electron density, density of state, energy band and desorption time of the adsorption system are analyzed. The results show that Pd-SnP₃ monolayer has good adsorption properties for CO, C₂H₂ and C₂H₄, while C₂H₂ and C₂H₄ can be rapidly desorbed from the surface of Pd-SnP₃ monolayer at room temperature. Pd-SnP₃ has potential as a low-power gas-sensitive sensor for detecting C₂H₂ and C₂H₄ characteristic gases and as a solid adsorbent material for cleaning CO gases. The simulation calculations in this paper provide theoretical guidance for the development of a SnP₃ monolayer sensor to detect dissolved characteristic gases in transformer oil.