Dissolved Gas Analysis in Transformer Oil Using Pt-Doped WSe₂ Monolayer Based on First Principles Method

Abstract

The composition and content of dissolved gases in transformer oil are closely related to the type of faults in the transformer and the severity of potential hazards. Dissolved gas analysis (DGA) in insulating oil is an important way to monitor the state of transformer equipment. CO, CH 4 , and C 2 H 2 are one of the dissolved gases in the transformer oil. Based on the density functional theory, the optimal adsorption site of the transition metal atom Pt on the surface of WSe 2 , one of the typical layered transition metal disulfides (LTMDs), is determined in the beginning. Attaining the adsorption behavior of these three gases on the surface of Pt-WSe 2 . The optimal structure of gas adsorption, charge transfer, adsorption energy, electronic density of states (DOS), deformation charge density (DCD), and frontier orbital are analyzed. As an electron acceptor, Pt-WSe 2 attracts electrons from all three gas molecules. The adsorption type of CO and C 2 H 2 molecules is chemisorption, whose adsorption effect is strong. The CH 4 adsorption is physical adsorption, whose adsorption effect is weak. The adsorption of all the three gas molecules leads to an increase in the bandgap of the Pt-WSe 2 , that is, the increase in the resistivity.INDEX TERMS Adsorption, transformer oil, Pt-WSe 2 monolayer, DGA, first-principles calculation.

Recursive parameter estimation methods and convergence analysis for a special class of nonlinear systems

“…The simulation results show that the BSO-HMISG algorithm can generate more accurate parameter estimates than the BSO-HSG algorithm. The proposed methods in this paper can be extended to study the parameter estimation problems of different systems with complex disturbances [72][73][74][75] and can be applied to other engineering areas [76][77][78][79][80][81] such as signal modeling and communication networked systems. [82][83][84][85][86]…”

Moving data window gradient‐based iterative algorithm of combined parameter and state estimation for bilinear systems

“…Similarly, the data filtering is also used in multivariate pseudo‐linear systems to deal with various stochastic system identification problems . It can combine some mathematical tools and strategies to develop new parameter identification theory and approaches for dynamical systems and can be applied to other literatures such as information processing and engineering systems …”

“…21,22 It can combine some mathematical tools and strategies to develop new parameter identification theory and approaches for dynamical systems and can be applied to other literatures 23,24 such as information processing and engineering systems. 25,26 The iterative algorithm processes a batch of measurement data and makes efficient use of the measurement data at each iteration. [27][28][29] Hence, some iterative methods can be used for finding the solutions to some matrix equations 30,31 and for deriving new signal modeling 32,33 and parameter identification algorithms.…”

Recursive methods for estimating the radial basis function‐based state‐dependent autoregressive model

“…Furthermore, the parameter identification issues of controlled auto regressive systems with quantized output were investigated by integrating the auxiliary model with the gradient search . Some parameter estimation methods can be used for establishing the models of different plants and engineering systems . The innovation is the useful information which can be utilized for improving the parameter estimation accuracy.…”

“…24 Some parameter estimation methods can be used for establishing the models of different plants and engineering systems. [25][26][27][28] The innovation is the useful information which can be utilized for improving the parameter estimation accuracy. Based on the innovation correction, the multi-innovation identification theory was presented which not only uses the current innovation but also uses the past innovations to update the parameter estimates.…”