Under atmospheric pressure, partial discharge initiated by free metallic particles has consistently been a significant factor leading to failures in high-voltage electrical equipment. Simulating the propagation of negative streamer discharge in N₂/O₂ mixtures contributes to a better understanding of the occurrence and evolution of partial discharge, optimizing the insulation performance of electrical equipment. In this study, a two-dimensional plasma fluid dynamics model coupled with the current module was employed to simulate the evolution process of negative streamer discharge caused by one free metallic particle under a suspended potential at 220 kV applied voltage conditions. Simulation results indicated that the discharge process could be divided into two distinct stages: In the first stage, the electron ionization region detached from the electrode surface and propagated independently. During this stage, the corona discharge on the negative electrode surface provided seed electrons crucial for the subsequent development of negative corona discharge. The applied electric field played a dominant role in the propagation of the electron region, especially in the electron avalanche region. In the second stage, space charge gradually took over, causing distortion in the spatial field, particularly generating a substantial electric field gradient near the negative electrode surface, forming an ionization pattern dominated by ionization near the negative electrode surface. These simulation results contribute to a comprehensive understanding of the complex dynamic process of negative streamer discharge initiated by free metallic particles, providing essential insights for optimizing the design of electrical equipment and insulation systems.

To eliminate the influence of white noise in partial discharge (PD) detection, we propose a novel method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and approximate entropy (ApEn). By introducing adaptive noise into the decomposition process, CEEMDAN can effectively separate the original signal into different intrinsic mode functions (IMFs) with distinctive frequency scales. Afterward, the approximate entropy value of each IMF is calculated to eliminate noisy IMFs. Then, correlation coefficient analysis is employed to select useful IMFs that represent dominant PD features. Finally, real IMFs are extracted for PD signal reconstruction. On the basis of EEMD, CEEMDAN can further improve reconstruction accuracy and reduce iteration numbers to solve mode mixing problems. The results on both simulated and on-site PD signals show that the proposed method can be effectively employed for noise suppression and successfully extract PD pulses. The fusion algorithm combines the CEEMDAN algorithm and the ApEn algorithm with their respective advantages and has a better de-noising effect than EMD and EEMD.

Compared to pure SF₆ gas, the SF₆/CF₄ gas mixture exhibits certain advantages in reducing greenhouse effects, lowering the liquefaction temperature, and decreasing the sensitivity to non-uniform electric fields, demonstrating significant application potential in high-voltage electrical equipment. This study employs a two-dimensional plasma fluid model to investigate the partial discharge phenomena induced by free metallic particles in SF₆/CF₄ gas mixtures, analyzing the spatiotemporal evolution characteristics of key parameters, such as the charged particle density and axial electric field, under different mixing ratios. The simulation results show that there are two kinds of positive stream discharge phenomena, “continuous and decaying”, when the gas mixture ratio is 90%CF₄-10%SF₆ and 40%CF₄-60%SF₆. The proportion of CF₄ in the gas mixture will affect the spatial distribution of charged particles and the production and disappearance of electrons. When the proportion of CF₄ is 90%, the content of positive ions in the discharge channel is the highest, and the electric field formed by the positive space charge of CF₄⁺ in the stream head promotes the continuous propagation of the stream. As the concentration of CF₄ decreases, the main ionization reaction at the stream head shifts from CF₄ to SF₆, and a negative space charge region dominated by SF₆⁻ particles is also formed near the stream head, changing the electric field distribution near the flow head. The adhesion reaction rate is greater than the ionization reaction rate, resulting in the disappearance of electrons greater than the production, and the stream phenomenon tends to decay. These simulation results are helpful to understand the dynamic process of positive stream discharge induced by free metal particles in SF₆/CF₄ gas mixtures, and they provide a theoretical basis for better solutions to equipment damage caused by partial discharge.