The gas relay is a common non-electric protection device inside transformers, installed on the connecting pipeline between the transformer oil tank and the oil conservator. When the transformer malfunctions and the oil flow value reaches the heavy gas setting value of the gas relay, a heavy gas alarm is triggered. Therefore, accurately analyzing the heavy gas action characteristics and the setting value of the gas relay directly affects the accuracy of the heavy gas alarm. The BF(Bi-Float) type double float ball gas relay uses steady-state oil flow to calibrate the setting values of heavy gas action. In reality, transformer faults cause transient oil flow. To explore the relationship between the oil flow state and gas relay flow velocity setting values, a dynamic model of the heavy gas action process of BF type double float ball gas relay was first established, and the influence of the oil flow state on the gas relay baffle action process was analyzed. Then, a transient oil flow impact test bench was developed to experimentally study the heavy gas action characteristics of gas relays under different intensities of transient oil flow impact. Theoretical and experimental research results indicate that different oil flow impact states have a significant effect on the flow velocity setting values of gas relays. The flow velocity setting value of the BF type double float ball gas relay used in this study under transient oil flow impact is 0.8 m/s, which is lower than its factory flow velocity setting value of 1 m/s. These research results have positive significance for optimizing the performance of gas relays and improving the operational reliability of power transformers.

Taking a large single-phase generator transformer product as the research object, this paper applied the finite element simulation method to analyze the vibration characteristics of its core. Firstly, through the analysis of vibration theory, the vibration laws and characteristics of the core are clarified, and a three-dimensional equivalent model of the transformer is constructed. The B-H curve of the silicon steel sheet is measured through experiments and used for the assignment of the core material when calculating the electromagnetic field later. Then, based on the simulation calculation of multi-physical field coupling, the no-load current on the primary side, the distribution and variation characteristics of the magnetic field inside the core are solved and analyzed. On this basis, the sequential coupling method was adopted to solve the displacement distribution of the core vibration and the displacement changes at different position points and conduct a comparative analysis. Subsequently, the accuracy of the simulation calculation method was verified through the test of a small prototype. Finally, based on the comparison of the dry and wet modal simulation results, the impact of transformer oil on the vibration characteristics of the core was evaluated and analyzed. It can be seen from the analysis that the core vibration is generally more intense at the upper part and corners; the impact of the internal oil flow on the vibration of the body of large transformers is relatively complex and thus cannot be ignored.

amorphous alloy transformer has energy-saving advantages, but its magnetostrictive effect is higher than that of silicon steel transformer, causing severe vibration and noise, which makes it very easy for amorphous alloy debris to be produced, thereby leading to insulation faults. Additionally, transformer is important power equipment for power delivery. Therefore, in order to reflect the vibration information of the core under different external environments, an analysis model for the transmission of core vibration to the tank is established, to analyze the vibration characteristics of the tank of the amorphous alloy 3D wound core transformer under both insulating oil and non-insulating oil conditions. Firstly, to obtain fundamental magnetization and magnetostriction characteristics, a single-frame amorphous alloy three-dimensional wound (3D) core magnetic property testing platform is constructed. Subsequently, drawing on the principles of elastic mechanics, a magneto-mechanical coupled vibration model is established for amorphous alloy 3D wound core. Meanwhile, a vibration test platform is constructed to obtain the distribution trend of core vibration under different operating conditions, which the accuracy of the finite element model for core vibration is validated. Finally, the investigation is carried on a 50kVA amorphous alloy wound 3D transformer to evaluate tank's vibration characteristics under the conditions with and without insulating oil, obtaining vibration intensity and frequency distribution characteristics of the tank, and the accuracy of the tank's vibration characteristics is validated for transformer model. On this basis, the influence of insulating oil temperature on the tank's vibration characteristics is considered to reveal the relationship among the vibration characteristics of insulating oil, core, and tank. To break through the limitations of traditional electrical detection methods and provide a theoretical basis for the online fault diagnosis of core.

Accurate assessment of winding condition for power transformers is critical for ensuring the stable operation of modern power systems. Vibration signal has been regarded as an effective and promising evaluator for winding diagnosis. While on-line vibration monitoring offers the continuous, non-invasive and in-service assessment for winding condition, establishing precise correlations between the variable vibration patterns and specific winding condition remains challenging. To this end, an off-line vibration response analysis (VRA) technique was presented in the paper. Specifically, vibration frequency response (VFR) curves, indicating the winding response, were first obtained when the transformer was excited by the developed vibration response testing system, consisting of constant current variable-frequency power supply, intermediate transformer, accelerometers, data acquisition, control and analysis system. The VFR curves were then quantitatively and comprehensively described through four kinds of correlation indices. Finally, hierarchical integration strategy was proposed to aggregate those indices into quantitative criterion for condition assessment. The proposed method was validated on a real transformer under both normal and fault conditions, demonstrating superior performance. Notably, a 10% decrease in the evaluation criterion indicates an incipient winding looseness, while a reduction of 25% or more suggests severe looseness, prompting timely maintenance recommendations.

With the increase in voltage levels of power systems, converter transformers are more susceptible to internal high-energy arcing faults because of their compact structure, causing pressure to increase inside the tank and ultimately resulting in deflagration accidents. Conventional pressure relief devices (PRDs) suffer limitations in terms of response speed and pressure relief capacity, making them inadequate for severe arcing faults within converter transformers. In this context, a novel approach based on resistive-type superconducting fault current limiters (R-SFCLs) is proposed to suppress overpressure. Specifically, a coupled model is established, in which the magnetic field, electric circuit, arc nonlinear characteristics, R-SFCLs insertion, and fluid-structure interactions are integrated. Afterward, a corresponding numerical method is developed and implemented. Simulations performed involving an actual 500 kV converter transformer reveal that the deployment of R-SFCLs effectively limits the arc power and the released energy. Moreover, combined with PRDs operation, the proposed method significantly mitigates overpressure inside the tank. Compared with the scenario without R-SFCLs, the peak pressure is reduced by 21.1% under a severe interturn fault shorting 30% of the grid side winding, and this effect increases with increasing fault severity.

Tank vibrations of a power transformer, originating primarily from winding vibration and core vibration through mechanical coupling and fluid–structure interaction, are regarded as essential carrier signals for assessing the integrity of the winding. To improve the diagnostic accuracy of winding condition, this paper presents a vibration centroid-based diagnostic model that integrates feature fusion from vibration signals. According to the frequency spectrum of vibration signals obtained using Zoom-FFT, a set of new spatial vibration feature vectors—namely vibration centroid coordinates and Boyce-Clark shape index—were defined. This approach converts spatially distributed vibration signals into compact and discriminate indicators. A diagnostic model was subsequently constructed by integrating the grey wolf optimization (GWO) algorithm with the least squares support vector machine (LSSVM), ensuring that optimal classification performance was achieved. No-load, short-circuit, and load tests were made on a 35 kV-rated oil-immersed transformer. During the experiments, the transformer winding was divided into four categories: healthy condition, winding looseness, axial deformation, and radial deformation. The proposed GWO-LSSVM-based classifier was trained and tested using the defined vibration feature vectors. The results indicate that the proposed method achieves superior performance, with a recognition rate of 98.44%, and offers high efficiency.