When the power converter connects to the high-frequency transformer breaks through the bottleneck and reaches a frequency of 100 kHz or even higher, the high-frequency transformer’s inter-turn insulation faces more serious high-frequency discharge and high-temperature problems. In order to improve the service performance of oil-immersed high-frequency transformer insulation paper, composite K-BNNS particles are prepared by ultrasonic stripping, heat treatment, and thermomagnetic stirring. Then, K-BNNS particles are mixed with PMIA (polymeric m-phenylenediamine solution) slurry to produce composite aramid paper. And the effects of K-BNNS particles with different contents on the thermal conductivity, dielectric properties, partial discharge properties, and mechanical properties of aramid paper are explored. It can be found that, when the addition of composite particles (K-BNNS) is 10%, the comprehensive performance of composite aramid paper is the best. Compared with Nomex paper, the in-plane and through-plane thermal conductivity of composite insulating paper F-10 increased by 668.33% and 760.66%, respectively. Moreover, the high-frequency breakdown voltage increased by 48.73% and the tensile strength increased by 2.49%. The main reason is that the composite particles form a complete thermal conductive network in the aramid paper matrix and a large number of hydrogen bonds with the matrix, which enhances the internal interface bonding force of the material and changes the charge transport mechanism.

This paper presents a novel Proportional Damping Injection (P + d) control scheme that incorporates a damping regulation strategy and an adaptive method for networked telerobotic systems. Unlike the traditional P + d controller with a fixed damping coefficient, the proposed approach includes a dynamic damping adjuster, designed based on position error, to enhance the position tracking speed and improve the system robustness. To address uncertainties in dynamic models and external forces, Radial Basis Function (RBF) neural networks and an adaptive strategy are employed for dynamic estimation. The closed-loop stability of the teleoperation system was rigorously established using the Lyapunov–Krasovskii method, and the relationship between the controller gains and communication delay boundaries was explicitly derived. Finally, simulations and experimental results validated the system’s stability and effectiveness, demonstrating the advantages of the proposed controller.

Existing studies have demonstrated that high-frequency discharge, thermal effect, and charge transport mechanism are the primary causes of high-frequency insulation failure, yet it remains unclear which mechanism plays the dominant role. Therefore, this paper establishes an experimental and simulation platform for partial discharge (PD) in inter-turn insulation under high-frequency (HF) square-wave voltage to investigate the damage mechanism of inter-turn insulation induced by high-frequency electro-thermal coupling. Experimental results show that below 10 kHz, the PD amplitude changes significantly while the temperature rise is relatively gentle, and the failure of HF transformer inter-turn insulation is mainly attributed to the coupling effect of HF PD and thermal effects. Above 10 kHz, the PD amplitude exhibits negligible variation whereas the temperature rises sharply. Notably, the inter-turn insulation breaks down rapidly with an extremely short time to breakdown at 30 kHz, indicating that high-frequency thermal effect becomes the dominant factor. The electric field acts in synergy with the thermal effect to accelerate the degradation of Nomex paper, thereby further promoting the thermal degradation and premature breakdown of the insulation. The findings of this study provide a solid theoretical basis for the life assessment and multi-physics modeling of HF transformer inter-turn insulation.

To address the issues of overlap between high-frequency power supply background noise and partial discharge signals, the reliance on empirical determination of optimization parameters in existing variational mode decomposition (VMD) algorithms, and the lengthy optimization time of other intelligent algorithms, a high-frequency partial discharge signal denoising method based on Catch Fish Optimization Algorithm-variational mode decomposition (CFOA-VMD) combined with multiscale wavelet thresholding is proposed. First, the characteristics of the high-frequency power supply background noise are analyzed using time-frequency domain methods; next, CFOA is employed to optimize the VMD parameters and perform signal decomposition; then, kurtosis values of each mode component are calculated to distinguish noise from effective signals; subsequently, multiscale wavelet thresholding is applied for secondary denoising of the retained effective components; finally, the denoised partial discharge signal is reconstructed. Simulation and experimental comparisons demonstrate that the proposed method effectively suppresses high-frequency noise in partial discharge signals, improving the signal-to-noise ratio by 23.7%, increasing the noise rejection ratio by 10%, and reducing denoising time by 80%. This research holds significant engineering application value in the field of on-site high-frequency partial discharge noise detection and elimination.