Zhicheng Wu

In situ monitoring of oil‐dissolved gases without degassing in oil‐immersed equipment has become a promising approach. Herein, a direct sensing strategy utilising conductive metal–organic frameworks (cMOF) is proposed to develop a sensor capable of detecting multiple characteristic dissolved gases. The response and recovery times to the typical dissolved gas C ₂ H ₂ were 135 and 57 s, respectively. Simulated corona discharge experiments in oil demonstrated that the sensor could detect discharge‐generated gases within 10 min, confirming its potential for in situ defect monitoring. This technology provides support for preventive maintenance of power systems.

This study introduces an application of binocular stereo vision technology to achieve high‐resolution 3D visualisation of submillimeter discharge channels. The proposed method can capture the depth information of weak luminous discharges and provide 3D discharge trajectories, providing new insights into the discharge mechanism. The camera parameters are selected by a multi‐objective optimisation algorithm and calibrated using a micro‐chessboard, thus addressing the complex calibration challenges associated with imaging microscopic objects. The brightness threshold‐based point cloud filtering algorithm developed for this study improves the imaging quality of luminous channels under low‐light conditions. Experimental validation involving 3D reconstruction of complex branched discharge channels in SF ₆ /N ₂ mixtures reveals the key characteristics of the leader stepping mechanism. The accuracy and feasibility of the proposed method lay a solid foundation for future studies of discharge phenomena and the development of physical models of low‐probability breakdown events.

Acoustic cameras are widely used for the non-contact measurement of sound-source distributions. In practice, beamforming maps are often degraded by the broadening of the point spread function (PSF) and by sidelobe artifacts. Although the Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) can improve spatial resolution, its computational cost and parameter sensitivity limit its use in real-time applications. Existing unrolled networks usually replace the proximal step with a generic convolutional neural network (CNN), but do not explicitly describe the inter-grid coupling introduced by the PSF. In this paper, a PSF-coupled prior-guided deep unrolling network, termed PG-DFNet, is proposed for real-time acoustic source measurement. A competition prior is constructed from the normalized PSF coupling matrix by comparing the external sidelobe leakage received at each grid point with its normalized local intensity. This prior is updated at each stage and introduced into the proximal module together with adaptive PSF-width information and coordinate features, so that the shrinkage process can exploit structured coupling information. The proposed method preserves the data-consistency structure of the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) while improving artifact suppression. Results obtained from simulated data and real measurements with a 64-channel microphone array show that PG-DFNet achieves higher energy concentration, lower sidelobe levels, and more accurate localization than conventional methods and the baseline unrolled network, while retaining real-time inference capability.

The acoustic wave from bubble discharge in oil paper insulation can provide critical diagnostic information for oil–immersed transformer, yet, the generation mechanism of acoustic characteristics remains unclear. This study found that the bubble discharge in oil paper insulation exhibit a distinct dual–frequency acoustic emission characteristic by using a liquid–coupled broadband acoustic sensing method. Dual–frequency acoustic emission refers to acoustic wave comprising dominant low frequency wave and minor high frequency component. A mapping relationship where the low frequency component of acoustic wave excited by bubble discharge is inversely proportional to the bubble radius and positively correlated with the electric field is obtained, confirming that the low frequency component originates from bubble pulsation driven by internal discharge. The peak pressure of high frequency component of acoustic wave is positively correlated with the discharge energy, whereas the equivalent frequency follows an inverse power law relationship with the discharge energy, indicating that the high frequency component originates from the rapid conversion of discharge energy into acoustic energy. Based on the generation mechanism of dual–frequency acoustic emission waves, a method is proposed to estimate the bubble size by low frequency component of acoustic wave and the discharge energy by high frequency component. This work reveals the physical mechanism underlying dual–frequency acoustic emission from bubble discharge and realizes the evaluation of bubble discharge through acoustic wave frequency, which can provide valuable support for discharge detection in oil–immersed transformer.

Photoacoustic spectroscopy is a promising method for detecting dissolved acetylene (C₂H₂) in transformer oil, facilitating early fault diagnosis in power transformers. However, temperature variations significantly influence the resonance frequency of the photoacoustic cell, potentially reducing detection accuracy. This study investigates the temperature effects on the first-order longitudinal acoustic mode of a resonant photoacoustic cell using finite element simulations with thermo-viscous acoustics. The results show that as the temperature increases, the resonant frequency increases linearly and the sound pressure amplitude decreases, consistent with analytical models. To enhance system robustness, a perturbation observation method is proposed, treating operating frequency as the independent variable and acoustic pressure as the dependent variable. Time-domain simulations validate its effectiveness in tracking resonance frequency shifts under varying temperatures, ensuring reliable detection. Future work should focus on improving frequency resolution, noise filtering, and adaptive step-size optimization for practical applications.

With the increasing operational frequencies and miniaturization of electronic devices and integrated circuits, epoxy (EP) composites for electronic packaging face the challenge of achieving multifunctional performance requirements, including microwave absorption, superior thermal conductivity (TC), and high dielectric strength. This work develops a novel strategy of tailoring the interfacial sp²/sp³ hybridization ratio to resolve the trilemma among multifunctional performance enhancements. Leveraging the intrinsic high TC and dielectric strength of diamond, combined with the tunable sp²/sp³-hybridized structure of diamond-like carbon (DLC), the fabricated Diamond@DLC/EP composites exhibit outstanding multifunctional performance. The high sp²/sp³ hybridization ratio structure enhances impedance matching and interfacial charge dissipation, resulting in a minimum reflection loss of -26.66 dB and an effective absorption bandwidth of 6.1 GHz for composites. Concurrently, the tailored sp²/sp³-hybridized structure endows the filler-matrix interface with a more gradual modulus gradient transition and reduced interfacial thermal resistance. Through the mitigation of interfacial defects and the reduction of phonon scattering, the composites achieve a breakdown strength of 66.71 V·μm^-1 and an enhanced TC of 1.15 W·m^-1·K^-1. This approach of tailoring the interfacial sp²/sp³-hybridized structure for the synergistic enhancement of multiple properties presents a promising design strategy for next-generation electronic packaging materials.