Topological metamaterial has been a research hotpot in both physics and engineering due to its unique ability of wave manipulation. The topological interface state, which can efficiently and robustly centralize the elastic wave energy, is promising to attain high-performance energy harvesting. Since most of environmental vibration energy is in low frequency range, the interface state is required to be designed at subwavelength range. To this end, this paper developed a topological metamaterial beam with local resonators and studied its energy-harvesting performance. First, the unit cell of this topological metamaterial beam consists of a host beam with two pairs of parasitic beams with tip mass. Then, the band structure and topological features are determined. It is revealed that by tuning the distance between these two pairs of parasitic beams, band inversion where topological features inverse can be obtained. Then, two sub-chains, their design based on two topologically distinct unit cells, are assembled together with a piezoelectric transducer placed at the conjunction, yielding the locally resonant, topological, metamaterial, beam-based piezoelectric energy harvester. After that, its transmittance property and output power were obtained by using the frequency domain analysis of COMSOL Multiphysics. It is clear that the subwavelength interface state is obtained at the band-folding bandgap. Meanwhile, in the interface state, elastic wave energy is successfully centralized at the conjunction. From the response distribution, it is found that the maximum response takes place on the parasitic beam rather than the host beam. Therefore, the piezoelectric transducer is recommended to be placed on the parasitic beam rather than host beam. Finally, the robustness of the topological interface state and its potential advantages on energy harvesting were studied by introducing a local defect. It is clear that in the interface state, the maximum response is always located at the conjunction regardless of the defect degree and location. In other words, the piezoelectric transducer placed at the conjunction can maintain a stable and high-efficiency output power in the interface state, which makes the whole system very reliable in practical implementation.

Gas Insulated Switchgear (GIS) is a type of critical substation equipment in the power system, and its safe and stable operation is of great significance for ensuring the reliability of power system operation. To accurately identify partial discharge in GIS, this paper proposes an acoustic identification method based on improved mel frequency cepstral coefficients (MFCC) and dung beetle algorithm optimized random forest (DBO-RF) based on the ultrasonic detection method. Firstly, three types of typical GIS partial discharge defects, namely free metal particles, suspended potential, and surface discharge, were designed and constructed. Secondly, wavelet denoising was used to weaken the influence of noise on ultrasonic signals, and conventional, first-order, and second-order differential MFCC feature parameters were extracted, followed by principal component analysis for dimensionality reduction optimization. Finally, the feature parameters after dimensionality reduction optimization were input into the DBO-RF model for fault identification. The results show that this method can accurately identify partial discharge of typical GIS defects, with a recognition accuracy reaching 92.2%. The research results can provide a basis for GIS insulation fault detection and diagnosis.

In the wireless charging process of electric vehicles, unmanned aerial vehicles (UAVs), inspection robots and other electrical equipment, coil misalignment is inevitable due to human factors, external factors such as airflow during landing and other positioning problems, which severely limits its application. Accurate localization of the receiver coil can effectively reduce or even avoid the misalignment, but the traditional localization techniques may not be suitable for the complex electromagnetic environment of wireless charging system. In this paper, a receiver localization method based on mutual inductance disturbance for wireless power transfer (WPT) system with a relay coil is proposed. This method can achieve two-dimensional (2-D) localization of the receiver coil, and it will be more effective for high-temperature superconducting (HTS) WPT system with larger transmission power. The simulation and experiment are carried out to locate the receiver coil, and the results verify the feasibility of the proposed method.

Power transformers, as critical components in regional power distribution and transmission systems, require early fault detection to ensure system reliability. This paper presents a scalable design capable of rapidly simulating winding faults in experimental transformers. By diagnosing three-phase transformer winding short-circuit faults using oscillatory shock voltages and numerical statistical methods, the relationship between the transfer function and winding short-circuit faults is investigated. The experimental results show that winding short-circuit faults cause significant changes in the transfer function curve. By analyzing transfer function variations across different phases, the location of a fault can be effectively determined. Furthermore, the correlation coefficient and absolute logarithmic deviation provide a clear indication of the fault severity. The transfer function of the high-voltage phase-to-phase is particularly sensitive to winding short-circuit faults. In non-fault phases, after the application of damped oscillatory waves, the transfer function correlation coefficient becomes negative and the absolute logarithmic deviation increases linearly with fault severity. These findings provide a rapid diagnostic solution for determining both the faulty phase and the severity of damage in three-phase transformer winding short-circuit faults.

In this work, a self-powered vibration sensing system is proposed, based on a spatial magnetic field energy harvester, a duty-cycled circuit module, a piezoresistive graphene-based vibration sensor, and a wireless communication unit. The energy harvester is capable of generating an output power of 729 μW under a magnetic field excitation of 0.11 mT at 50 Hz. The duty-cycled circuit module enables closed-loop self-powered operation of the sensing system by efficient power storage and periodic measurement, and LoRa wireless transmission. The graphene-based sensor exhibits stable low-frequency vibration responses and good linearity and can capture composite vibration signals containing 4 Hz and 50 Hz components. These results indicate the potential of the proposed system for future transmission-line vibration sensing applications.