Insulation Condition Research Articles

Justification of choice of methods for diagnostics of insulation condition of electrical machines of electric railway stock

Justification of choice of methods for diagnostics of insulation condition of electrical machines of electric railway stock

Symmetry, topology, and geometry: The many faces of the topological magnetoelectric effect

A delicate tension complicates the relationship between the topological magnetoelectric effect (TME) in three-dimensional (3D) Z2 topological insulators (TIs) and time-reversal symmetry (TRS). TRS underlies a particular Z2 topological classification of the electronic ground state of crystalline band insulators and the associated quantization of the magnetoelectric response coefficient calculated using bulk linear-response theory but, according to standard symmetry arguments, simultaneously forbids a nonzero magnetoelectric coefficient in any physical finite-size system. This contrast between theories of magnetoelectric response in formal bulk models and in real finite-sized materials originates from the distinct approaches required to introduce notions of (electronic) polarization and orbital magnetization in these fundamentally different environments. In this work we argue for a modified interpretation of the bulk linear-response calculations in nonmagnetic Z2 TIs that is more plainly consistent with TRS and use this interpretation to discuss the effect's observation—still absent over a decade after its prediction. Our analysis is reinforced by microscopic bulk and thin-film calculations carried out using a simplified but still realistic effective model for the well established V2VI3 [V=(Sb,Bi) and VI=(Se,Te)] family of nonmagnetic Z2 TIs. When a uniform dc magnetic field is included in this model, the anomalous n=0 Landau levels (LLs) play the central role, both in thin films and in bulk. In the former case, only the n=0 LL eigenfunctions can support a dipole moment, which vanishes if there are no magnetic surface dopants and is quantized in the thick-film limit if magnetic dopants at the top and bottom surfaces have opposite orientation. In the latter case, the Hamiltonian projected into the n=0 LL subspace is a one-dimensional Su-Schrieffer-Heeger model with ground-state polarization that is quantized in accordance with the bulk linear-response coefficient calculated for (a lattice regularization of) the starting 3D model. Motivated by analytical results, we conjecture a type of microscopic bulk-boundary correspondence: a bulk insulator with (generalized) TRS supports a magnetoelectric coefficient that is purely itinerant (which is generically related to the geometry of the ground state) if and only if magnetic surface dopants are required for the TME to manifest in finite samples thereof. We conclude that in nonmagnetic Z2 TIs the TME is activated by magnetic surface dopants, that the charge-density response to a uniform dc magnetic field is localized at the surface and specified by the configuration of those dopants, and that the TME is qualitatively less robust against disorder than the integer quantum Hall effect. Published by the American Physical Society 2024

First principles prediction of novel quantum topological insulator state in two-dimensional XMg2Bi2 (X=Eu/Yb)

Topological insulator (TIs), a novel quantum state of materials, has a lot of significance in the development of low-power electronic equipments as the conducting edge states display exceptional endurance against back-scattering. The absence of suitable materials with high fabrication feasibility and significant nontrivial bandgap, is now the biggest hurdle in their potential applications in devices. Here, we illustrate using first principles density functional calculations that the quintuplet layers of EuMg2Bi2 and YbMg2Bi2 crystals are potential two-dimensional TIs with a sizeable nontrivial gaps of 72 meV and 147 meV respectively. Dynamical stability of these quintuplet layers of EuMg2Bi2 and YbMg2Bi2 is confirmed by our phonon calculations. The weakly coupled layered structure of parent compounds makes it possible for simple exfoliation from a three-dimensional structure. We observed gapless edge states inside the bulk band gap in both the systems which indicate their TI nature. Further, we observed the anomalous and spin Hall conductivities to be quantized in two dimensional EuMg2Bi2 and YbMg2Bi2 respectively. Our findings predict two viable candidate materials as two dimensional quantum TIs which can be explored by future experimental investigations and possible applications of quantized spin and anomalous Hall conductance in spintronics.

Evolution of an Overlapped Bandgap and Topological Flat Bands in a Higher‐Order Valley Photonic Insulator Based on Dendritic Structure

AbstractRobust edge states and corner states in photonic topological insulators provide effective ways to manipulate the propagation of electromagnetic waves. Bandgaps of the previously reported photonic topological insulators are independent of each other. In this paper, a higher‐order valley photonic insulator composed of arrays of dendritic structure is designed. The band structure shows an overlapped bandgap is observed, and the overlapped bandgap divides the band structure into three bandgaps. The evolution of the overlapped bandgap is investigated by changing the geometric parameters and increasing the fractal to break the C3v symmetry drastically. Besides, it is notable that the band structure of the proposed valley photonic insulator is flat bands. It is demonstrated that undistorted transmission can be observed as a plane electromagnetic wave transmits through the proposed valley photonic insulator. The interface consisting of two valley photonic structures with distinct topological nontrivial phases is constructed. Edge states and corner states with strong energy localization are obtained in multi‐band frequencies. Remarkably, two triangular structures with different Wannier center configurations both have corner states in the same bandgap, which does not obey the valley selectivity. The phenomenon is caused by the weak valley locking property due to the overlapped bandgap. The proposed valley photonic insulators are expected to benefit applications in optical devices such as topological lasers.

Design of an ultra-wideband and switchable VO2-based microwave absorber

We propose a design of an ultra-wideband microwave metamaterial absorber using Vanadium dioxide (VO2) based on a dual-layer structure. The ultra-wideband absorption performance of the proposed structure can switch by using the phase transition of VO2. When the VO2 is in the insulator state, the proposed absorber achieves an ultra-wideband absorption response in the range of 3.7–22.5 GHz with an absorptivity higher than 0.9 and a relative bandwidth of 143.5% at normal incidence, which covers the entire bands from the C to Ku. The designed absorber is polarization insensitive and wide incident angle stable for both transverse electric (TE) and transverse magnetic (TM) modes. Owing to the outstanding merits of absorption performance and frequency-tunable capability, our design structure can be suitable for many promising applications in the microwave range, such as smart radar, camouflage and stealth radome technology.

Chern Insulator States with Tunable Chern Numbers in a Graphene Moiré Superlattice.

Moiré superlattices, constituted by two-dimensional materials, demonstrate a variety of strongly correlated and topological phenomena including correlated insulators, superconductivity, and integer/fractional Chern insulators. In the realm of topological nontrivial Chern insulators within specific moiré superlattices, previous studies usually observe a single Chern number at a given filling factor in a device. Here we present the observation of gate-tunable Chern numbers within the Chern insulator state of an ABC-stacked trilayer graphene/hexagonal boron nitride moiré superlattice device. Near quarter filling, the moiré superlattice exhibits spontaneous valley polarization and distinct ferromagnetism associated with the Chern insulator states over a range of the displacement field. Surprisingly we find a transition of the Chern number from C = 3 to 4 as the displacement field is increased. Our observation of gate-tunable correlated Chern insulators suggests new ways to control and manipulate topological states in a moiré superlattice device.

A new detection method for the ageing state of composite insulators based on spectral–spatial feature fusion

Composite insulators are integral to the power grid, providing electrical insulation and mechanical support. However, their prolonged exposure to outdoor conditions renders them vulnerable to ageing. This can result in flashovers and economic losses. Hyperspectral imaging (HSI) has been identified as a promising non-contact detection method to effectively assess the microscopic ageing status of these insulators’ surfaces. This study involved conducting artificial accelerated ageing experiments to mimic extended outdoor operational conditions. The static contact angle of ageing silicone rubber samples served as the basis for ageing classification. High-resolution HSIs of samples at various ageing stages were obtained, covering wavelengths from 400 nm to 1040 nm. Singular spectrum analysis was applied to denoise spectral and spatial domains, eliminating environmental and equipment-related noise effectively. Additionally, a convolutional neural network (CNN) was utilised to extract deep features from the spectral domain and combine them with spatial domain features, thus reducing dimensionality. The resulting fused spatial–spectral features were classified using a support vector machine. The joint denoising and feature fusion in this study’s spectral–spatial domain resulted in a notable improvement of 34.9 % in overall accuracy, achieving a score of 98.3 %. This approach exhibited superior performance, particularly in evaluating severely aged samples. The proposed approach enhances the accuracy in assessing the ageing status of composite insulators and enables pixel-level visualisation of ageing distribution. This assists in guiding the design of insulators’ shapes and materials for various environmental conditions. Moreover, this method is potentially applicable in detecting ageing in other electrical equipment.

Two-step machine learning-assisted label-free surface-enhanced Raman spectroscopy for reliable prediction of dissolved furfural in transformer oil

Accurate detection of dissolved furfural in transformer oil is crucial for real-time monitoring of the aging state of transformer oil-paper insulation. While label-free surface-enhanced Raman spectroscopy (SERS) has demonstrated high sensitivity for dissolved furfural in transformer oil, challenges persist due to poor substrate consistency and low quantitative reliability. Herein, machine learning (ML) algorithms were employed in both substrate fabrication and spectral analysis of label-free SERS. Initially, a high-consistency Ag@Au substrate was prepared through a combination of experiments, particle swarm optimization-neural network (PSO-NN), and a hybrid strategy of particle swarm optimization and genetic algorithm (Hybrid PSO-GA). Notably, a two-step ML framework was proposed, whose operational mechanism is classification followed by quantification. The framework adopts a hierarchical modeling strategy, incorporating simple algorithms such as kernel support vector machine (Kernel-SVM), k-nearest neighbors (KNN), etc., to independently establish lightweight regression models on each cluster, which allows each model to focus more effectively on fitting the data within its cluster. The classification model achieved an accuracy of 100%, while the regression models exhibited an average correlation coefficient (R2) of 0.9953 and the root mean square errors (RMSE) consistently below 10-2. Thus, this ML framework emerges as a rapid and reliable method for detecting dissolved furfural in transformer oil, even in the presence of different interfering substances, which may also have potentiality for other complex mixture monitoring systems.

Fractal Analysis of Time Domain Dielectric Response to Reduce Complexity of Insulation Condition Diagnosis Methodology

Fractal Analysis of Time Domain Dielectric Response to Reduce Complexity of Insulation Condition Diagnosis Methodology

Accurate Identification of Partial Discharge Signals in Cable Terminations of High-Speed Electric Multiple Unit Using Wavelet Transform and Deep Belief Network

Cable termination serves as a crucial carrier for high-speed train power transmission and a weak part of the cable insulation system. Partial discharge detection plays a significant role in evaluating insulation status. However, field testing signals are often contaminated by external corona interference, which affects detection accuracy. This paper proposes a classification model based on wavelet transform (WT) and deep belief network (DBN) to accurately and rapidly identify corona discharge in the partial discharge signals of vehicle-mounted cable terminals. The method utilizes wavelet transform for noise reduction, employing the sigmoid activation function and analyzing the impact of WT on DBN classification performance. Research indicates that this method can achieve an accuracy of over 89% even with limited training samples. Finally, the reliability of the proposed classification model is verified using measured mixed signals.

PMSNet: Multiscale Partial-Discharge Signal Feature Recognition Model via a Spatial Interaction Attention Mechanism.

Partial discharge (PD) is a localized discharge phenomenon in the insulator of electrical equipment resulting from the electric field strength exceeding the local dielectric breakdown electric field. Partial-discharge signal identification is an important means of assessing the insulation status of electrical equipment and critical to the safe operation of electrical equipment. The identification effect of traditional methods is not ideal because the PD signal collected is subject to strong noise interference. To overcome noise interference, quickly and accurately identify PD signals, and eliminate potential safety hazards, this study proposes a PD signal identification method based on multiscale feature fusion. The method improves identification efficiency through the multiscale feature fusion and feature aggregation of phase-resolved partial-discharge (PRPD) diagrams by using PMSNet. The whole network consists of three parts: a CNN backbone composed of a multiscale feature fusion pyramid, a down-sampling feature enhancement (DSFB) module for each layer of the pyramid to acquire features from different layers, a Transformer encoder module dominated by a spatial interaction-attention mechanism to enhance subspace feature interactions, a final categorized feature recognition method for the PRPD maps and a final classification feature generation module (F-Collect). PMSNet improves recognition accuracy by 10% compared with traditional high-frequency current detection methods and current pulse detection methods. On the PRPD dataset, the validation accuracy of PMSNet is above 80%, the validation loss is about 0.3%, and the training accuracy exceeds 85%. Experimental results show that the use of PMSNet can greatly improve the recognition accuracy and robustness of PD signals and has good practicality and application prospects.

Emerging topological states in EuMn2Bi2: A first principles prediction

New materials with magnetic order driven topological phases are hugely sought after for their immense application potential. In this work, we propose a new compound EuMn2Bi2 from our first principles density functional theory calculations to host novel topological phases such as Dirac/Weyl semimetal and topological insulator in its different magnetic states which are energetically close to one another. The new compound EuMn2Bi2 is found to be dynamically stable from our phonon calculations supporting its experimental preparation in future. By comparing the total energies of various possible magnetic structures of EuMn2Bi2, we identified the ground state. The magnetic ground state is found to be a normal insulator with tiny band gap which is an order of magnitude less than the same in another well studied sister compound EuMn2As2. However, there exist other magnetic states energetically very close to the ground state in EuMn2Bi2 which display remarkable non-trivial band topology such as Dirac/Weyl points close to the Fermi level and topological insulator state driven by magnetic order which is not observed in EuMn2As2. The energetic proximity of these magnetic order driven topological phases makes them tunable via external handle such as magnetic field indicating that the proposed new material EuMn2Bi2 would be a very versatile magnetic topological material if prepared experimentally in future.

Surface terminations control charge transfer from bulk to surface states in topological insulators

Topological insulators (TI) hold significant potential for various electronic and optoelectronic devices that rely on the Dirac surface state (DSS), including spintronic and thermoelectric devices, as well as terahertz detectors. The behavior of electrons within the DSS plays a pivotal role in the performance of such devices. It is expected that DSS appear on a surface of three dimensional(3D) TI by mechanical exfoliation. However, it is not always the case that the surface terminating atomic configuration and corresponding band structures are homogeneous. In order to investigate the impact of surface terminating atomic configurations on electron dynamics, we meticulously examined the electron dynamics at the exfoliated surface of a crystalline 3D TI (Bi2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document}Se3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_3$$\\end{document}) with time, space, and energy resolutions. Based on our comprehensive band structure calculations, we found that on one of the Se-terminated surfaces, DSS is located within the bulk band gap, with no other surface states manifesting within this region. On this particular surface, photoexcited electrons within the conduction band effectively relax towards DSS and tend to linger at the Dirac point for extended periods of time. It is worth emphasizing that these distinct characteristics of DSS are exclusively observed on this particular surface.

Simple model for the gap in the surface states of the antiferromagnetic topological insulator MnBi[formula omitted]Te[formula omitted]

We study the influence of the antiferromagnetic order on the surface states of topological insulators. We derive an effective Hamiltonian for these states, taking into account the spatial structure of the antiferromagnetic order. We obtain a typical (gapless) Dirac Hamiltonian for the surface states when the surface of the sample is not perturbed. Gapless spectrum is protected by the combination of time-reversal and half-translation symmetries. However, a shift in the chemical potential of the surface layer opens a gap in the spectrum away from the Fermi energy. Such a gap occurs only in systems with finite antiferromagnetic order. We observe that the system topology remains unchanged even for large values of the disorder. We calculate the spectrum using the tight-binding model with different boundary condition. In this case we get a gap in the spectrum of the surface states. This discrepancy arises due to the violation of the combined time-reversal symmetry. We compare our results with experiments and density functional theory calculations.

Improved Common-Mode Leakage Current Measurement Method for Insulation Condition Monitoring in Distribution Grids

Common-mode (CM) leakage current is an essential insulation indicator for condition monitoring in distribution grids. However, online measurement of CM leakage current is a difficult task in the industry due to the disturbances of far larger load currents. To address this challenge, a novel CM leakage current measurement method based on multi-layer magnetic shield has been proposed in this paper. The analytical solution for the magnetic field around the shield is firstly derived and validated by finite element analysis. Comprehensive comparison with previous single-layer shield design is then conducted for a typical industrial case, proving that an improvement of about 46 dB can be achieved for CM leakage current measurement by the novel design. A sensor prototype has also been developed with optimized parameters and validated by experiments. The effectiveness of the proposed method is proved, with minor CM leakage current accurately extracted from load currents which are 3000 times larger.

Simulation analysis of thermal insulation performance of diesel engine piston based on PEO and La2Zr2O7 thermal barrier coating

In this research, we explored the application of ‘thermal swing’ thermal barrier coatings (TBCs) in diesel engines, aiming to surpass the performance of conventional TBCs. Traditional TBCs often suffer from limitations like consistently high surface temperatures and a delayed response to sudden variations in cylinder temperatures, which adversely impact engine efficiency. To overcome these challenges, plasma electrolytic oxidation (PEO) technology was employed to engineer TBCs with the sought-after ‘thermal swing’ feature. Comparative simulations were conducted to assess the thermal characteristics of PEO coatings on pistons, in contrast to standard La2Zr2O7 coatings. The steady-state thermal analysis revealed that PEO coatings maintained a lower peak temperature compared to La2Zr2O7 coatings under similar thermal insulation conditions, indicating a superior ability of the PEO coatings in heat dissipation and in sustaining lower surface temperatures.In the transient thermal analysis, focusing on temporal temperature variations, the PEO coatings exhibited a markedly quicker and more robust response to cylinder temperature fluctuations. This indicates that PEO coatings are highly effective in adapting swiftly to temperature changes, thereby contributing to enhanced engine performance. Additionally, the PEO coating demonstrated a notable reduction in the end temperature (TE), which is crucial for mitigating the heating effect on intake gas, in comparison to La2Zr2O7 coatings with equivalent thermal insulation properties. However, it was observed that this advantage significantly decreased when the PEO coating thickness surpassed 0.3 mm. Drawing from these observations, it is concluded that PEO coatings hold several thermal advantages over La2Zr2O7 coatings, particularly in terms of thermal load management and responsiveness to in-cylinder temperature shifts. These benefits are most pronounced when the PEO coating maintains a thickness below 0.3 mm.

Monitoring and Leak Diagnostics of Sulfur Hexafluoride and Decomposition Gases from Power Equipment for the Reliability and Safety of Power Grid Operation

Sulfur hexafluoride (SF6) is a typical fluorine gas with excellent insulation and arc extinguishing properties that has been widely used in large-scale power equipment. The detection of SF6 gas in high-power electrical equipment is a necessary measure to ensure the reliability and safety of power grid operation. A failure of SF6 insulated electrical equipment, such as discharging or overheating conditions, can cause SF6 gas decomposition, resulting in various decomposition products. The decomposed gases inside the equipment decrease the insulating properties and are toxic. The leakage of SF6 can also decrease the insulating properties. Therefore, it is crucial to monitor the leakage of SF6 decomposed gases from electrical equipment. Quantitative testing of decomposition products allows us to assess the insulation state of the equipment, identify internal faults, and maintain the equipment. This review comprehensively introduces the decomposition formation mechanism of SF6 gas and the current detection technology of decomposition products from the aspects of principle and structure, materials, test effect, and practicability. Finally, the development trends of SF6 and decomposition gas detection technology for the reliability and safety of power grid operation are prospected.

Low-temperature magnetoresistance hysteresis in vanadium-doped Bi2−xTe2.4Se0.6 bulk topological insulators

Bi2−xTe2.4Se0.6 single crystals show gapless topological surface states, and doping (x) with vanadium allows to shift the chemical potential in the bulk bandgap. Accordingly, the resistivity, carrier density, and mobility are constant below 10 K, and the magnetoresistance shows weak antilocalization as expected for low-temperature transport properties dominated by gapless surface states of so-called three-dimensional topological insulators. However, the magnetoresistance also shows a hysteresis depending on the sweep rate and the magnetic field direction. Here, we provide evidence that such magnetoresistance hysteresis is enhanced if both three-dimensional bulk states and quasi-two-dimensional topological states contribute to the transport (x = 0 and 0.03), and it is mostly suppressed if the topological states govern transport (x = 0.015). It is proposed that the hysteresis in the magnetoresistance results from different spin-dependent scattering rates of the topological surface and bulk states. Generally, this observation is of relevance to the studies of topologically insulating materials in which both topological surface and bulk states exist.

Evidence of topological surface states with upward band bending in (Bi[formula omitted]Sb[formula omitted])[formula omitted]Te[formula omitted] topological insulator

Significant efforts have been put in the past to minimize the bulk conduction to probe the exotic surface states of topological insulators (TIs), nevertheless, the surface transport is usually hindered by the presence of bulk conduction. The identification and separation of the contribution of topological surface states (TSS) by electrical transport is important for understanding the unique properties of TIs and developing new electronic devices based on these materials. In this report we have studied Shubnikov-de Haas (SdH) oscillations, magneto-resistance (MR) and hall resistivity under high magnetic field in (Bi0.45Sb0.60)2Te3 single crystal grown by modified Bridgman method. Our results show the existence of SdH oscillations which arise from TSS. The obtained Fermi wave vector and Fermi velocity of surface charge carriers show a good agreement with those found by angle-resolved photoemission spectroscopy experiments. Two band model fit to hall resistivity confirms the high mobility of surface bands and low mobility of bulk bands. Band bending effect is investigated which exhibits a depletion of carriers from near by bulk towards the surface states resulting in an upward band bending. A large non-saturating MR (∼347)% is observed as a result of multichannel quantum coherent transport mechanism.

Research Progress and Prospect of Condition Assessment Techniques for Oil–Paper Insulation Used in Power Systems: A Review

Oil–paper insulation is the critical insulation element in the modern power system. Under a harsh operating environment, oil–paper insulation will deteriorate gradually, resulting in electrical accidents. Thus, it is important to evaluate and monitor the insulation state of oil–paper insulation. Firstly, this paper introduces the geometric structure and physical components of oil–paper insulation and shows the main reasons and forms of oil–paper insulation’s degradation. Then, this paper reviews the existing condition assessment techniques for oil–paper insulation, such as the dissolved gas ratio analysis, aging kinetic model, cellulose–water adsorption isotherm, oil–paper moisture balance curve, and dielectric response technique. Additionally, the advantages and limitations of the above condition assessment techniques are discussed. In particular, this paper highlights the dielectric response technique and introduces its evaluation principle in detail: (1) collecting the dielectric response data, (2) extracting the feature parameters from the collected dielectric response data, and (3) establishing the condition assessment models based on the extracted feature parameters and the machine learning techniques. Finally, two full potential studies are proposed, which research hotspots’ oil–paper insulation and the electrical–chemical joint evaluation technique. In summary, this paper concludes the principles, advantages and limitation of the existing condition assessment techniques for oil–paper insulation, and we put forward two potential research avenues.