This study presents an analysis of time-domain crosstalk between two parallel coaxial cables from 10 MHz − 1 GHz. Although such coupling has been extensively studied in the frequency domain, it is advantageous to evaluate the coupling in the time-domain for the analysis of signal integrity-related issues. The near-end crosstalk is modelled using one dimensional transmission line modelling (TLM) approach, which is validated against practical measurements and commercial simulation software. A prony approximation method and equivalent circuit approach were used to account for frequency-dependent parameters such as surface transfer impedance and skin effect in the TLM simulations.

A novel online hybrid resampling (HR) scheme based on the combination of residual and multinomial resampling schemes is proposed. It can be implemented within the framework of the sequential Monte Carlo-based inversion algorithm, also known as particle filter (PF). Based upon the degeneracy of each particle, the choice of best resampling scheme among both candidates is made at each instant iteratively. Consequently, the inversion performance of PF improves by reducing the computational complexity of the resampling scheme. The proposed online HR scheme is incorporated here within the framework of the PF-based inversion scheme once applied on nuclear power plant steam generator non-destructive testing measurement data. The promising results showcase the efficacy of the technique.

Traditional labour-intensive methods always suffer from time and frequency blurring and cross-term interference when detecting fault features from vibration signals and their time–frequency representation. Such methods need essential expertise and prior knowledge to identify features. Intelligent fault diagnosis methods based on deep learning have attracted great attention because of their ability to automatically learn the representative features in fault diagnosis. Therefore, a novel multi-object deep convolutional neural network (CNN) is proposed to diagnose the faults. In this method, time domain, frequency domain, and time–frequency data are organised as the hybrid multi-object input to avoid the shortcoming of the single type of data, which cannot reveal abundant information about amplitude and frequency in vibration signals. Deep CNN with four convolutional layers is constructed to intelligently learn the distinguished features. The adjacent convolutional layer is used to sensitively capture slight changes in the input data, and the other layers are used to extract and reduce the abundant features. Random forest is used to accurately classify the fault types. The vibration signal of cylinder rolling bearing and gearbox is used to validate the proposed method. The results are compared with those of other state-of-the-art methods to show the superior performance of the proposed method.

This study describes a low-cost sensor-based scheme for online moisture measurement in transformer oil. Considering a harsh environment, moisture measurement of oil at ppm level is challenging, so the sensor should be highly sensitive and thermally and chemically stable. The conventional methods are mostly offline, have long test times and are costly. A thin-film parallel plate capacitive moisture sensor has been fabricated using inexpensive materials to measure the moisture of fresh, aged and 0.5% water content oil samples. The moisture sensing film is highly hydrophilic and is made of alumina oxide, a very stable material. Experiments were conducted to determine the response parameters of the sensor in the presence of moist nitrogen gas, the concentration of which was measured by a commercial SHAW dew point meter. Experiments were also performed to measure the moisture of different oil samples in the laboratory. Results show that the output of the sensor is sensitive (6 pF/ppm moisture), has negligible hysteresis (∼1% at 1 kHz) and has fast response and recovery times (T _res = 70 s, T _rec = 170 s).

Clustering, an energy efficient approach is preferred in wireless sensor network due to the limited energy consumption of sensor nodes. Clustering saves energy as the communication is restricted to a few nodes, thereby increasing the network lifetime. Recently, an iterative linear regression-based clustering is proposed to improve the cluster quality in a wireless sensor network. The quality of clusters so obtained is evaluated through Matlab using the cluster validity analysis platform. However, the performance of the clusters so obtained using iterative linear regression in terms of energy efficiency is not dealt. Hence, an attempt is made to investigate the performance of the network through real time experiments. The network performances are studied in terms of intra-cluster and inter-cluster energy consumption, first node death, half node death and last node death. To prove the effectiveness of the proposed technique, it is compared with the standard k-means clustering algorithm. The results reveal that the clusters obtained using iterative linear regression is efficient in enhancing the lifetime of the wireless sensor network.

This study reports a modified AC standstill method (ACSM) for the axis inductances measurement of permanent magnet synchronous motors (PMSMs), which is free of locked tooling. Based on the voltage function, the axis inductances of a PMSM are derived from the ACSM under the two same phase (TSP) condition through the Laplace transform. The inductance values of the studied external rotor PMSM are measured by this reported TSP ACSM, which are also compared with the DC standstill and the previous ACSM tests. During the process of the TSP ACSM measurement, the voltage source inverter of the motor provides three phase excitation signals which can produce self-saturation and cross-saturation. The theoretical analysis and experimental measurement results validate the accuracy of this reported method.

In this study, the authors present the latest developments on the measurements for the shielding effectiveness (SE) of gaskets and materials in reverberation chambers (RCs). A variant method, where the insertion loss of the fixture is achieved from the SE of the fixture with no sample in the aperture is found; it is appropriate for gaskets and for any flat material having a sufficiently high reflectivity at least on one side. A simple and usable condition under which the simplest method for the SE measurements of gaskets and materials in RCs can be used is also given, as well as particular cases where it can be directly applied are shown. This method, whose applicability is enhanced in this study, can be used for gaskets and any flat sample. Such developments simplify measurement setup and associated procedures. Comparisons of results support the methods for the SE measurements of gaskets and material in RCs shown in this study.

A method combining the finite-element method (FEM) numerical calculation with machine learning is developed and used to calculate the eddy current losses of the rotor damping slot wedge of generator with different structures and electromagnetic properties. FEM simulation data is used as the input, and the stacking method is used to build the ensemble Gaussian process regression model for eddy current loss prediction to predict and analyse the calculation results. The error is tiny. The FEM results are highly consistent with the prediction data. As demonstrated by comparison experiments, the prediction accuracy of the stacking Gaussian process regression (SGPR) model is greater than that of other models. Therefore, the SGPR model provides a new auxiliary design method for large generators that can help improve generator design efficiency.

It is necessary to have a model to design magnetic gear (MG) optimally and to investigate the effective parameters on its performance. This study proposed a two-dimensional (2D) model to predict the magnetic components of coaxial MG (CMG). This model is based on the mesh analysis method considering core nonlinear B-H curve. In the proposed model, the radial and tangential components of flux densities, magnetic fluxes as well as the inner/outer rotor torque are estimated by extraction of the magnetic equivalent circuit (MEC). The effect of non-linear B-H magnetising curve is considered on the MEC model and it is compared with linear core (constant probability). Furthermore, the dynamic model of CMG is presented and its torque-angle curve and consequently its pull-out torque is obtained. To validate the proposed model, the 2D MEC model results are compared with results of finite element method analysis.

Electronic enclosures often require ventilation and electromagnetic shielding, which have conflicting design requirements. This study proposes a hybrid model, based on circuit model and full-wave method, for estimating the shielding effectiveness of empty metallic enclosures with ventilation apertures of arbitrary shape or aperture arrays of arbitrary distribution on one side of the enclosures. Such perforated enclosures are split into a perforated plate and semi-enclosed waveguide that is shorted at the end. The S parameters of the perforated plate are calculated by a full-wave method and used to estimate the aperture impedance. An equivalent circuit model of a perforated enclosure is established, considering arbitrarily-positioned apertures, arbitrarily-chosen observation points, and higher-order modes. A modified plane wave decomposition technique is adopted to solve the problem of plane waves with arbitrary incident and polarisation directions. In particular, the effects of the electric field components perpendicular to the perforated plate are considered. The efficiency and accuracy of the hybrid model are evaluated by the transmission line matrix method, finite integration technique, experimental observations and existing circuit models. The hybrid model requires much less simulation time than pure full-wave methods such as the transmission line matrix method.

Layered dielectric materials are currently in use for electric field stress control, but are limited by charge accumulation at the dielectric–dielectric interfaces. The current work uses micrometric particles to modify the effective permittivity of epoxy resin samples. Two broad kinds of samples are considered: discrete layered material (DLM) samples and functionally graded material (FGM) samples. DLM samples are obtained by bonding layers of epoxy resin with different filler loadings such that abrupt variation in permittivity might occur along the sample thickness. FGM specimens are prepared by hot pressing a comparatively large number of very thin layers of micro-filled epoxy resin with very small differences in permittivity one over the other, thus creating a gradual spatial permittivity gradation. Dielectric properties of FGM and DLM specimens are compared in this study. Space charge accumulation is studied using the pulsed electroacoustic method; the accumulated charge density is seen to be lower in FGM. The uniformity of electric field distribution under applied electric stress is computed, and the field utilisation factor in FGM is seen to have a higher value. Also, the dissipation factor is lower and the short-term breakdown strength is higher in FGM than in DLM samples, providing reason to prefer FGM for insulation to control electric stress.

The synthetic aperture radar (SAR) imaging method has been recently proposed for online radial deformation detection of high voltage transformer windings. In this method, electromagnetic waves should be transmitted toward the transformer windings through an antenna. The antenna should be moved along the height of the transformer. Since electromagnetic waves cannot penetrate the metal tank, a window is required on the body of the transformer tank to transmit waves toward the winding. The proper design of such a window and investigation of SAR imaging methods with the existence of it, is necessary to make the previous SAR imaging studies applicable to the transformer winding. Therefore, in order to study the design and implementation of a dielectric window, a prototype of a tank with a dielectric window is built considering electrical and mechanical constraints. The experimental results show the feasibility of applying the SAR imaging for localisation of radial deformation with the existence of a dielectric window in real transformers.

An experimental and testing platform was established to comparative study the decomposition characteristic of SF₆ under different voltage waveform (negative direct current (DC) voltage, positive DC voltage, and alternating voltage), and investigate the influence of pressure and adsorbent. Content variation of typical products under different conditions and the influence mechanism were observed and analysed in detail. The results indicate that SF₆ decomposition characteristics are closely related to a voltage waveform, pressure, and adsorbent. Concentrations of by-products under AC voltage are higher than those under DC voltage and SF₆ decomposes more easily under positive voltage than negative voltage, which can be explained by different discharge energy and distribution characteristic of space charges. The values of typical products show an obvious downward trend with pressure due to falling discharge energy, volume of active region and dissociation rate of SF₆. Concentrations of typical products including SOF₂, SO₂F₂, and SO₂ decrease dramatically after adding adsorbents because of physical absorption and chemisorption.

The equivalent series resistance (ESR) is an important parameter for determining the quality of a capacitor. In general, the value of the ESR can be obtained only at a single frequency point during mass production testing, because obtaining the whole ESR curve by means of scanning the frequency range is time consuming. We present a novel method to investigate how the ESR varies with frequency during batch testing. We use the multi-frequency synthesis excitation waveform to obtain the ESR at multiple frequency points. This allows the entire ESR curve to be obtained during one measurement period, thus greatly improving the measurement speed. The mathematical principle, the circuit realisation and the signal processing algorithm are discussed. Furthermore, a principle verification test is conducted, and the ESR values at seven frequency points are synchronously measured. The obtained results are consistent with those acquired from a standard LCR meter, and the entire measurement is completed within 10 ms, which confirms that our method is efficient and suitable for measurements in the mass production testing.

The construction of ultra-high-voltage direct-current power transmission projects in high-altitude areas calls for the research into the discharge characteristics of the air gaps in the valve hall of a power converter station in such areas. Tests on the switching impulse discharge characteristics of the sphere-plane air gap were conducted at Yangbajing test base (Tibet, China) at an altitude of 4300 m on conditions that there were burrs on the 1.3 m diameter shield balls. The discharge characteristics, under the influences of burrs with different lengths and locations, were obtained and compared with test data from low-altitude areas. The results indicate that the arrangements of burrs with different lengths and locations can significantly reduce the switching impulse discharge voltage of sphere-plane air gaps, while the voltage sag gradually decreased down with increasing burr length. Moreover, the larger the sphere-plane air gap is, the smaller the influence of such burrs have. High altitude also substantially decreased the switching impulse discharge voltage of the air gap. When the surface of shield balls was smooth, the U50 saturation of the air gap was more significant than at low altitude; however, if there were burrs on the shield balls, the saturation effect was less significant.