Node localisation plays a significant role in wireless sensor networks, as most of the applications require exact location of sensor nodes. To obtain the exact location of sensor nodes, a range-based localisation method based on Jaya optimisation using received signal strength indicator (RSSI) is proposed. The distance between the target node and the reference nodes is obtained from the measured RSSIs using regression-based log normal shadowing model. Further, improvement in the localisation accuracy is accomplished by formulating the location of target node as an optimisation problem. Jaya optimisation algorithm is adopted, as it is parameter-free and efficient. The Jaya algorithm is used for estimating the distance as well as the coordinates of the target node. The proposal is compared with particle swarm optimisation and validated through simulation and hardware experiments. The maximum localisation error using Jaya and particle swarm optimisation through simulation is observed to be 0.08 and 0.37 m, respectively. Real-time experiments using Jaya algorithm exhibited the maximum localisation error of about 0.14 m for indoor environment and 0.3 m for outdoor environment. The results of the proposed methodology show significant improvement in terms of accuracy.

This research is a continuation of researches into transformation errors of current transformers, when the cores consist of two different magnetic materials at non-rated loads and overcurrents. Analyses of the electromagnetic field distribution for different secondary winding loads were performed (magnetic field distributions of current transformers, current error and phase displacement diagrams). Computations were conducted based on the finite element numerical method and the results were compared with tests of real-life models.

Here, the distributed parametric circuit model of the series-resonant charge power source in Tesla pulse driver is built. The generation mechanisms and characteristics of three types of dU/dt interferences and one kind of di/dt interference are analysed. The voltage ringing and its corresponding dU/dt generated on the shared parts of the main circuit play as the input common-mode interference (CMI) to the driving and triggering circuits. Circuit simulation and tests were both carried out to get the characteristics of high-frequency CMIs in different key points of the main circuit. The generation and conducting of the high frequency CMIs were mainly caused by the abrupt charge and discharge resonances of the distributed capacitors. CMI suppression methods were put forward and demonstrated, such as resistor-capacitor absorption between the middle points of the converter H-bridge, resistor-capacitor grounding at the negative port of the input DC mother line, the negative port grounding of the load capacitor, and symmetrical layout of two L-C resonant arms in the series-resonant circuit. The voltage ringing, dU/dt and di/dt interferences in the series-resonant converter were all effectively suppressed by these methods.

Multiple incipient faults are practically known to exist in transformers. They tend to produce suddenly changing ratio limits in ratio-based methods or oscillation of fault location in graphical methods. In consequence, the energy associated with them lies in-between low and high severity single faults. Hence multiple fault detection needs to be addressed appropriately which may otherwise pose the serious constraints during transformer condition monitoring. In this study, novel and intelligent classification approach is proposed to upgrade the classical dissolved gas analysis (DGA) technique to cater the requirement of multiple fault diagnosis. This consists of Duval-triangle-based optimised fuzzy inference system and neural network models sensitive to both single and multiple incipient faults. Both models have been rigorously trained and tested using dataset credited to field and literatures to achieve high fault recognition and isolation rates, alternatively low false detection and no-detection rates. Both parameters are combined into single index to determine the accuracy in terms of F1 score which is evaluated to be >97%. The diagnostic ability of the scheme is highly promising and can improve reliability of transformer fault forecasting by DGA.

To improve the performance and increase the lifetime of oil-filled transformers, the thermal and dielectric properties of the transformer oil should be enhanced. Recently, nanotechnology was used as an effective science in the field of transformer oil development. In this study, barium titanate (BT) nanoparticles were inserted into the base transformer oil by a concentration of 0.005 g/L as an individual nanofluid sample (INFS). This insertion enhances the heat transfer coefficient by 33% but the breakdown voltage (BDV) was decreased by >10%. To overcome this problem of dielectric properties degradation, other three hybrid nanofluid samples (HNFS) were prepared using three different types of metal oxide (MO) nanoparticles; titania, alumina, and silica. These samples were prepared by adding a concentration 0.01 g/L of MO nanoparticles together with 0.005 g/L of BT nanoparticles into the oil. The thermal and dielectric properties of HNFS were measured to study the behaviour of nanoparticles hybridisation on transformer oil properties. HNFS using titania nanoparticles provided the best composition regarding either BDV or heat transfer coefficient. Dynamic light scattering (DLS) technique was used to evaluate the particle size distribution of hybrid nanoparticles and to clarify the corresponding physical mechanisms behind the obtained enhancement.

The dynamic space charge distribution within cross-linked polyethylene (XLPE) cable insulations is simulated in this study. To simulate charge dynamics inside the insulation, different models have been developed. Conductivity-based models describe electronic and ionic charges. Such models are structurally simpler than bipolar charge transport models because of their macroscopic description. So far, the macroscopic description is insufficient, as it does not depict the accumulation of homocharges and heterocharges near the electrodes and the transport of charge packets. In this study, a conductivity-based model is developed to simulate the transport of charges and the formation of homocharges and heterocharges. The conductivity model depends on the electric field and on the temperature. This model is extended by two Gaussian curves, moving from the electrodes to the counter electrodes, which features an increased conductivity in comparison to bulk conductivity. The bulk conductivity is obtained from measurements in the literature. The permittivity is modelled to be non-constant in the vicinity of the electrodes due to e.g. interdiffusion between the bulk insulation and the semiconducting layer. A comparison between the simulation results and the reference measurements confirms the applicability of the presented approach for the description of the dynamic charge distribution in XLPE cable insulation.

In vitro experiments proved the usefulness of electron paramagnetic resonance (EPR) spectrometry for detecting detonation nanodiamonds (NDs) in samples of biomaterials (blood and homogenates of organs of mice). A characteristic EPR signal (g = 2.003, ΔH ≃ 10 G) was detected in biomaterials containing NDs, and its intensity linearly increased at nanoparticle concentrations of between 1.6 and 200 µg/ml. In vivo experiments demonstrated that EPR spectrometry was effective for monitoring the inter-organ distribution of NDs intravenously injected to mice. In 2.5 h after the injection of NDs, the nanoparticles mainly accumulated in the lungs and liver of the animals – about 25 and 20%, respectively, of the initially injected NDs. The amounts of NDs accumulated in the heart and kidneys were considerably lower. Also, EPR spectrometry did not detect NDs in the blood, spleen, brain, and femoral muscles of mice. Ten days after injection, EPR spectrometry detected redistribution of NDs in mice. The amounts of nanoparticles decreased approximately by a factor of 3.5 in the lungs and increased almost by a factor of 3 in the liver; NDs were detected in the spleen. This study suggests ways to use EPR spectrometry to study the distribution, accumulation, and elimination of detonation NDs injected into laboratory animals.

Accurate estimation of a phasor, frequency, and rate of change of frequency during changing power system condition is important to initiate precise control action for reliable power system operation. Conventional phasor estimation techniques cannot estimate the phasor accurately during dynamic conditions of power system. Furthermore, the phasor-based frequency estimation algorithms are being affected under such conditions. In this study, both angle and amplitude modulation parameters are considered in the signal model to improve the accuracy of the phasor estimation. The method uses Taylor's series expansion to linearise the signal model and computes the signal parameters using least squares. The method first computes the phasor using estimated parameters of the signals, subsequently calculates the frequency and rate of change of frequency. The performance of the proposed method is evaluated for standard test signals. Real signals recorded in numerical relay are used to assess the performance of the proposed method. The results are compared with the available method and found that the method can supplement the existing methods used in phasor measurement units and intelligent electronic devices.

Nanofluids (NFs) are an emerging technology in the field of dielectrics. These oils are used in transformers and other power apparatus for the purpose of insulation and cooling. The vegetable oil (VO) proposed in this study is the Pongamia pinnata oil (PPO), commonly known as karanji oil. The molecular structure of PPO is changed by the transesterification process and converted to Pongamia oil methyl ester (POME) as the crude oil is not suitable for direct use because of its high viscosity, high pour point, and acid number. For preparing the NF, 0.01 wt.% of exfoliated hexagonal boron nitride (Eh-BN) is dispersed in mineral oil (MO) and POME to prepare MO-based NF (MO-NF) and POME-based NF (POME-NF), respectively. This study explores the various thermophysical and electrical properties of four types of oils – MO, MO-NF, POME, and POME-NF. Thermophysical properties such as thermal conductivity, interfacial tension, flash point, and pour point, and electrical properties such as dielectric constant, dielectric dissipation factor, and dielectric strength are measured and a comparative analysis is carried out among all the four types of oils. The charging dynamics study has also been investigated to understand the phenomenon underlying the enhanced breakdown voltages of VO-based NFs.

Two methods for measuring the dielectric constant and loss tangent of the dielectric materials using software-defined radio (SDR) are presented, which may be used as an alternative to the expensive vector network analysers (VNA). The first method used was the cylindrical cavity resonator designed for a resonance frequency of 2.5 GHz. The second method used was the complementary split ring resonator designed for a resonance frequency of 1.25 GHz. In both cases, measurements were carried out using VNA and SDR to compare the efficiency of both tools. The measurement accuracy was assessed by comparing the results with the declared values in the data sheets of dielectric manufacturers. The results showed a good agreement with the available data sheet values and further demonstrated that the SDR is an excellent tool for microwave measurements.

Grid impedance is an important parameter in most power system applications such as power quality analysis of smart grids. In this study, a new time–frequency distribution is employed for grid-impedance estimation in high-frequency range using a single rectangular pulse injection. There is no compatibility level for harmonics within the frequency range of 2–150 kHz which is the most important issue in the international standardisation committee. Compatibility level is defined based on harmonic emission and immunity levels of grid-connected equipment. Therefore, knowledge of grid-impedance characteristics over the frequency range of 2–150 kHz is very important to estimate the level of distortion caused by grid-connected equipment and defines future regulations and standards. For impedance estimation, a pulse must be injected to the grid, then the current through and voltage at a point of common coupling are measured. The measurement duration must be long enough to consider the transient state. The most appropriate shortest measurement duration is selected from the time–frequency plane using Wiener entropy. Test and simulation results validate the accuracy of the proposed method for grid-impedance estimation in high-frequency range.

The study presented here investigates the performance of nano-reinforced cross-linked polyethylene (XLPE) for high-voltage insulation applications with particular focus on dielectric characteristics, treeing behaviour and mechanical properties. The nanocomposites with varying content of organo-modified layered silicate (nanoclay) were prepared by melt mixing of polyethylene, cross-linking agent and nanoclay. X-ray diffraction and atomic force microscopy studies showed that layered silicates were uniformly dispersed with exfoliation in XLPE matrix up to 5 wt% nanoclay content with formation of intercalated structures with slight agglomeration at higher nanofiller content. The dielectric loss, relative permittivity and dielectric strength of the nanocomposites increased with increasing nanoclay content, which was attributed to the inherent properties of XLPE and nanoclay, nanofiller dispersion and interfacial polarisation. The effect of frequency on the dielectric properties was also investigated. Incorporation of nanoclay in XLPE altered the electric field stress distribution in the material and consequently retarded water tree growth. The electric field distribution and the probability of water tree growth were studied by finite element method. Additionally, mechanical properties of the nanocomposite viz. tensile strength and modulus were also enhanced. The changes in the properties were correlated to the morphology of the nanocomposites, as well as polymer filler interactions.

This study proposes an analytical model to evaluate the equivalent impedances of domestic induction heating systems. The method of separation of variables is employed to determine the vector potential produced by a filamentary coil under a semi-infinite conductor. Then, based on the superposition principle of linear problems, the total vector potential of the coaxial, coplanar, connected-in-series rectangular cross-sectional multi-windings with same thicknesses, which are made of enamelled Litz wire, is derived by integrating the vector potential of filaments. Finally, the total voltage on the windings and the equivalent impedance of the induction heating system are obtained. The proposed analytical method is flexible to be used for calculating the equivalent impedance of multi-windings with any number of windings in an induction heating system with any mixture of windings with different lengths in the radial direction, and any distance between two adjacent windings in the radial direction. The proposed generally analytical method is successfully verified by comparison with the finite element method and shows improvement with respect to the conventional analytical method.

Aeromagnetic compensation, elimination of magnetic interferences produced by the aircraft platform, plays a vital role in aeromagnetic applications. Conventional compensation methods are based on the Tolles–Lawson (T–L) model, which accounts for only the manoeuvring interferences. However, magnetic interferences due to other factors, such as currents from electrical systems and movable parts, are found significant in practice. In this study, the authors take these interference factors into consideration, including the strobe light and beacon light, the rudder and elevator. The magnetic interference from constant current is equivalent to the ‘permanent magnetisation’ and has been contained in the T–L model. The interferences due to the strobe and beacon lights are modelled to be proportional to the currents and their temporal variations. The model coefficients can be estimated in advance in a ground experiment. The interferences by the pivoting rudder and elevator are still characterised by the T–L model but in the local rudder or elevator coordinate systems, and the compensated coefficients can be obtained on the ground or in the sky. Onsite experiments both on the ground and in the sky are conducted to illustrate the proposed modelling, and improved compensation results are obtained.

A bias-compensated normalised least mean square (BCNLMS) algorithm with variable step size (denoted as BCVNLMS) is developed in this work to improve the accuracy and convergence speed for the three-phase power system (TPPS) frequency estimation in circumstance of the noise and harmonic interference. Taking into account the problem of bias estimation caused by the mixed noises in the acquisition signal of the TPPS, the NLMS algorithm with an unbiased criterion (called BCNLMS) was employed to compensate the bias and improve the estimate accuracy. Furthermore, an adaptive variable step scheme is also incorporated into the BCNLMS algorithm to improve the convergence speed and stability during the process of adaptively frequency estimation. The experimental results show that the proposed BCVNLMS algorithm outperforms other well-known methods for frequency estimation of the TPPS in several scenarios such as severe noise pollution, harmonic interference and frequency mutation.

The study proposes a novel hardware-based architecture of the reconfigurable embedded system for the multi-channel immersion ultrasonic system. It provides the addressing-based analogue multiplexing scheme, which requires only one data acquisition unit and common on-chip storage for the multi-channel imaging system. It also provides unique channel reconfigurable facility to the user to modify the number of channels (up to 256 for pulse-echo and 512 for transmit–receive mode by installing only the partial front-end hardware (pulser, pre-amplifier) and without modifying the remaining data acquisition hardware (common-amplifier, digitiser) and back-end embedded system. The developed system further supports dynamic on-line reconfiguration of the analogue front-end hardware, real-time hardware-based data processing, and data transfer operation. The authors have implemented the addressing-based reconfigurable architecture of the coherent averaging for noise reduction. For the experimentation, the complete four-channel ultrasonic imaging system for immersion testing has been designed, developed, and evaluated in the laboratory. Furthermore, this study describes the capability of the proposed system by performing multi-channel real-time data acquisition, hardware-based coherent averaging, channel multiplexing–demultiplexing, reconfigurable control, and software-based post-processing. Here, they present the performance evaluation of the developed multi-channel system by carrying out the B-scan and C-scan image acquisition of the water-immersed mechanical components.

One of the popular methods for insulation diagnosis is measurement and analysis of polarisation–depolarisation current (PDC). During normal operation, charges get confined at the interface of oil–paper insulation. A part of these accumulated charges get absorbed in depolarisation current and contribute to the overall PDC data. The process through which charges are released from their confinement is known as charge de-trapping, which is highly influenced by thermal energy content of the insulation and hence by measurement temperature. In the current work, an effort has been made to investigate the effect of measurement temperature on de-trapped charge. Two samples are prepared and analysed in the laboratory at different temperatures for this purpose. This is followed by analysis of data collected from several real-life power transformers. Related analysis presented here suggests that measurement temperature of the system plays an important role in determining the amount of de-trapped interfacial charge during PDC measurement.

Here, a new device is presented to supervise the ageing process of insulating oils used in power transformers. It is based on the use of a microstrip antenna whose electrical properties are very sensitive to the permittivity and conductivity of the medium. As many works showed that the drift of permittivity due to transformers aging is very small, the achieved sensor must exhibit a great sensitivity. In order to assess the aging of the insulation oil, the authors will track the resonant frequency of the antenna which is directly related to the permittivity of the oil, and the reflection coefficient level of the antenna at the resonance frequency which is linked to the conductivity. The experiments have been made on vegetable oil and results revealed to be enthusiastic. The sensor is proposed to be used in an embedded system in order to achieve a low cost and safe preventive diagnosis.