Derivative recovery through local smoothing, is a well-known approach to obtain an estimate of a solution field's derivative, to one polynomial order higher than its direct representation. In the finite element method context, this is often referred to as ‘gradient recovery’. The method of moments (MoM) is routinely used to solve electromagnetic field integral equations in terms of the electric surface current density, which is often represented by mixed first-order, Rao–Wilton–Glisson (RWG) basis functions upon a mesh of triangle elements. A procedure for recovering a mixed second-order, approximate solution from an RWG-based MoM solution is presented. Recovery of the solution itself rather than its derivative, is made possible by exploiting specific properties of the mixed-order, surface divergence-conforming function spaces. The procedure is not strictly local, however, only sparse, positive-definite global linear systems must be solved. The procedure is independent of the integral operator. Computational complexity is lower than that of existing residual-based MoM error estimators. Results are shown with the recovered solution being a better approximation than the original solution. The procedure is useful for post-processing and for local or global a posteriori error estimation. It can be incorporated into any RWG-based MoM code.

This study presents theoretical as well as experimental studies in order to obtain interpretations about the role of nanoparticles in the breakdown mechanism of transformer oil. The published breakdown mechanisms for nanofilled transformer oil are briefly discussed in order to highlight the points of agreement and disagreement with these mechanisms. Moreover, a proposed breakdown mechanism for nanofilled oil is presented depending on a proposed particle charging mechanism that is theoretically discussed and experimentally validated. Finally, the obtained experimental results prove the efficacy of the proposed theoretical mechanisms.

In this study, the temperature influence on iron loss of non-oriented steel laminations is investigated. The iron loss variation under different flux densities, frequencies and temperatures is systematically measured and analysed by testing two typical non-oriented steel laminations, V300-35 A and V470-50 A. The iron loss variation with temperature is almost linear in the typical operating temperature range of electrical machines. Furthermore, the varying rate of iron loss with temperature varies with flux density and frequency. A coefficient which can fully consider the temperature influence is introduced to the existing iron loss model to improve the iron loss prediction accuracy. The predicted and measured results show that the temperature influence on the iron loss can be effectively considered by utilising the improved model, i.e. the prediction accuracy of the improved iron loss model remains constant, even when the temperature varies significantly. A potential simplification of this improved model is also discussed in this study.

The impacts of a lightning strike are amplified in an environment with special features such as a ship electric grid, especially within the extended integration of electronic systems. In most marine regulations, lightning protection specifications are inadequate in the cases of metallic vessels, regarding the necessity of installing lightning rods and the method for the definition of their protection zone and subsequently of their height. Therefore, impulse voltage experiments on a scaled-down ship model were conducted in order to acquire interception probability distributions of its superstructures and to assess the accuracy of various protection zone models, established for isolated rods, on the given complex topology of a ship. The experimental results highlighted the overestimation of the protection zone even by the well-established rolling sphere model for negative polarity impulses depending on the geometrical conditions and the satisfying performance of statistical models that incorporate proximity effects and lightning interception probability.

This study presents a novel technique for estimation of contamination level as well as flashover voltage of outdoor insulators based on dielectric dissipation factor evaluated from the applied sinusoidal excitation and corresponding surface leakage current. Existing literature shows that surface leakage current of insulator is infested with odd harmonics though the applied voltage is sinusoidal in nature. The presence of harmonic contents in leakage current is due to non-linear characteristics of the insulator surface owing to formation of dry bands. The nonlinear characteristic of the insulator surface depends on its contamination level which in turn affects the corresponding flashover voltage. Therefore, the harmonic configuration in leakage current can be correlated with the contamination level on insulator surface and corresponding flashover voltage. Considering the fact, in this contribution, a non-linear equivalent circuit of insulator has been proposed based on harmonic components of the leakage current. For each harmonic component of the leakage current flowing through the insulator system, energy lost and energy stored in the system is calculated, which eventually enables to calculate dielectric dissipation factor. The proposed technique is applied for experimental investigation on 11 kV disc porcelain insulator artificially contaminated in the laboratory under controlled environmental conditions.

In plenty of researches and real systems, barometer and accelerometer which can provide altitude and acceleration measurements, respectively, are utilised in altitude estimation of small unmanned aerial vehicle. These sensors can draw on their merits and improve the accuracy of altitude estimation. The altitude measurement of barometer has the drift problem as one of its disadvantages which could deteriorate the performance of altitude estimation. In addition, barometer and accelerometer both have stochastic error which reduce the accuracy of altitude estimation. A novel scenario is proposed by utilising differential altitude measurement and complementary filter to deal with above issues. It is accurate and suitable for real-time application. In this scenario, altitude drift is reduced by using differential altitude measurement, and the stochastic error of altitude is minimised by using complementary filter algorithm. Stair and flight experiments are implemented to test this scenario. The experimental results indicate that it can provide good dynamic performance and flexibility for altitude estimation.

Phase-to-ground fault is the most probable fault type in power systems, which is generally limited through neutral grounding resistor. The grounding resistor may have negative impacts on the system such as decrease in sensitivity of the differential protection. Fault current limiter (FCL) is a suitable alternative for the grounding resistor. However, the input signals of differential protections may be adversely affected by the FCL, resulting mal-operation of this protection. In this study, effects of FCL installed in neutral line of power transformers on the relevant differential protection algorithms are analysed. Performance of some well-known differential protection algorithms for discrimination between internal fault and magnetising inrush currents in presence of the neutral FCL is evaluated in detail. Then, a supplementary method based on the least error squares technique is proposed to rectify the deformed portion of the current waveform due to presence of the FCL. The reconstructed signal is considered as a proper input for the discrimination algorithms. Various simulations and experiments are carried out to validate the performance of the suggested technique. The results indicate the consistency of the suggested technique for different power systems, operating conditions, and real applications.

A microprocessor board comprises many capacitors in parallel for decoupling purposes. Due to space constraints, they are kept close to each other. When two capacitors with different self-resonant frequencies are connected in parallel, between their self-resonant frequencies an impedance peak known as antiresonance is introduced. If the capacitors are placed close to each other, their mounting loops are magnetically coupled. This coupling affects the antiresonance peak value, which is studied in this study. An expression for the peak value of antiresonance is derived using circuit theory, and it is compared with accurate solutions obtained in Matlab™. A general critical damping condition is formulated based on this. The expressions are validated with simulation and experimental studies. The obtained results will be useful for improving capacitor selection algorithms used in power distribution network design by incorporating the coupling effects into the constraints.

The aim of this study is to evaluate the intensity and damage potential of seismic accelerograms on structures combining a fuzzy inference system with a set of new seismic intensity parameters. The proposed seismic parameters stem from the energy content of seismic signals. More specifically, a time-window is utilised to define the strong motion duration of seismic excitations and the ensemble empirical mode decomposition is employed for a time–frequency analysis of the selected strong motion area. The maximum inter-storey drift ratio is selected as the seismic structural damage index. Strong interdependence between the proposed seismic intensity parameters and the selected damage index is reported. The membership functions of the fuzzy system are tuned by means of a genetic algorithm. The effectiveness of the proposed fuzzy model is tested on a reinforced concrete frame structure. The methodology should be repeated for every new examined structure and it can be applied to other building types with minor changes. Numerical results indicate total mean square error <0.25 for the maximum inter-storey drift ratio estimation and 91% correct classification rate to seismic categories, revealing the effectiveness of the fuzzy model to estimate numerically the structural damage.

Water is the most valuable natural resource. To preserve this good, several water monitoring systems for pipe networks have been proposed. However, there is a lack of research on the development of high-frequency electromagnetic sensors for this task. This study proposes a non-destructive technique to locate carrying water polyvinyl chloride pipes using a microstrip patch antenna. An experimental apparatus was mounted and the resonant frequency and Q factor of the antenna were measured for different relative positions between the sensor and the pipe filled with water. To detect the pipe position, experimental data were trained and tested by applying an approach based on support vector machines. The best results were from using a simple linear kernel, which allowed 100% accuracy using a 30% fraction of data used for holdout validation.

This study concerns the in-motion alignment in the strapdown inertial navigation system (SINS) with large misalignment angles. As the non-linear filtering method applied in the alignment model is quite computer intensive, which has a significant impact on the alignment accuracy and speed. To solve this problem, a robust H-infinity cubature Kalman filter (CKF)/KF hybrid filter (RHCHF) is proposed to lower the computational burden and strengthen the robustness. By virtue of the idea of model decomposition, the RHCHF could estimate the non-linear and linear parts of alignment model, respectively. Through the introduction of robust factor to adjust the filter parameters, it can ensure the accuracy reliably. The comparisons of the simulation and vehicle experiment demonstrate that the RHCHF could achieve the results at a significantly lower expense than the unscented Kalman filter, and obtain a high accuracy even when the statistical property of noise is uncertain or the outliers of measurement occur occasionally.

For the high-speed and light autonomous underwater vehicle (AUV), it is moving freely, and the speed and attitude are in dynamic movement. Then, the traditional static and quasi-static ground alignment cannot be used any more. Using the optimisation-based alignment (OBA) scheme, this study presents a novel estimation method for fast initial coarse alignment of a AUV's strapdown inertial navigation system (SINS). The novel OBA method use the inertial measurement unit, the pressure sensor measurements and the navigational velocity ν ^v in v-frame produced by the motor thrust to solve the attitude estimation problem which is known as Wahba's problem. Unlike several current techniques, the presented estimation method is effective to any movement form. The simulation results show that the attitude determined by this novel method can meet the accuracy requirement of coarse alignment and it can be used as input for the fine alignment.

Spectrum sensing in the low signal-to-noise ratio (SNR) environment is vital task for the evolution of cognitive radio technology. The numerous signal processing algorithms have since been proposed to improve the spectrum sensing performance. In the recent past, entropy based sensing methods are shown to be robust in a low SNR environment with small data sets. However, these methods only focus on information content and ignore temporal order of the signal. Hence, selection of appropriate entropy technique that considers both information content and temporal order is important. In addition, many works consider that the distribution of noise follows Gaussian under assumption that the sample size is infinity. The detection threshold designed using this assumption yield unreliable decisions. On the contrary, the captured data is limited in real-time and it should be minimum to reduce the computational complexity. To address these two issues, empirical permutation entropy with adaptive thresholding detection technique is proposed. Then, the work is extended to weighted gain cooperative sensing that uses Higuchi fractal dimension method to generate weight for each node. Simulation results reveal that the proposed method is robust, less sensitive to sample size, and improves the single node as well as multinode sensing performance.

In this study, an evolutionary strategy is presented to get the optimal grounding grid design to minimise the design cost, the touch and step voltages of the grounding grid to ensure the economical constraint as well as the safety conditions. The proposed technique is used for one and two-layer soil. This technique is based on the comparison between the quality factors of the initial grid dimension according to the cost, touch and step voltages with the other quality factors obtained from new generations (offspring) of the grid dimensions. Effects of top layer thickness, number of grid meshes, vertical rods number and length, and the soil resistivity of the top and bottom layers on grounding resistance (R _g) and earth surface potential are studied. Different case studies are introduced to evaluate the performance of the proposed technique and to provide the knowledge about the grid dimensions that is substantial for the economical design of the grounding grids.

For the simulation of rectilinearly moving conductors across a magnetic field, the Galerkin finite-element method (GFEM) is generally employed. The inherent instability of GFEM is very often addressed by employing streamline upwinding/Petrov–Galerkin (SU/PG) scheme. However, the SU/PG solution is known to suffer from distortion at the boundary transverse to the velocity and the remedial measures suggested in fluid dynamics literature are computationally demanding. Therefore, simple alternative schemes are essential. In an earlier effort, instead of conventional finite-difference-based approach, the numerical instability was analysed using the Z-transform. By employing the concept of pole-zero cancellation, stability of the numerical solution was achieved by a simple restatement of the input magnetic flux in terms of associated vector potential. This approach, however, is restricted for input fields, which vary only along the direction of the velocity. To overcome this, the present work proposes a novel approach in which the input field is restated as a weighted elemental average. The stability of the proposed scheme is proven analytically for both one- and two-dimensional cases. The error bound for the small oscillations remnant at intermittent Peclet numbers is also deduced. Using suitable numerical simulations, all the theoretical deductions are verified.

Electromyogram (EMG) signals contain a lot of information about the neuromuscular diseases like amyotrophic lateral sclerosis (ALS). ALS progressively degenerates the motor neurons in spinal cord. In this study, a new technique for the analysis of normal and ALS EMG signals is proposed. EMG signals are decomposed into narrow band intrinsic mode functions (IMFs) by using empirical mode decomposition (EMD) technique. The area of complex plot, two bandwidths namely amplitude modulation bandwidth (B _AM) and frequency modulation bandwidth (B _FM), normalised instantaneous frequency (IF _n ), spectral momentum of power spectral density (SM_PSD) and mean of first derivative of instantaneous frequency (MFD_IF) are extracted from analytic IMFs obtained by EMD technique. These six features are used as input in least square support vector machine classifier for the classification of ALS and normal EMG signals. Experimental results and comparative analysis show that classification performance of the proposed method is better than other existing method in the same database.

Recently Y. Ren and J.T. Conway calculated the mutual inductance and the magnetic force between an ordinary coil and a bitter coil or between two bitter coils. The bitter coil is the coil with inverse radial current density. In this study, the authors calculate the mutual inductance and the magnetic force between two disk coils (pancakes) with inverse radial current density. This coil configuration with proposed current density seems to be similar to bitter coils. Both calculations give the semi-analytical expressions either for mutual inductance or for the magnetic force. Also they derived the self-inductance for the disk coil with radial current density which is obtained in closed form. The results of this method are compared by those obtained by the modified filament method for the presented configuration.

This study explores wavelet decomposition based skewness analysis for walking speed assessment. This has been achieved by using four force sensing resistors attached beneath the foot and one flex sensor attached on ankle. Experimentation is carried out on walking pattern of able individuals and data are collected using data acquiescing set-up and de-noised using Savitzky–Golay filter. De-noised data are then decomposed at different discrete wavelet transform (DWT) levels from where skewness values of approximate coefficient are assessed. Variation of skewness with respect to walking speed has been observed which shows that skewness values are having definite relations with walking speeds at certain DWT levels. Based on these, an algorithm is proposed for walking speed assessment. Experimentation is again carried out to validate the proposed algorithm. Satisfactory result is achieved indicating that assessment of wavelet decomposition based skewness of approximate coefficients may be very useful for walking speed measurement.