Dissolved gas analysis (DGA) is a prevailing methodology being widely used to detect incipient faults in power transformers. Although various methods have been developed to interpret DGA results, they may sometimes fail to diagnose precisely, especially when solid insulation deterioration is involved. This study presents a time series correlation technique, in which the sampled data of dissolved gases in the transformer oil are considered as a time series and the series correlation scheme in statistics is adopted to explore and manipulate the fault information. Both the constant and variable characteristic parameters are initially chosen based on analysis in terms of frequency histograms. With quantitative correlation analysis between the constant and variable characteristic parameters, a new criterion for solid insulation diagnosis is thereby proposed, which can be used to diagnose whether solid insulation deterioration is involved in a transformer fault, as well as further distinguish the electrical faults from the thermal ones. According to the proposed technique, explorative tests regarding two power transformers have shown promising results. With regard to the 91 fault samples collected from China Power Grid, the diagnosis accuracies for electrical and thermal faults were 86.5 and 77.7%, respectively, whereas it was 61.5% for the prevailing CO₂/CO criterion.

Since uncertainties in variables are unavoidable, an optimal solution must consider the robustness of the design. The gradient index approach provides a convenient way to evaluate the robustness but is inconclusive when several possible solutions exist. To overcome this limitation, a novel methodology based on the use of first- and second-order gradient indices is proposed introducing the notion of gradient sensitivity. The sensitivity affords a measure of the change in the objective function with respect to the uncertainty of the variables. A Kriging method assisted by algorithms exploiting the concept of rewards is employed to facilitate function predictions for the robust optimisation process. The performance of the proposed algorithm is assessed through a series of numerical experiments. A modification to the correlation model through the introduction of a Kriging predictor and mean square error criterion allows efficient solution of large scale and multi-parameter problems. The three-parameter version of TEAM Workshop Problem 22 has been used for illustration.

The working current of DC grounding electrodes is constantly increasing with the rapid development of high-voltage direct current systems. Thus, the temperature rise of grounding electrode conductors is increasingly becoming an important safety factor. Therefore this study measured the soil temperature characteristics of water content and resistivity; established an electric heat coupling finite element model for DC grounding electrodes that is based on current field and temperature field theories to analyse the temperature changes in common DC grounding electrodes. In contrast to traditional models, the proposed model realises electric heat coupling field calculation by considering the mutual influence of temperature rise and soil parameters. The results show that the soil resistivity increases with increasing temperature and the soil resistivity change further influence the temperature changes of the grounding electrodes. The change in grounding electrode temperature rise is not steady and includes a sharp growth stage.

Defect inversion is of special interest to magnetic flux leakage (MFL) inspection in industry. This study proposes an iterative neural network to reconstruct three-dimensional defect profiles from three-axial MFL signals in pipeline inspection. A radial basis function neural network is utilised as the forward model to predict the MFL signals given a defect profile, and the defect profile gets updated based on a combination of gradient descent and simulated annealing in the iterative inversion procedure. Accuracy of the proposed inversion procedure is demonstrated in estimating the profile of different defects in steel pipes. Experimental result based on three-axial simulated MFL data also shows that the proposed inversion approach is robust even in presence of reasonable noise.

The study proposes a fast modelling technique to predict output signal of an open-ended rectangular waveguide when scanning an arbitrary-shape surface crack in a metal. In this technique, the crack is first segmented into an appropriate number of short rectangular waveguides each of which is modelled by a two-port network with an equivalent RLC circuit. The generalised scattering matrix technique is then used to predict the probe output signal. The efficiency of the proposed model is demonstrated by comparing the simulation results of several case studies with measurements and those obtained using the mode-matching method and a commercial finite integration technique code.

Electric field intensity can be determined analytically, experimentally and numerically. Charge simulation method (CSM) is one of the most commonly used numerical methods for its many characteristics features. It can be used stand alone or in combination with other numerical methods. Sometimes optimisation techniques are used to facilitate the locating of the simulating charges as well as their values. Several optimisation techniques have emerged in the past decades that mimic biological evolution. The most representative techniques include genetic algorithms (GA) and particle swarm optimisation (PSO). Although PSO is more computationally efficient than GA, the later was used frequently to develop optimised versions of CSM during the last two decades. On the other hands, PSO technique was used recently only once to optimise the location of the simulating charges. In this study, the combination process between PSO and CSM became more convenient by optimising both charge locations and their values. This work eliminates the problems that were associated with the last trial and increases the degree of freedom that leads to solutions that are more realistic. The validity of the proposed method was verified by comparison with the analytical and numerical solutions.

Exponential voltage was proposed as a stimulus in the analog-to-digital converter (ADC) test because it is much more similar to the theoretical one than the sinusoidal signal. For the correct execution of the ADC test, the distortion of the exponential stimulus must be assessed by evaluating the amplitude and the time coefficient of the fundamental and the superimposed exponential components that best fit the real exponential voltage. To achieve this goal, the Prony-like method is proposed in this paper. Two problems arise: the a priori evaluation of the degree of polynomial function that best fits the input samples, and the number of exponential components that have to be evaluated. To overcome these problems, two proper sub-routines are pointed out allowing operation without a priori information and in accordance with the physical model of the signal. The results of experimental tests are shown in order to assess the correctness and the accuracy of the proposed procedure.

Hybridising of different optimisation techniques provides a scope to improve global exploration capability of the resulting method. In this study, an enhanced differential evolution (DE) algorithm, called hybrid Taguchi-differential evolution (TDE) algorithm is proposed to solve power system state estimation problem as an optimisation problem. TDE combines the positive properties of the Taguchi's method to the classical DE algorithm for improving the accuracy and reliability of state estimation problem. The systematic reasoning ability of the Taguchi method is incorporated after crossover operation of DE algorithm to obtain the potential chromosome, better convergence rate and subsequently, to improve the robustness of the results. The proposed method is tested on IEEE test bus systems along with two ill-conditioned systems under different simulated conditions. The results reveal that solutions yield towards global optimum and it compares far better than conventional DE, particle swarm optimisation, gravitational search algorithm and weighted least square based state estimation techniques in terms of optimisation performance, solution quality and the statistical error analysis.

In this study, an efficient and exact numerical technique based on modal method of moments (MoM) is presented to evaluate shielding effectiveness of an infinite cylindrical enclosure with a lateral aperture on its wall. To this end, modal vector wave functions are used to represent the electric field and consequently the surface magnetic current on the aperture. To calculate inside and outside magnetic fields, the circular waveguide dyadic Green's functions are utilised. The unknown magnetic current on the aperture is calculated using the MoM by enforcing the continuity of tangential magnetic field on the aperture. This method is employed for different enclosure sizes when illuminated by transverse magnetic (TM) polarised wave at two different incident angles.

In friction stir welding (FSW), a proper selection of the FSW tool is an important factor which, as an appropriate tool, cannot only improve the quality of the weld but also diminish the destructive effects including applied forces and high temperature induced during the welding process. This research is aimed to scrutinise the effect of the tool geometries on the axial and translational forces, temperature and mechanical properties for AA7075-T6 are investigated. The threaded tapered, non-threaded triangular and non-threaded cylindrical pins were employed. It was observed that the tool shoulder diameter was directly correlated with the generated temperature, axial and translational forces and weld characteristics. Moreover, the lowest amounts of measured forces were recorded in the case of threaded tapered pin whereas the generated temperature, UTS, elongation and grain size were higher for this pin as compared with the other pins. Nevertheless, in the tapered pin, hardness is lower than that of the other pins. It was also shown that the created fluctuations during the FSW process and stabilising time were lower for the threated tapered pin compared with the other two pins.

To reduce circulating current losses in stator strands of hydro-generator, strand transposition is widely used in stator bars. At present, the traditional analytical method for calculating circulating current losses cannot accurately simulate the distribution of leakage magnetic field, which will bring a large deviation to the calculation result and not benefit the winding design. The numerical calculation method for circulating current losses in stator bar is presented in this study, by which the leakage magnetic field distribution of stator transposition bar can be described in detail through establishing three-dimensional actual transposition model. The 0°/360°/0° transposition bar in a 180 MW hydro-generator is taken as an example and the circulating current losses in stator bar strands are calculated. The causes of errors in traditional analytical method are discussed through the comparison of the leakage magnetic field distribution obtained by numerical calculation method and traditional analytical method.

A review of vibration signal estimation techniques employed in ultrasonic vibration measurement systems is presented. The review focuses on the Doppler signal extraction methods including the theory and analysis pertaining to the background of ultrasonic vibration measurement techniques. The phase modulated received signal in the vibration measurement system involves constant phase shift because of ultrasonic path length, phase shift introduced by Doppler effect because of vibrating object and the parametric phase shift caused by interaction of high frequency ultrasonic wave and low pressure developed by vibrating object. Among the three phase shifts, the Doppler phase shift contains the vibrating signal information and the extraction of Doppler signal helps in knowing the velocity of the vibrating object, amplitude and phase of the vibration. Various techniques of Doppler phase shift retrieval are categorised based on the modulation index estimation procedures from the received ultrasonic signal. An analysis is made based on the information retrieval methods for estimation of vibration signal parameters, range of the vibration amplitude, frequency and the preferable carrier frequency for transmission. Further, the analysis also presents various applications in which ultrasonic vibration measurements system are employed successfully.

Parametric and non-parametric statistical methods are compared and discussed for the accuracy assessment of digital surface models coming from airborne laser scanner. Such datasets are chosen from different types of areas: from the relatively favourable flat terrain to the complex built-up areas and abrupt terrain zones with vegetation. For those complex sites, a reference ‘ground truth’ is established using a mobile mapping system, whereas flat terrain areas are checked through static ground surveying using global positioning system. The experimental results confirm that systematic errors and many outliers remain in the airborne laser scanner dataset corresponding to built-up and abrupt terrain areas, and thus that nonparametric statistical methods are suitable for an accuracy assessment.

Stress and residual stress are two crucial factors which play important roles in mechanical performance of materials, including fatigue and creep, hence measuring them is highly in demand. Pulse eddy current (PEC) and ultrasonic testing (UT) are two non-destructive tests (NDT) which are nominated to measure stresses and residual stresses by numerous scholars. However, both techniques suffer from lack of accuracy and reliability. One technique to tackle these challenges is data fusion, which has numerous approaches. This study introduces a promising one called neural network data fusion, which shows effective performance. First, stresses are simulated in an aluminium alloy 2024 specimen and then PEC and UT signals related to stresses are acquired and processed. Afterward, useful information obtained is fused using artificial neural network procedure and stresses are estimated by fused data. Finally, the accuracy of fused data are compared with PEC and UT information and results show the capability of neural network data fusion to improve stress measurement accuracy.

This study presents the development and implementation of an alternative Flickermeter based on a low cost embedded electronic system. The development of this new device is based on the original Flickermeter proposed by the IEC 61000-4-15, but with important modifications added. These modifications allow for direct quantification of light variation, in such a way, so as to eliminate the effect associated with the different lamp technologies available through the correct quantification of flicker severity. In order to achieve this objective blocks 1 and 3 of the original IEC Flickermeter were altered and block 2 was completely eliminated. The implementation of a low cost embedded electronic system represents the differential of the developed system in relation to equipment currently available on the market, which is based on solutions of a more elevated cost. The developed prototype was appropriately tested and thus provided encouraging results. In addition, the article also presents an analysis that refers to the susceptibility of lamps manufactured upon the same technologies to flicker, such as compact fluorescent and LED lamps, widely used nowadays for substituting traditional incandescent lamps.