A novel type of microwave probes based on the loaded aperture geometry has been proposed and experimentally evaluated for dielectrics characterisation and high-resolution near-field imaging. Experimental results demonstrate the possibility of very accurate microwave spectroscopic characterisation of thin lossy dielectric samples and biological materials containing water. High-resolution images of the subwavelength lossy dielectric strips and wet and dry leaves have been obtained with amplitude contrast around 10–20 dB and spatial resolution better than one-tenth of a wavelength in the near-field zone. A microwave imaging scenario for the early-stage skin cancer identification based on the artificial dielectric model has also been explored. This model study shows that the typical resolution of an artificial malignant tumour with a characteristic size of one-tenth of a wavelength can be discriminated with at least 6 dB amplitude and 50° phase contrast from the artificial healthy skin and with more than 3 dB contrast from a benign lesion of the same size. It has also been demonstrated that the proposed device can efficiently deliver microwave energy to very small, subwavelength, focal areas which is highly sought in the microwave hyperthermia applications.

In electrical resistance tomography (ERT), finite element (FE) meshes of different topologies lead to different sensitivity matrices, which have great influence on the imaging quality of the ERT system. To improve the ill-posedness of the traditional sensitivity matrix and thus to improve the image quality, the reciprocal of the sensitivity matrix condition number is designed as the fitness function, based on which the modified genetic algorithm is utilised to optimise the topology of the FE mesh offline, and the optimised FE mesh is used to generate the sensitivity matrix, which is thereafter applied to image reconstruction using the modified Newton–Raphson algorithm. The feasibility of the proposed method is demonstrated in both simulation and prototype experiments. Comparisons among the mesh the authors optimised, the traditional mesh and meshes modified with other methods (all the meshes have the same number of nodes and elements) show that the proposed method has obviously reduced the condition number of the sensitivity matrix, and thus enhanced the imaging quality.

This study presents a method for the estimation of soil structure based on genetic algorithm (GA), which can reveal actual soil structures through the experimental curve of apparent resistivity that was measured near the ground grid. GA involves the use of the errors produced by the experimental and theoretical curve of soil apparent resistivity to achieve soil structure optimisation. In this study, new soil structures were generated by GA, and finite element method (FEM) was used to compute the theoretical curve of apparent resistivity under these soil structures. The relative position of ground grid and the measurement profiles was considered in FEM, which can reveal the true measurement site. Compared with present methods, the proposed method that combines FEM and GA can adapt to a solution domain of complex geometry shape while ground grid and soil exist simultaneously. Thus, the proposed method can handle the experimental curve which is influenced by the grounding system. In addition, the solution accuracy of the soil parameters was reasonably established and thus allowed the algorithm to exhibit convergence within 50 generations.

This study investigates the influence of a wide range of magnetising frequencies and peak flux densities on the magnetic properties of the electrical steels. In the relevant studies some important factors and operational properties, for example, skin effect, non-uniform flux density distribution, complex relative permeability and magnetisation characteristic of the material, which are often neglected in the literature, are highlighted. Analytical modelling and experimental works were performed for 3% grain oriented silicon steel. In order to show the impact of peak flux density on the magnetic properties, two peak flux densities 1.3 T as a high permeability point and 1.7 T as a low permeability point were considered. The results highlighted that magnetising frequency and peak flux density are two determinant factors with significant effect on the magnetic properties of electrical steels.

A characterisation system is developed to evaluate the performances of the digital partial discharge measuring instruments (PDMIs) that implement complex analysis functions, such as PD pattern classification and identification. The system can reproduce PD patterns, obtained from mathematical models or experiments on artificial defects or on-site measurements. The structure of the system and the characterisation of the generated charge sequences are discussed. The potentiality of the developed characterisation system has been proved in the evaluation of the advanced features of some digital PDMIs.

Measured data variation is crucial in medical measurements as it may affect the diagnosis and hence the treatment. This study introduces a procedure for measurement assessment in medical laboratories. The authors employ different quality measures such as the signal-to-noise, discrimination and precision-to-tolerance ratios to evaluate a measurement system of different gages. The different quality criteria will be mapped into one quality diagram that informs about the adequacy of a measurement system. A gage repeatability and reproducibility study in conjunction with analysis of variance analysis are employed. The authors also introduce a health quality characteristic index (HQCI) as a standard indicator of health status according to a given health characteristic. The established procedure, diagrams and HQCI guidelines could remarkably chart the accuracy of measurements and the precision of the used gages on blood pressure data conducted in a clinic. The presented guidelines can be potentially valuable for the assessment measurement with minimal statistical knowledge.

There are a few components of the current signal that may lead to inaccurate current measurement in power systems, and therefore, may cause malfunction on numerical protective relays and control devices. Some of these components include harmonics, the decaying DC offset, and noises. In this study, a phasor estimation method based on artificial neural networks is proposed, which will provide fast response time and accuracy. The method uses the multilayer perceptron structure to precisely estimate the amplitude and phase angle of the current waveform by determining its input weights during an online training process. The proposed algorithm is tested and compared with other reliable and well-known methods for a performance evaluation.

To achieve fast-response frequency estimation under step-change dynamics as well as accurate frequency estimation under slowly varying dynamics, a dynamic-model-based frequency estimation with step-change detection (DFESD) algorithm is proposed in this study. In DFESD, the derivative of the initial phasor estimation, which is obtained from short-time Fourier transform and the first-order Taylor-expansion phasor model, is used to detect the step changes in signals. Then, the initial estimations are adaptively selected by the data-selection strategy to estimate the frequency, of which the estimation is based on a high-order Taylor-expansion model to express the dynamic characteristics in signal. DFESD is a Taylor-expansion-based algorithm and it avoids the states mixture of both pre- and post- step-change data within one long data window, so it can track the frequency accurately under slowly varying dynamics and give fast-response estimation under step-change dynamics. Performance of the proposed algorithm is evaluated by computer-simulated and electromagnetic transients including DC (EMTDC) generated signals, and the results prove the efficiency of DFESD for accurate or fast-response frequency estimation under various test cases.

This study presents a novel estimation method for fast initial coarse alignment of a shipborne strapdown inertial navigation system. Unlike several current techniques, the alignment accuracy of the presented estimation method is not reduced by the shipborne disturbances causing by wave action (when moored) and the inertial measurement unit output constant error. The coarse alignment method is based on the acceleration sensed by accelerometers and the attitude matrix respect to the inertial frame sensed by star sensor. The specific force along the inertial frame is derived from the acceleration sensed by accelerometers, and the information characteristics of the specific force along the inertial frame are discussed. The analysed results show that the constant and periodical information is included in the transformation specific force along the inertial frame. Therefore Butterworth low-pass filter is used to extract the constant information to calculate the attitude of the vehicle. The effectiveness of this approach was demonstrates by simulation and experimental study. The results showed this coarse alignment method can estimate attitude information, and the attitude errors of the alignment result are small angles. Therefore the alignment accuracy meets the demands of fine alignment.

To investigate the effect of altitude on radio interference (RI) of AC power lines, a corona cage test system was used to measure the RI excitation function values of different bundle conductors in different altitude locations, such as Wuhan 23 m, Jingyuan 1408 m, Xining 2261 m, Gonghe 2943 m and Yangbajain 4300 m. Then, the RI curves with different altitudes, bundle numbers and subconductor diameters were obtained. The analysis and comparison show that the actual RI altitude correction values fall in between the range of 1 dB/300 m and 40(1 − σ/σ ₀) when the altitude below 3200 m, which is widely used as Italian correction term and Westinghouse correction term, respectively. Above this altitude, they are not applicable to predict the correction values. In this study, an RI correction term is proposed from the test results, which are fitted well for different altitude regions <4300 m.

This study proposes an algorithm for electrocardiogram (ECG) data compression using the conventional discrete Fourier transform. The coefficients are calculated using sine and cosine basis functions instead of complex exponentials, to avoid generation of complex coefficient values. Two well defined strategies are proposed for the choice of the significant coefficients – a fixed strategy based on the selection of a fixed band-limiting frequency, and an adaptive strategy depending on the spectral energy distribution of the signal. The different parameters for the two strategies are empirically selected based on extensive study of a wide variety of ECG data chosen from different databases. The significant coefficients are encoded using a unique adaptive bit assignment scheme to optimise the bit usage. The bit assignment map created to store the bit allocation information is run-length encoded to eliminate further redundancies. For the MIT-BIH arrhythmia database, the proposed technique achieves an average compression ratio of 14.67 for the fixed strategy and 16.58 for the adaptive strategy with excellent reconstruction quality, which is quite comparable to the other reported techniques. The simplicity and low cost infrastructural requirement of the algorithm, makes it suitable for implementation on an embedded platform to be used in mobile devices.

The precise localisation of rail vehicles is fundamental to the development and employment of more efficient train control systems in security, logistics and disposition applications. A key element of this is the exact and reliable velocity and distance estimation. The popular satellite navigation (global navigation satellite systems) and visual odometry, based on optical systems, tend to fail in the rough environment of rail application scenarios. This study describes an approach to making a precise distance estimate using an innovative eddy current sensor system. This is achieved through the combination of an augmented cross-correlation approach to highly accurate velocity estimation. That is subsequently employed to determine the travelled distance based on counting rail clamps in a spatial transformed space. This approach relies on recursive state estimation of the dynamic states and a statistical assessment of the counted rail clamps for the purpose of outlier rejection. The proposed methods are compared and evaluated in a quantitative way on the basis of experimental data. The results prove that the proposed approach can improve the accuracy and reliability of velocity measurement and relative position detection.

In this study, the use of time domain (TD) scan based on fast Fourier transform technique for radiated spurious emission (RSE) measurements is investigated. Measurement time and results of TD scan are compared with those of conventional frequency sweep method. The RSE measurements carried out are based on two different wireless technologies, that is, GSM 900 and GSM 1800. The findings show that the TD scan can reduce overall RSE test time up to 86% with comparable measurement results.

To ensure reliable operations of power transformers, online condition monitoring needs to be performed. However, extensive noise can be coupled into measured signals and cause ambiguities in evaluating transformers’ conditions. This study proposes a hybrid method, which combines pre-whitening and blind equalisation for de-noising the signals obtained from online partial discharge (PD) measurements of transformers. A measured signal is first gone through a pre-whitening process for initial noise reduction and then processed by blind equalisation. Finally, an equalised signal that can reveal PD source in a transformer is converted to a kurtogram for an accurate PD pattern representation. The proposed method has been applied to signals obtained from laboratory experiments and online measurements of transformers at substations. Results show that the method can effectively de-noise PD signals contaminated by severe noise and consistently represent PD patterns induced by different PD sources.

This study introduces a circuit breaker flashover accident caused by lightning strokes in a row of Xingren convertor station in Guizhou. To find out the reason of the flashover and whether fault circuit breaker insulation coordination can meet requirements under multiple lightning strikes, the overvoltage condition of hot-standby circuit breakers under lightning surge is calculated and checked by using EMTP and full-scale high impulse voltage test of the fault circuit breaker is conducted for the first time. Owing to the hot-standby state of the circuit breaker, the flashover accident is more likely to happen when lightning surge invades the substation or convertor station again. Measures to improve the hot-standby circuit breakers’ lightning withstand level are proposed and by simulating analysis, the measure combined installing a line arrester at a tower of the inlet line and installing an arrester near a certain breaker on the line proves to be effective.