An adaptive sampling method based on simplex-mesh refinement is proposed for creating a forward database that can facilitate the inverse problem solution in non-destructive testing. The resulting mesh-database is used as a generic interpolator of the forward problem. The available sensitivity data are utilised for obtaining an optimal sampling with respect to the piecewise linear interpolation applied for data retrieval. The resulting database provides guaranteed quality of approximation using a relatively few number of samples. The method is illustrated by a crack reconstruction problem of eddy current testing.

The interferometric fibre optic gyroscope (IFOG) is a kernel component of strap down inertial navigation system (SINS) for providing angular rotation of any moving object. The behaviour of SINS degrades because of noise and random drift errors of the IFOG sensor. This study proposes a hybrid of adaptive sampling strong tracking algorithm (ASSTA) and scaled unscented Kalman filter algorithm for denoising the IFOG signal. In this algorithm, the state error covariance (P) is updated by using a suboptimal fading factor based on the innovation sequence followed by the ASSTA method. The proposed algorithm is applied for denoising the IFOG signal under static and dynamic environment to crush the random drift errors and noises. Allan variance analysis is used for analysing the efficiency of algorithms. Simulation results depict that the suggested algorithm is suitable for reducing drifts of the gyro signal.

In this study, a basic gait motion simulator mechanism combining control units and electromechanic hardware has been proposed and implemented for the test stages of knee prostheses. The main goal to develop such simulator equipment is to regenerate predefined and controllable periodic movement, specifically hip vertical displacement and thigh angle motion applied to above-knee prosthesis so that test studies will be less dependent to human trials in any development phase. Gait motion simulator performance tests were conducted with both an image-based motion measurement system and a direct-type motion measurement system. In the hip simulator performance evaluation phase, accelerometer and video signals were collected simultaneously from the experimental system for kinematic analysis. The overall system consists of a hip simulator, a microcontroller-controlled prosthetic knee and a solid ankle cushion heel foot on a treadmill. Experimental results were evaluated for assessing the degree of approximation of the natural periodic hip movement by designed electromechanical simulator. The analysis showed that the test platform presented in this study is a useful yet low budget alternative to more expensive general-purpose electromechanic test devices for development purposes.

Rogowski coil is one of the popular current transducers for measuring currents either in the sinusoidal form or in the form of high-frequency pulses. In this study, first, the performance of the Rogowski coil is investigated through comprehensive experiments to be formed as a design methodology. Then, the results create a base for proposing two systematic approaches for designing Rogowski coils. The first approach is a knowledge-based approach and the second one involves a heuristic search method which results in optimum design according to the selected objective function, considering the practical limits in the physical parameters. The proposed design procedures cover Rogowski coils which measure large sinusoidal currents for power system protection purposes and also those for measuring impulsive currents with large as well as low peaks.

Transients from lightning strikes can enter underground cables at overhead line to power cable transitions. Possible overvoltages on these surges at cross-bonding connections of the cable screens are of major concern. A model is developed for modelling overvoltages from transient signal propagation through a combined cross-bonding cable and box. This model is applied to the first Dutch 400 kV cable connection. Such model incorporates model parameters whose values depend on design details of the cross-bonding box. The values for these model parameters are extracted from the measured transmission and reflection signal on steep pulses injected into the actual cross-bonding box configuration. The model combines transmission line description for the cross-bonding cables with mainly inductive behaviour of the cross-bonding box. The obtained results are verified by measurements. The model is applied to investigate overvoltages induced at the cross-bonding cable and box on 1.2/50 µs impulse voltage injection representing a lightning impulse voltage applied to the core conductor of the cross-bonding cable. Furthermore, the effectiveness of surge arresters to reduce overvoltages at the cross-bonding cable screen is demonstrated by simulations with this model in PSCAD.

Wavelet-based de-noising is used to separate partial discharge (PD) signals from the noises resulting from measurement circuits or the surrounding environment. PD de-noising by using the wavelet shrinkage method is capable of separating the noise component to some extent, but the selection of the wavelet base has a remarkable effect on the de-noising results. The wavelet base is directly related to the distortion of the PD waveform and quality of the de-noising process. Although there are applications on PD noise separation in the literature, the selection of the wavelet base, which affects the evaluation of the PD characteristics, is still challenging. Instead of using correlation-based wavelet base selection for de-noising PD data, in this study a novel wavelet base selection method based on the most informative sub-band energy and entropy for separating noise from PD pulses is introduced and successfully applied to raw data obtained from the PD measurement set-up. The advantage of the proposed method is that the wavelet base selection solution is automatic and independent of the original noise-free pulse waveform. This study shows that the proposed method is useful for the extraction of noisy PD pulses by describing the basic discharge parameters such as discharge amplitude and the duration and time of occurrence more clearly.

Multilevel inverter has arrived on the scene as an attractive and unique tool which is extensively employed for adapting dc (direct current) voltage to ac (alternating current) voltage. These appliances have recently taken shape as reliable sources of elevated power and found themselves well-utilised more often than not in industrial applications, by employing sine or adapted sine waves. The sine wave form generated in the multilevel inverter output has huge harmonics which should be minimised by appropriate steps. With a view to minimise the harmonics at the output signal, it is necessary to cut short the related total harmonic deformation (THD) of switching angles. Genetic algorithm is widely employed for the function of harmonic optimisation. However a hurdle appears as the cost function tends to invite further intricacy for the optimisation, entailing an added number of iterations. Therefore, with an eye on scaling down the number of iterations, the intention of genetic and particle swarm optimisation algorithms is to optimise the switching angles to the utmost. This method also leads to the decline of the related THD values. The innovative method is executed in the MATLAB/Simulink working platform.

This study analyses the stability of cubature Kalman filter (CKF) for non-linear systems with linear measurement. The certain conditions to ensure that the estimation error of the CKF remains bounded are proved. Then, the effect of process noise covariance is investigated and an adaptive process noise covariance is proposed to deal with large estimation error. Since adaptation law has a very important role in convergence, fuzzy logic is proposed to improve the versatility of the proposed adaptive noise covariance. Accordingly, a modified CKF (MCKF) is developed to enhance the stability and accuracy of state estimation. The performance of the modified CKF is compared to the CKF in two case studies. Simulation results demonstrate that the large estimation error may lead to instability of CKF, while the MCKF is successfully able to estimate the states. In addition, the superiority of MCKF that uses fuzzy adaptation rules is shown.

Indoor intrusion detection systems are widely implemented in many special departments and environments. Owing to the special target market, several specific features of such systems are required including high accuracy, high performance, high concealment and ease of deployment. In this study, the authors proposed an infrared light spot displacement-based surveillance system for indoor intrusion detection. This system, named BriGuard, shares a similar idea with radar. A 940 nm infrared light beam goes through an optical diffraction grating to generate light spot matrix imagery in the view of a complementary metal oxide semiconductor image sensor. The coordinates of the light spots are extracted and recorded. When someone enters the monitored area, the imaging plane changes and leads to a variation of the pre-recorded light spots coordinates. The light beam is modulated in order to be distinguished from the light in the environment. The lightweight algorithms require little computation power and data storage. BriGuard achieves a nearly zero false detection rate while covering a distance up to 10 m. It can process 30 full HD (1920 × 1080) frames per second. More importantly, because of unnoticeable infrared lights and very small form factor, the whole detection equipment is very hard to observe.

A self-assembled film of nickel phtalocyanine (NiPc) has been immobilised onto gold (Au) substrate to develop a new impedimetric method for environmental pollutants detection. NiPc/Au electrode was first characterised using contact angle measurements and cyclic voltammetry to investigate the adhesion and the kinetic behaviour of the self-assembled film. Results demonstrated the interaction between Au and benzene group and at the same time showed the formation of a completely covered NiPc layer on the Au surface. In addition, the NiPc film seems to exhibit reversible redox behaviour and is found to act as an electronic conductor which allows rapid electron transfer. The electrochemical impedance spectroscopy spectra of the NiPc/Au electrode, as a function of hydroquinone (HQ) and Bisphenol A (BPA) concentration, reveal that the value of the charge transfer resistance increases with increased concentration. The electrical behaviour of the structure was studied according to an equivalent circuit by fitting the experimental spectra. Moreover, this technique demonstrates that this membrane exhibits a high sensitivity towards the toxic pollutants HQ and BPA. The differences in selectivity are clearly displayed by variations in the membrane resistance (R _m) and in the charge transfer resistance (R _tc) of the interface.

In this study, a sliding mode controller is designed to control the position tracking of robot manipulator. The proposed control has global asymptotical stability in the presence of structured uncertainties, un-structured uncertainties and un-modelled dynamics of the robot manipulator as well as in motors dynamics. The proposed control structure is designed in such a way that initially, by using inverse dynamic method, it reduces the uncertainties bound and finally, sliding mode control eliminates the influence of the remaining uncertainties in closed-loop system stability. Further, in control input for eliminating undesirable chattering phenomena using the fuzzy logic, an adaptive fuzzy approximator is designed in such way that approximates the uncertainty bounds. Mathematical proof shows that the adaptive fuzzy sliding mode control of a closed-loop system has global asymptotical stability. Since the number of existing fuzzy rules are low in adaptive fuzzy approximator rules base and in single input–single output form, so control input computational load is very low and this order makes the proposed control of practical implementation possible. To evaluate the performance of the proposed controller, a case study on a robot manipulator with two degrees of freedom is implemented. Simulation results show the desired performance of the proposed controller.

This study presents an experimental investigation of the behaviour of electrical double layer (EDL) under oil flow and voltage application inside a capacitive sensor. This sensor is incorporated in a closed-loop filled with fresh transformer oil. The sensor configuration allows a potential application for risk assessment. The behaviour of EDL is investigated by recording the streaming and the capacitive current waveforms for grounded and energised middle copper-electrode cases and at different oil-flow velocities and temperatures. The effect of direct and alternating voltage energisation is examined for different wave shapes and frequencies. In addition, the physicochemical reaction coefficient, the wall space–charge density and the accumulated charges inside the sensor are calculated by the static and the dynamic methods. The results are interpreted in terms of EDL evolution, physicochemical reaction at the solid–liquid interface, relaxation time of charges and electron emission from the negatively energised electrode. The results reveal that the calculated wall space–charge density slightly decreases with the increase in the oil-flow velocity, contrary to the physicochemical reaction coefficient. For the case of AC energisation, the results show that there is an innocuous effect of the generated harmonic voltages on the oil-flow electrification phenomenon.

This study discusses the estimation of time of arrival (TOA) used for ranging and positioning applications in orthogonal frequency division multiplexing ultra-wideband- (OFDM-UWB) based system. The correlation-based method applied for impulse radio-UWB (IR-UWB) is not suitable for OFDM-UWB because OFDM-UWB signal is much longer than IR-UWB in time domain. This study proposes a new method for TOA estimation of OFDM-UWB signal based on wavelet packet transform (WPT). The author's method estimates TOA of OFDM-UWB signal through the time information of the frequency band of UWB, which is one of the branches of WPT decomposition of the oversampled received baseband signal. It does not need the whole OFDM signal to estimate TOA of UWB signal because every segment of OFDM-UWB signal in time domain contains all information of UWB frequency band; therefore the resolution of TOA is improved. Signal-to-noise ratio can also be improved because WPT decomposes the power of additive white Gaussian noise equally in all wavelet packet branches, and false alarm rate can be controlled. The author's method is robust in that it can counter narrow band noise and impulse noise effectively. Numerical results show our method is effective for accurate estimation of TOA for OFDM-UWB signal.

This study deals with a reduced sensor configuration of a power factor correction (PFC) based zeta converter for brushless DC (BLDC) motor drive for low power applications. The speed of the BLDC motor is controlled by varying the dc-link voltage of the voltage source inverter (VSI) feeding BLDC motor drive. A low-frequency switching of the VSI is used for achieving the electronic commutation of BLDC motor for reduced switching losses. The PFC-based zeta converter is designed to operate in discontinuous inductor current mode; thus utilising a voltage follower approach which requires a single voltage sensor for dc-link voltage control and PFC operation. The proposed drive is designed to operate over a wide range of speed control with improved power quality at ac mains. The performance of the proposed drive is validated with experimental results obtained on a developed prototype of PFC converter.

In accordance with the uncertainty of decision rules extraction process in boundary region of the rough set, this study proposes a rough-set belief rule model using multinomial subjective logic. The model builds the belief rule expectation for classification and recognition. It not only considered the effects of single condition attributes on decision, but also the multi-attributes. Finally, the example analysis and comparison with the R _0.5(X) model indicates the validity and advantage of this model.

In spite of many research efforts on fault diagnosis using frequency response analysis (FRA) method, there is still no universally accepted and systematic interpretation technique for these tests and ‘expert opinion’ is often sought when any damaging trend is observed as a result of fault occurrence. This study deals with statistical criteria for interpretation of the FRA results and presents a number of statistical and mathematical indicators that have not been used so far. A measurement setup accompanied by a transformer as a test object, on which winding faults are imposed, completes the test setup for performing the FRA measurements. The parameters are applied to the experimental FRA measurements and the results are compared by a simple normalising equation. Finally, the indicators which are adding more objectivity and transparency to interpretation of the FRA results are presented. Sweep frequency response analysis (SFRA) method is used in this study because of its efficiency and simplicity. It was found through this research work that F-test, which introduced in this study for the first time, has higher sensitivity, and the differences between the normal and faulty responses of the transformers' windings is more reflected in this parameter compared with the other ones.

Parameter estimation and dynamic modelling of power systems and their components are basis of design, planning and stability or security assessment in power systems. This study considers the estimation of power system model parameters by a global identification framework based on the maximum-likelihood principle. The proposed framework is formulated as a non-linear optimisation problem, which is solved by a hybrid method based on the bat-inspired algorithm and differential evolution method. The combination of these algorithms makes the hybrid method faster and it obtains closer to the global minimum than a pure global method. Since noise and model uncertainties are inherent parts of system identification, the effect of these factors on the performance of the proposed identification framework are studied. Results based on synthetic data in frequency domain show that the estimated parameters are close to the correct values even in the presence of significant measurement noise and considerable uncertainties.