The very demanding requirements of the SKA-low instrument call for a challenging antenna design capable of delivering excellent performance in radiation patterns, impedance matching, polarization purity, cost, longevity, etc. This paper is devoted to the development (design and test of the first prototypes) of an active ultra-wideband antenna element for the low-frequency instrument of the SKA radio telescope. The antenna element and differential low noise amplifier described here were originally designed to cover the former SKA-low band (70–450 MHz) but it is now aimed to cover the re-defined SKA-low band (50–350 MHz) and furthermore the antenna is capable of performing up to 650 MHz with the current design. The design is focused on maximum sensitivity in a wide field of view (+/− 45° from zenith) and low cross-polarization ratios. Furthermore, the size and cost of the element has to be kept to a minimum as millions of these antennas will need to be deployed for the full SKA in very compact configurations. The primary focus of this paper is therefore to discuss various design implications for the SKA-low telescope.

SKALA, a log-periodic array antenna for the SKA-low instrument: design, simulations, tests and system considerations

Linear Arrays with Arbitrarily Distributed Elements

Wind power is one of the fastest-growing technologies for renewable energy generation. Unfortunately, in the recent years some cases of degradation on certain telecommunication systems have arisen due to the presence of wind farms, and expensive and technically complex corrective measurements have been needed. This paper presents a comprehensive review on the impact of wind turbines on the telecommunication services. The paper describes the potential affections to several telecommunication services, the methodology to evaluate this impact, and mitigation measures to be taken in case of potential degradation, both preventive and corrective. The telecommunication services included in this review are those that have demonstrated to be more sensitive to nearby wind turbines: weather, air traffic control and marine radars, radio navigation systems, terrestrial television and fixed radio links. The methods described in the paper allow a thorough case-by-case analysis before the wind farm is installed, taking into account the particular features of each installation and the involved services. The prediction of the potential impact makes it possible to propose alternative solutions in order to assure the coexistence between the wind turbines and the telecommunication services.

Impact analysis of wind farms on telecommunication services

Composite such as Glass Fibre Reinforced Polymer (GFRP) is increasingly used as insulation in many industrial applications such as the steel pipelines in the oil and gas industry. Due to ageing and cyclic operation, many hidden defects exist under insulation, such as corrosion and delamination. If these defects are not promptly detected and restored, the growth of defects causes a catastrophic loss. Therefore, an effective inspection technique using non-destructive testing (NDT) to detect the underneath defect is required. The ability of microwave signals to penetrate and interact with the inner structure within composites makes them a promising candidate for composite inspection. In the case of GFRP, the random patterns cause permittivity variations that influence the propagation of the microwave signals, which results in a blurred spatial image making the assessment of the material’s state difficult. In this research, a novel microwave NDT technique is presented based on k-means unsupervised machine learning for defect detection in composites. At present, the defect evaluation using an unsupervised machine learning-based microwave NDT technique is not reported elsewhere. The unsupervised machine learning is employed to enhance the imaging efficiency and defect detection in GFRP. The technique is based on scanning the composite material with an open-ended rectangular waveguide operating from 18 to 26.5 GHz with 101 frequency points. The influence of the permittivity variations on the reflected coefficients due to the random patterns of GFRP is mitigated by measuring the mean of a set of the adjacent points at each operating frequency point using a small rectangular window. The measured data is converted to the time domain using a fast inverse Fourier transform (IFFT) to provide significant features and increase the signal resolution to 201-time steps. K-means algorithm is utilized to cluster the given features into the defect and defect-free regions in GFRP. The findings presented in this paper demonstrate the benefits of an unsupervised machine learning to detect a defect down to 1 mm, which is a considerable contribution over any existing defect inspection technique in composites.

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Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm

Wind Turbine Clutter (WTC) is the radar clutter caused by strong backscatter from large wind turbines within the radar vicinity. Due to the rotation of the rotor blades, the Doppler spectrum of WTC varies from scan to scan. This time-varying radar signature results in the failure of classic ground clutter filter techniques. The Adaptive Spectrum Processing (ASP) algorithm proposed in this paper explores the spatial and spectral characteristics of weather returns in weather radar, and adaptively generates band pass filters based on the moment estimates of uncontaminated weather in detected wind farm region. The actual NEXRAD weather radar data have been used to verify this algorithm. The experiment shows significant improvement on moment estimation in terms of both bias and variance.

Wind Turbine Clutter mitigation for weather radar by Adaptive Spectrum Processing

The next generation radio telescopes such as the Square Kilometer Array (SKA) are expected to contain thousands of antenna array elements operating over a broad frequency range where the signals from each antenna element are combined and processed simultaneously providing high sensitivity with multiple beams providing a wide field of view. One crucial design aspect influencing both the performance and the cost of such systems is the array geometry. Due to the large bandwidth and number of broadband antenna elements, the optimization of such array system is difficult to achieve with the current array geometry optimization techniques which rely mainly on genetic algorithms and pattern search techniques. This paper provides a study of the effects of array geometry on the performance broadband array system. In addition, it provides a method where the array geometry can be more easily optimized for different applications. This is demonstrated for optimizing a typical SKA station in the frequency band between (70-450 MHz).

Geometry Design Optimization of Large-Scale Broadband Antenna Array Systems

The application of radar absorbing materials (RAM) in order to reduce the interference of wind farms with radar systems is considered as a possible mitigation solution. This paper will address the key challenges when trying to efficiently apply RAM to certain parts of the wind turbine blades to significantly reduce the scattering of radar signals. Modeling of the radar cross-section (RCS) is presented for a generic 40 meter blade wind turbine before and after applying RAM to different parts of the blade. The results of modeling possible solutions of partially RAM treated blades are compared.

Partial treatment of wind turbine blades with radar absorbing materials (RAM) for RCS reduction

Ceramic based coatings such as Thermal Barrier Coatings (TBCs) are widely deposited onto gas turbine engine components to protect their metal substrate against high temperature However, improper adhesive application, thermal stress and moisture penetration through the insulation materials can cause defects such as delamination to grow between the insulation and the metal surface Such defects could lead to catastrophic failure if not immediately detected and repaired Hence, it is imperative to non-destructively inspect these interfaces for delamination to avoid such an event In this paper, a novel microwave non-destructive testing technique for ceramic-based coatings is proposed This technique is based on scanning the surface of the coating with an open-ended rectangular waveguide and analyzing the reflections in the time domain The proposed time-domain technique appears to reveal more about the depth of any existing delamination than any other microwave non-destructive testing (NDT) technique Here, a ceramic sample with machined delamination is scanned using rectangular waveguides operating from 265 to 40 GHz After applying Fourier analysis to the frequency domain waveguide reflections, time-domain results showed the delamination with significantly better depth resolution compared to frequency domain analysis The results reported in this paper prove the advantages of the time-domain technique to forecast the relative delamination depth, which is important for many industrial applications The depth information of delamination can be used in a condition-based predictive maintenance schedule to plan the inspection intervals efficiently, minimize the unnecessary replacements and provide practical guidance for future design

/pdf/nondestructive-evaluation-of-coatings-delamination-using-rvpe4yyw5y.pdf

Nondestructive Evaluation of Coatings Delamination Using Microwave Time Domain Reflectometry Technique

Radar pulses from magnetron radar are far from perfect rectangular shape. This paper investigates the effect of integrating a measured pulse shape of marine navigational radar into a radar propagation model used to assess the effect of a complex environment, in this case a wind farm. A comparison between the results from the model and measured data taken near the North Hoyle wind farm in North Wales, UK is provided.

Laith Rashid

Papers

Geometry Design Optimization of Large-Scale Broadband Antenna Array Systems

Partial treatment of wind turbine blades with radar absorbing materials (RAM) for RCS reduction

Nondestructive Evaluation of Coatings Delamination Using Microwave Time Domain Reflectometry Technique

Radar propagation modeling in complex environments for marine navigational radar using measured pulse shapes