Time-varying metamaterials and metasurfaces for antennas and propagation applications

In this contribution we present the most recent results from our group about the opportunities offered by time-varying metamaterials and metasurfaces for conceiving antenna systems and devices exhibiting artificial non-reciprocity, frequency conversion, energy accumulation and temporal electromagnetic scattering. Such artificial metastructures are characterized by constitutive parameters (permittivity, permeability and/or surface impedance) that are modulated in time through an external control or requires modulated excitation signal for enabling anomalous scattering behaviour. Here, we briefly describe the physical insights of the unusual interaction arising between the electromagnetic field and such metamaterials and metasurfaces, and then we present some antennas and propagation applications, showing the performances of non-reciprocal antenna systems, magnet-less isolators, Doppler cloaks, temporal devices and metasurface-based virtual absorbers.

Near-Field-Based 5G Sub-6 GHz Array Antenna Diagnosis Using Transfer Learning

In this paper, we propose a method for near-field-based 5G sub 6-GHz array antenna diagnosis using transfer learning. A classification network was implemented for normal/abnormal operation of the array antenna and the failure of a specific port. Furthermore, a regression network that could predict the amplitude and phase of the excitation signal of the array antenna was employed. Additionally, to accelerate the array antenna diagnosis, several near-field lines were sampled and reflected in the regression network. The proposed method was verified by measuring a fabricated 5G sub-6 GHz band 4×4 array antenna in various scenarios using a divider and coaxial cables. The tests showed that the trained network accurately diagnosed 29 of 30 measurement results.

Regression Model-Based Flux Observer for IPMSM Sensorless Control with Wide Speed Range

A new linear regression form is derived for a flux observer and a position observer is designed. In general, the observability of the permanent-magnet synchronous motor is lost at zero speed. In this work, the proposed regressor vector contains current derivative terms in both directions (dq-axis), and it gives the chance for the model-based flux observer to operate at zero speed. When an excitation signal is injected into d and q axes with the proposed flux observer, it helps to satisfy the persistent excitation condition in the low-speed range. Therefore, the sensorless performance of the model-based is improved greatly, even at zero speed. However, it appears with a disturbance term, which depends on the derivative of the d-axis current. Thus, the disturbance does not vanish when an excitation signal is injected. In this work, the disturbance term is also taken care of in constructing an observer. It results in an observer which allows signal injection. Thus, high frequency signal can be injected in the low speed region and turned off when it is unnecessary as the speed increases. This model-based approach utilizes the signal injection directly without recurring to a separate high frequency model. In other words, it provides a seamless transition without switching to the other algorithm. The validity is demonstrated by simulation and experimental results under various load conditions near zero speed.

Impulse Response Modeling of the Box Shaped Acoustic Guitar

Music is the pulse of human lives and is an amazing tool to relieve and re-live. And when it comes to the signal processing, impulse is the pulse of the researchers. The work presented here is focused on impulse response modeling of noted produced by box shaped acoustic guitar. The impulse response is very fundamental behavior of any system. The music note is the convolution of the impulse response and the excitation signal of that guitar. The frequency of the generated music note follows the octave rule. The octave rule can be checked for impulse responses as well. If the excitation signal and impulse response are separated, then an impulse response of a single fret can be used to generate the impulse responses of other frets. Here the music notes are analyzed and synthesized on the basis of the plucking style and plucking expression of the guitar-player. If the impulse response of the musical instrument is known, the output music note can be synthesized in an unusual manner. Researchers have been able to estimate the impulse response by breaking the string of the guitar. Estimating the impulse response from the recorded music notes is possible using the methodology of cepstral domain window. By means of the Adaptive Cepstral Domain Window (ACDW) the author estimated the impulse response of guitar notes. The work has been further extended towards the classification of synthesized notes for plucking style and plucking expression using Neural Network and Machine Learning algorithms.

A Segmentation Model of ECU Excitation Signal Based on Characteristic Parameters

According to the basic structure and working principle of the excitation signal sensors of a diesel engine electronic control unit (ECU), a segmentation model of an ECU excitation signal based on characteristic parameters (ESCP-SM) is proposed. In the ESCP-SM, the ECU excitation signal is divided into several parts, and each part has its characteristic parameters model. By using the same global parameters and strictly controlling each part’s proportional parameters, the ESCP-SM can achieve signal alignment and dynamic frequency modulation. Based on the simulation experiment, spectrum analysis proves that this modeling method ensures that the original signal’s effective information is not lost. Pearson similarity analysis shows that the similarity between the simulation signal and practical signal reaches 74%, exhibiting strong correlation. In addition, we set up a physical testing environment. ESCP-SM is realized based on virtual instrument technology, and provides excitation signals for a Komatsu 8 ECU. By modifying the parameter configuration, the ECU can drive the injector to work correctly.

Numerical Modelling of Ultrasonic Guided Wave Propagation and Defect Detection in Offshore Steel Sheet Piles

Sheet piles are significantly more prone to advanced corrosion rates due to accelerated low water corrosion. Current inspection and assessment techniques are costly, time-consuming and labour-intensive. Guided wave testing (GWT) has gained increased attention due to its capability of screening long distances; however, it has not been used previously to inspect the active zone in steel sheet piles. This paper focuses on the numerical modelling of wave propagation and defect detection in U-shaped piles to demonstrate the capabilities of GWT for the inspection of non-accessible areas of steel sheet piles. Two shear transducer arrays were designed, bearing high SH0 mode purity and directionality. A wave propagation comparison study concluded that the back wall reflection signal from the web of a U-pile was 11.5% higher than the respective signal from the plate, and the excitation signal in the flange, at 5.65 m and 7.12 m, was respectively 35% and 46% less than the excitation signal in the web at the same distance. Defect reflection, measured from five representative defect scenarios, ranged from 7.5 to 47% of the signal amplitude in the web of the pile and 5 to 32.5% in the flange of the pile.