Wavenumber Filtering Research Articles

An identification method of bonding state in ETIS based on GPR

Abstract The external thermal insulation system (ETIS) often has safety quality problems caused without debonding, and the classical debonding detection methods can not achieve high precision and high efficiency safety detection at the same time. Ground penetrating radar (GPR) can be one of the most efficient tools to identify the bonding state. In this paper, a methodology for bonding state detection is presented. Firstly, a modeling and simulation method for ETIS is designed, which is closer to the real form of the adhesive shape. Secondly, a 3D frequency wave-number domain filter is used to remove the low-rank direct-coupled waves and the low-frequency components, then a matched filter is used to estimate the time delay arrival and identify the adhesive shape in ETIS. Finally, the effectiveness of the algorithm for the recognition of bonding state is verified by numerical results and experiments.

Transducer Resolution Effect on Pressure Fluctuations Beneath Hypersonic Turbulent Boundary Layers

The size of a pressure transducer is known to affect the accuracy of measurements of wall-pressure fluctuations beneath a turbulent boundary layer because of spatial averaging over the sensing area of the transducer. In this paper, the effect of finite transducer size is investigated by applying spatial averaging or wavenumber filters to a database of hypersonic wall pressure generated from a direct numerical simulation (DNS) that simulates the turbulent portion of the boundary layer over a sharp 7° half-angle cone at nominally Mach 8. A good comparison between the DNS and the experiment in the Sandia Hypersonic Wind Tunnel at Mach 8 is achieved after spatial averaging is applied to the DNS data over an area similar to the sensing area of the transducer. The study shows that a finite sensor size similar to that of the PCB132 transducer can cause significant attenuation in the root-mean-square and power spectral density (PSD) of wall-pressure fluctuations, and the attenuation effect is identical between cone and flat plate configurations at the same friction Reynolds number. The Corcos theory is found to successfully compensate for the attenuated high-frequency components of the wall-pressure PSD.

An inverse method for characterization of dynamic response of 2D structures under stochastic conditions

The reliable estimation of the wavenumber space (k-space) of the plates remains a long-term concern for acoustic modeling and structural dynamic behavior characterization. Most current analyses of wavenumber identification methods are based on the deterministic hypothesis. To this end, an inverse method is proposed for identifying wave propagation characteristics of two-dimensional structures under stochastic conditions, such as wavenumber space, dispersion curves, and band gaps. The proposed method is developed based on an algebraic identification scheme in the polar coordinate system framework, thus named Algebraic K-Space Identification (AKSI) technique. Additionally, a model order estimation strategy and a wavenumber filter are proposed to ensure that AKSI is successfully applied. The main benefit of AKSI is that it is a reliable and fast method under four stochastic conditions: (A) High level of signal noise; (B) Small perturbation caused by uncertainties in measurement points’ coordinates; (C) Non-periodic sampling; (D) Unknown structural periodicity. To validate the proposed method, we numerically benchmark AKSI and three other inverse methods to extract dispersion curves on three plates under stochastic conditions. One experiment is then performed on an isotropic steel plate. These investigations demonstrate that AKSI is a good in-situ k-space estimator under stochastic conditions.

Spin wave excitation and detection using different meander-shaped antennas: experiment and simulation

The excitation and detection of spin waves (SWs) with specific wavenumbers is very important not only for fundamental SW research but also for the development of future SW devices. Conventional SW theoretical and numerical studies focused on the excitation of dynamic magnetization in waveguides, and did not address the practical limitations imposed by the geometry and configuration of the detection antenna. Using the finite element method, we calculated the induced current with meander-shaped antennas on the detection side, and succeeded in simulating the wavenumber filter effect of SW signals on detection. This was confirmed using experimental measurements on permalloy waveguides. In addition, we investigated, using simulation and experimentally, the effects of combinations of different meander-shaped antennas and broadband signal-ground antennas for excitation and detection. It is found advantageous to set the meander antenna on the detection side to enable filtering and selectivity of SW wavenumber. These findings are important for the development of SW devices.

Water ingress detection in an aluminum honeycomb sandwich structure using laser ultrasonics based on mode conversion behaviors

This paper investigates the method for water ingress detection in an aluminum honeycomb sandwich structure by laser ultrasonics. To clarify the propagation of Scholte waves generated at the solid-liquid interface, the theoretical dispersion curves in the water-aluminum layered structure are calculated by the global matrix method. Using a laser ultrasonic visualizing inspector, the guided wave propagation in the wavefields has been visualized, which shows the mode conversion behaviors occurring in the water ingress area. The clarification of mode conversion is then investigated by the finite element method. The Scholte modes at the solid-fluid interface and the Lamb modes in the face sheet are interconverted because of the change in the waveguide structure. Wavenumber filter reconstruction and the resulting energy maps are applied to illustrate the mode conversion in the wavefields and to detect the water ingress area. Results show that the appearance of the water layer contributes to the mode conversion behaviors during the guided wave propagation in the honeycomb sandwich structure, which offers the potential for water ingress detection based on the mode conversion behaviors.

Surface defect identification based on broadband laser-generated Rayleigh wave with wavenumber filtering

As a non-contact, couplant-free and nondestructive technique, the laser ultrasonic technology has great potential for detecting surface defects. In this paper, we propose a surface defect identification method based on broadband laser-generated Rayleigh wave with wavenumber filtering in an area scanning mode. Firstly, a particular lowpass filter is constructed in frequency-wavenumber domain to extract the scattered wave generated by the defects, and then a surface defect image can be reconstructed based on the broadband scattered wave wavenumbers. Secondly, a threshold denoising method is employed to enhance the signal-to-noise ratio and improve the image sharpness. Thirdly, the experimental validation is carried out, in which a laser ultrasonic detection system is used to detect the surface defects of aluminum alloy specimens and identify their different parameters. The experimental results verify that the proposed method can identify the location, size and orientation of surface defects effectively, meanwhile, its imaging effect shows significantly superior to that of the conventional reflected wave energy and standing wave energy methods. Furthermore, the correlation between maximum local scattered wave energy and the depth of defects is found, which can characterize the severity of the surface defects.

Acoustic resonance mechanism for axisymmetric screech modes of underexpanded jets impinging on an inclined plate

In this paper, the acoustic resonance mechanism for different axisymmetric screech modes of the underexpanded jets that impinge on an inclined plate is investigated experimentally. The ideally expanded Mach number of jets ( $M_j$ ) ranges from 1.05 to 1.56. The nozzle-to-plate distance at the jet axis and the impingement angle are respectively set as 5.0 $D$ and $30^{\circ }$ , where $D$ is the nozzle exit diameter. The acoustic results show that the $M_j$ range for the A2 screech mode of impinging jets is broader than that of underexpanded free jets, and a new axisymmetric screech mode A3 appears. With the increase of $M_j$ , the effect of the impinging plate on the shock cell structures of jets becomes obvious gradually, and the second suboptimal peaks are evident in the axial wavenumber spectra of mean shock structures. The coherent flow structures at screech frequencies are extracted from time-resolved schlieren images via the spectral proper orthogonal decomposition (SPOD). The axial wavenumber spectra of the selected SPOD modes suggest that the A1, A2 and A3 screech modes are respectively closed by the guided jet modes that are energized by the interactions between the Kelvin–Helmholtz wavepacket and the first three shock wavenumber peaks. The upstream- and downstream-propagating waves that constitute the screech feedback loop are analysed by applying wavenumber filters to the wavenumber spectra of SPOD modes. The frequencies of these three screech modes can be predicted by the phase constraints between the nozzle exit and the rear edge of the third shock cell. For the A3 mode, the inclined plate invades the third shock cell with the increase of $M_j$ , and the phase constraint cannot be satisfied at the lower side of the jets, which leads the A3 mode to fade away. The present results suggest that external boundaries can modulate the frequency and mode of jet screech by changing the axial spacings of shock cells.

Principle and Experimental Study of Flow Noise Reduction for Underwater Vehicle Hull-Mounted Sonar

When the underwater vehicle is sailing at high speed, the noise of flow becomes one of the principal background noises of the hull-mounted sonar, and suppressing the flow noise is an important way to further develop the detection execution of the hull-mounted sonar. In this paper, by establishing a physical model for the analysis of flow noise, The theoretical calculation of the fluctuating level of noise acquired by a plane element sensor imbedded in an rubbery layer is performed, and the impact of different wave-number filter elements such as sensor receiving area and rubbery layer on reducing turbulent noise is discussed, and then, the effectiveness of the flow noise reduction is verified through the measurement in a large-scale flow noise test tunnel.

Small-data-driven fast seismic simulations for complex media using physics-informed Fourier neural operators

Deep learning (DL) seismic simulations have become a leading-edge field that could provide an effective alternative to traditional numerical solvers. We have developed a small-data-driven time-domain method for fast seismic simulations in complex media based on the physics-informed Fourier neural operator (FNO). Unlike most DL-based modeling schemes that either solve wave equations by embedding the physical constraints into the cost function or conduct physics-informed learning by incorporating the wave functions into convolutional neural networks (CNNs), the FNO uses a learning architecture similar to the structure of split-step Fourier wave propagators, which is composed of two CNNs formulated in the space and wavenumber domains, respectively. The space-domain CNN acts as a local trainable phase-screen compensation. The wavenumber-domain CNN represents a nonlocal spatial convolutional operator acting as a trainable wavenumber filter for the phase-shift process. The FNO method approximates the mathematical-physical behavior of wave equations through learning the mapping between seismic wavefields at different time/locations from training seismic data. That is, the learning process parameterizes the integral kernel directly in the Fourier space, so that we can establish an expressive and efficient architecture for a better balance between accuracy and performance than the traditional spatial CNNs. Applications to gradient, layered, and Marmousi velocity models demonstrate its performance in accuracy and efficiency. The FNO seismic simulation is a data-driven method that needs a small amount of training data, especially when using blended source training data. It is a discretization-independent method that is not subject to the limitation of spatial sampling and time steps imposed on traditional numerical solvers, implying that the training data can be discretized arbitrarily. It also is a model-independent method that can include absorption attenuation into seismic modeling without the need of viscoelastic wave equations.

On the accuracy and spatial sampling of finite-difference modelling in discontinuous models

Finite-difference modelling estimates the wavefield in the subsurface by solving the elastic or acoustic wave equation numerically in a discrete version of the subsurface. The derivatives in the wave equation are approximated by their finite-difference counterparts. In this paper, we investigate the accuracy of acoustic finite-difference modelling as a function of the spatial sampling rate, the frequency, the source-receiver offset and the model parameters and parametrisation. To represent discontinuities in a regular grid, we apply a tapered low-pass wavenumber filter to densely sampled compliance and density models using the Nyquist wavenumber of the desired grid as cut-off wavenumber. A long filter taper improves the finite-difference modelling accuracy but also leads to longer oscillations in the model grids. We use a 2D acoustic central-grid pseudospectral scheme and compare it to analytical solutions of the wave equation and the reflectivity method. We show that previous recommendations for the spatial sampling of four grid points per shortest wavelength in staggered-grid schemes also apply to central-grid schemes. In the case of a single thin layer, the accuracy of finite-difference modelling is dependent on the impedance contrast and the layer thickness. For accurate wide-angle reflection amplitudes of a thin layer with a strong impedance contrast, a denser grid sampling than four grid points per shortest wavelength is required. Furthermore, we demonstrate that the presented wavenumber filtering approach is better suited for the downsampling of regularly sampled compliance and density data derived from well logs than Backus averaging.

Wide-angle formulation of the Beilis-Tappert method

The theory and numerical examples are given for a wide-angle formulation of the Beilis-Tappert method for wave propagation over irregular terrain. The vertical wave number k in the Beilis-Tappert method is not a physical wave number. Consequently, an essential but previously unknown element of the Beilis-Tappert method is the need to use a slope-dependent k-space vertical wave number filter. The filter selects the physical vertical wave numbers in k-space integrals. The importance of the vertical wave number filter (“k-control”) is demonstrated theoretically and numerically for propagation over a steep hill and over a shallow hill. For the steep hill, it is shown that k-control is as important as the extension to wide angles. For the shallow hill, k-control and the wide-angle extension are much less important, so that, for some applications, the original narrow-angle formulation gives acceptable accuracy.

De-noising distributed acoustic sensing data using an adaptive frequency–wavenumber filter

Summary Data recorded by distributed acoustic sensing (DAS) along an optical fibre sample the spatial and temporal properties of seismic wavefields at high spatial density. Often leading to massive amount of data when collected for seismic monitoring along many kilometre long cables. The spatially coherent signals from weak seismic arrivals within the data are often obscured by incoherent noise. We present a flexible and computationally efficient filtering technique, which makes use of the dense spatial and temporal sampling of the data and that can handle the large amount of data. The presented adaptive frequency–wavenumber filter suppresses the incoherent seismic noise while amplifying the coherent wavefield. We analyse the response of the filter in time and spectral domain, and we demonstrate its performance on a noisy data set that was recorded in a vertical borehole observatory showing active and passive seismic phase arrivals. Lastly, we present a performant open-source software implementation enabling real-time filtering of large DAS data sets.

Application of the multi potential geophysical techniques for groundwater evaluation in a part of Central Sinai Peninsula_ Egypt

This study highlights the groundwater evaluation of the Nubian sandstone aquifers regarding assessing the main structural elements, trends, and depth to the basement rocks that control the groundwater aquifers in Egypt's central Sinai area. Gravity and magnetic data were analyzed using different techniques, such as wavenumber filtering, least-squares separation techniques, and tilt derivatives. Euler deconvolution with different structural indexes (SI), power spectrum analyses, 3-D crustal modeling. The deep-seated structures affecting the study area, and the basement depth, which range between 1170 and 4590 m., have been utilized. The main structural trends affecting the study area were delineated to control the groundwater aquifer's regional geometry. Moreover, it was found that the NorthWest-SouthEast trend direction – Suez Gulf trend – was caused by primary shear, and the NorthEast-SouthWest trend direction – Aqaba Gulf trend – was caused by the secondary shear. The direction of each trend's lateral movement was to the right and the left, respectively. Meanwhile, the geoelectrical resistivity measurements were also utilized to determine the ground water-bearing formations using eighteen deep vertical electrical soundings (VES) stations. The results revealed the depth to the uppermost part of the Nubian sandstone aquifer ranging between 598 and 1106 m; the combination of the depth to the uppermost part of the Nubian aquifer, the depth of the basement relief map revealed that the aquifer thickness varies from 430 to 3750 m, and the resistivity values ranging between 22 and 214 Ω.m.

Two-dimensional (2D) dynamic vibration optical coherence elastography (DV-OCE) for evaluating mechanical properties: a potential application in tissue engineering.

Mechanical properties in tissues are an important indicator because they are associated with disease states. One of the well-known excitation sources in optical coherence elastography (OCE) to determine mechanical properties is acoustic radiation force (ARF); however, a complicated focusing alignment cannot be avoided. Another excitation source is a piezoelectric (PZT) stack to obtain strain images via compression, which can affect the intrinsic mechanical properties of tissues in tissue engineering. In this study, we report a new technique called two-dimensional (2D) dynamic vibration OCE (DV-OCE) to evaluate 2D wave velocities without tedious focusing alignment procedures and is a non-contact method with respect to the samples. The three-dimensional (3D) Fourier transform was utilized to transfer the traveling waves (x, y, t) into 3D k-space (kx, ky, f). A spatial 2D wavenumber filter and multi-angle directional filter were employed to decompose the waves with omni-directional components into four individual traveling directions. The 2D local wave velocity algorithm was used to calculate a 2D wave velocity map. Six materials, two homogeneous phantoms with 10 mm thickness, two homogeneous phantoms with 2 mm thickness, one heterogeneous phantom with 2 mm diameter inclusion and an ex vivo porcine kidney, were examined in this study. In addition, the ARF-OCE was used to evaluate wave velocities for comparison. Numerical simulations were performed to validate the proposed 2D dynamic vibration OCE technique. We demonstrate that the experimental results were in a good agreement with the results from ARF-OCE (transient OCE) and numerical simulations. Our proposed 2D dynamic vibration OCE could potentially pave the way for mechanical evaluation in tissue engineering and for laboratory translation with easy-to-setup and contactless advantages.

Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods

Abstract. Gravity waves are important drivers of dynamic processes in particular in the middle atmosphere. To analyse atmospheric data for gravity wave signals, it is essential to separate gravity wave perturbations from atmospheric variability due to other dynamic processes. Common methods to separate small-scale gravity wave signals from a large-scale background are separation methods depending on filters in either the horizontal or vertical wavelength domain. However, gravity waves are not the only process that could lead to small-scale perturbations in the atmosphere. Recently, concerns have been raised that vertical wavelength filtering can lead to misinterpretation of other wave-like perturbations, such as inertial instability effects, as gravity wave perturbations. In this paper we assess the ability of different spectral background removal approaches to separate gravity waves and inertial instabilities using artificial inertial instability perturbations, global model data and satellite observations. We investigate a horizontal background removal (which applies a zonal wavenumber filter with additional smoothing of the spectral components in meridional and vertical direction), a sophisticated filter based on 2D time–longitude spectral analysis (see Ern et al., 2011) and a vertical wavelength Butterworth filter. Critical thresholds for the vertical wavelength and zonal wavenumber are analysed. Vertical filtering has to cut deep into the gravity wave spectrum in order to remove inertial instability remnants from the perturbations (down to 6 km cutoff wavelength). Horizontal filtering, however, removes inertial instability remnants in global model data at wavenumbers far lower than the typical gravity wave scales for the case we investigated. Specifically, a cutoff zonal wavenumber of 6 in the stratosphere is sufficient to eliminate inertial instability structures. Furthermore, we show that for infrared limb-sounding satellite profiles it is possible as well to effectively separate perturbations of inertial instabilities from those of gravity waves using a cutoff zonal wavenumber of 6. We generalize the findings of our case study by examining a 1-year time series of SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) data.

Non-destructive evaluation of isotropic plate structures by means of mode filtering in the frequency-wavenumber domain

Non-Destructive Testing (NDT) techniques are prevalent in the aerospace, green energy and automotive industries. These techniques, including ultrasound, despite their use, still have limitations surrounding speed and resolution. This work presents the development of a band-pass mode filtering technique in the frequency wavenumber domain for the purpose of damage detection in isotropic materials. Data was captured in the temporal and spatial domain using a 3D Scanning Laser Doppler Vibrometer (SLDV) with piezoelectric transducers exciting the structure with a variety of steady state signals ranging in frequency from 75 kHz to 400 kHz and a frequency modulated signal from 75 kHz to 400 kHz. A thickness map was created based on the frequency and wavelength of the A0 Lamb wave mode. The technique was demonstrated on two aluminium specimens with dimensions of 400 mm by 400 mm with a thickness range of 0.5 mm to 8 mm with distinct geometric features. Through using multi-frequency excitation combined with mode based filters an estimation of thickness was achieved with a mean percentage thickness error of 15%. Circular thickness reductions with a diameter of 10 mm were clearly identified at the maximum plate thickness of 8 mm. This technique was shown to perform better than wavenumber filtering by allowing data from multi frequency steady state excitation to be combined into a single resulting thickness map. This improvement was shown to be particularly important at greater thicknesses.

Local Phase Velocity Based Imaging of Viscoelastic Phantoms and Tissues.

Assessment of soft tissue elasticity and viscosity is of interest in several clinical applications. In this study, we present the feasibility of the local phase velocity based imaging (LPVI) method to create images of phase velocity and viscoelastic parameters in viscoelastic tissue-mimicking materials and soft tissues. In viscoelastic materials, it is necessary to utilize wave-mode isolation using a narrow bandpass filter combined with a directional filter in order to robustly reconstruct phase velocity images with LPVI in viscoelastic media over a wide range of frequencies. A pair of sequential focused acoustic radiation force push beams, focused once on the left-hand side and once on the right-hand side of the probe, was used to produce broadband propagating shear waves. The local shear wave phase velocity is then recovered in the frequency domain for multiple frequencies, for both acquired data sets. Then, a 2-D shear wave velocity map is reconstructed by combining maps from two separate acquisitions. By testing the method on simulated data sets and performing in vitro phantom and in vivo liver tissue experiments, we show the ability of the proposed technique to generate shear wave phase velocity maps at various frequencies in viscoelastic materials. Moreover, a nonlinear least-squares problem is solved in order to locally estimate elasticity and viscosity parameters. The LPVI method with added directional and wavenumber filters can produce phase velocity images, which can be used to characterize the viscoelastic materials.

Recurrent Synoptic-Scale Rossby Wave Patterns and Their Effect on the Persistence of Cold and Hot Spells

AbstractThe persistence of surface weather during several recent high-impact weather events has been pivotal in generating their societal impact. Here we examine Hovmöller diagrams of the 250-hPa meridional wind during several periods with particularly persistent surface weather and find a common pattern in these Hovmöller diagrams. This pattern can be characterized as a “recurrent Rossby wave pattern” (RRWP), arising from multiple transient synoptic-scale wave packets. During such RRWP periods, individual troughs and ridges forming the wave packets repeatedly amplify in the same geographical region. We discuss the synoptic evolution of two RRWP periods, in February–March 1987 and July–August 1994, and illustrate how the recurrence of the transient wave packets led to unusually long-lasting cold and hot spells, which occurred simultaneously in several regions, each separated by roughly one synoptic wavelength. Furthermore, a simple index termedRis proposed to identify RRWPs, which is based on both a time and wavenumber filter applied to conventional Hovmöller diagrams. A Weibull regression analysis then shows that large values ofRare statistically significantly linked to increased durations of winter cold and summer hot spells in large areas of the Northern Hemisphere midlatitudes. Traditionally, persistent high-impact surface weather has often been linked to the occurrence of proximate atmospheric blocking. In contrast to blocking, RRWPs affect persistent surface temperature anomalies over multiple synoptic wavelengths. We therefore argue that, in addition to blocking, RRWPs should be considered as an important flow feature leading to persistent high-impact surface weather.

Research on Morlet Wavelet Based Lamb Wave Spatial Sampling Signal Optimization Method

In recent years, Lamb wave and piezoelectric transducers (PZTs) array based wavenumber filtering technique for damage estimation has been gradually studied. Compared with the time domain and frequency domain analysis of the Lamb wave signals, the wavenumber domain analysis is an effective approach to distinguish wave propagating direction and wave modes. However, the spatial resolution sampled by the PZTs is lower than that sampled by scanning laser Doppler vibrometer. As for the diameter of the PZT, it cannot be very small. In this paper, a new Lamb wave spatial sampling signal optimization method based on Morlet wavelet is proposed. Firstly, the frequency band parameter of the Morlet mother wavelet function is calculated by the Lamb wave excitation signal. Then, the sum of squared errors between the Lamb wave spatial sampling signal and the Morlet wavelet function fitting waveform at each scale factor and time factor is calculated. Finally, the scale factor and time factor corresponding to the least sum of squared errors can be judged to be the best match scale factor and time factor respectively, and the Morlet wavelet function fitting waveform in that scale factor and time factor can be seen as the optimized Lamb wave spatial sampling signal. The validation experiment performed on a glass fiber epoxy composite plate shows that the proposed method can improve the spatial resolution and length of the Lamb wave spatial sampling signal, and the sum of squared errors of this method is no more than 0.2.

On modified wavenumber filters for rail contribution estimations.

This brief communication exposes an overview of various wavenumber filters to separate the rail contribution to pass-by noise via the wave signature extraction method [Zea, Manzari, Squicciarini, Feng, Thompson, and Lopez Arteaga, J. Sound Vib. 409, 24-42 (2017)]. It has been found that the originally proposed filters underestimate the rail noise at frequencies above 1.6 kHz due to the presence of higher-order wave families that is unaccounted for. The goal of this letter is thus to propose and examine different filter functions that can capture such waves, and to assess whether the rail contribution estimations can be improved.