Time-reversal Multiple Signal Classification Research Articles

Green function based ultrasonic super resolution imaging for defect location and characterization

Green function is the important component for ultrasonic time reversal based super resolution imaging methods. Time reversal with multiple signal classification (TR-MUSIC) and its phase-coherent form (PC-MUSIC) are two typical imaging methods. In this paper, the effect of Green function on the TR-MUSIC and PC-MUSIC has been investigated. And TFM has also been introduced as a comparison. Point spread function modelling has been implemented to compare the performance of imaging methods under different forms of Green function via simulation. Several experiments have been implemented on metallic samples with defects. The defects can be divided into two categories: point-like targets and extended targets, depending on their relationship with the ultrasonic central wavelength. The perform of imaging methods under different forms of Green function has been compared in terms of lateral resolution, axial resolution, robustness to the noise and imaging for extended targets. A series of parameters have been defined to achieve quantitative comparison. The experimental results show that when compared with TR-MUSIC, PC-MUSIC is sensitive to the Green function. When the proper combination including Green function, the frequency bandwidth as well as the dimension of signal subspace has been setup, the defect can be correctly located and accurately quantitative evaluated based on the PC-MUSIC image.

Step Frequency TR-MUSIC for Soft Fault Detection and Location in Coaxial Cable

Soft faults in cables may trigger short circuits and open circuits in time, in that, they ought to be detected and thus eliminated at an earliest possible stage, as to ensure safe and stable operation of the cables. A method called the time-reversal multiple signal classification (TR-MUSIC) had been proposed in the literature, which has been demonstrated to be an effective technique for locating soft faults in cables, owing to its high resolution and excellent noise robustness. However, traditional TR-MUSIC relies on a vector network analyzer for measuring the scattering matrix of cables, which adds cost and complexity to its implementation. In this regard, a new way of acquiring the desired scattering parameters is herein proposed. An arbitrary function generator is used to inject incident signals into the cable under test, and an oscilloscope is used to collect the reflected signals. After post-processing, the phase of scattering parameters can be obtained. There’s another key issue in the image of the detection results, ghost traces caused by the periodicity of Green’s function severely impact the vision saliency of the actual fault location, which limits the performance of the fault location. A step frequency variant of TR-MUSIC has been proposed, therefore, to mitigate ghost traces. Experimental results show that the fault location error of the proposed approach is smaller than 0.33% for a 51-m long coaxial cable. Moreover, in the case of introducing noise, the proposed approach can operate in situations with signal-to-noise ratios as low as –6 dB.

Ultrasonic time-reversal-based super resolution imaging for defect localization and characterization

In this paper, time reversal with multiple signal classification (TR-MUSIC) and its phase-coherent form (PC-MUSIC), the two typical ultrasonic time-reversal-based super resolution imaging techniques, have been introduced and explored to image defects in metallic samples. The principles for super resolution imaging technique and defect characterization based on ultrasonic image have been presented firstly. And then both TR-MUSIC and PC-MUSIC are tested with experimental ultrasonic array data acquired from the metallic samples including defects using the full matrix capture (FMC) process. Here, if the size of defect is smaller than the central ultrasonic wavelength, the defect can be regarded as point-like target. On the contrary, if the size of defect is larger than the central ultrasonic wavelength, it can be regarded as extended target. The comparison on super resolution imaging for point-like and extended targets has been investigated. For point-like targets, TR-MUSIC as well as PC-MUSIC can distinguish and locate the position, and the overall performance of TR-MUSIC is better than that of PC-MUSIC. For extended target, TR-MUSIC can only determine the area where the defect occurs. PC-MUSIC can distinguish and assess the length of extended target parallel to the array, the lowest error is 9.62% when the dimension of signal subspace is set to be 10 for the case considered. In addition, the defect characterization based on ultrasonic super-resolved image has been studied, and a sizing strategy is introduced. The length and angle of extended targets oblique to the array can be obtained from the PC-MUSIC images. The worst errors for assessing the length and angel are 9.14% and 13.3% respectively. And for the cases considered in the experiment, the longer the length of extended target, the smaller the error.

A Local TR-MUSIC Algorithm for Damage Imaging of Aircraft Structures.

Lamb wave-based damage imaging is a promising technique for aircraft structural health monitoring, as enhancing the resolution of damage detection is a persistent challenge. In this paper, a damage imaging technique based on the Time Reversal-MUltiple SIgnal Classification (TR-MUSIC) algorithm is developed to detect damage in plate-type structures. In the TR-MUSIC algorithm, a transfer matrix is first established by exciting and sensing signals. A TR operator is constructed for eigenvalue decomposition to divide the data space into signal and noise subspaces. The structural space spectrum of the algorithm is calculated based on the orthogonality of the two subspaces. A local TR-MUSIC algorithm is proposed to enhance the image quality of multiple damages by using a moving time window to establish the local space spectrum at different times or different distances. The multidamage detection capability of the proposed enhanced TR-MUSIC algorithm is verified by simulations and experiments. The results reveal that the local TR-MUSIC algorithm can not only effectively detect multiple damages in plate-type structures with good image quality but also has a superresolution ability for detecting damage with distances smaller than half the wavelength.

Robust and Low-Complexity Time-Reversal Subspace Decomposition Methods for Acoustic Emission Imaging and Localization

This article focuses on the acoustic emission (AE) localization problem in the complex and unknown probed domain. The schemes based on time-reversal (TR) theorem are proposed to achieve accurate imaging and localization, even when there is no accurate priori knowledge of the Green's functions. In the proposed strategies, a signal enhancement method is proposed to de-noise sensor wavefields from single or multiple sources firstly. Then the wideband signal matrix is condensed into a single frequency matrix by coherent processing. The steering vectors are estimated based on minimizing noise variance. And by incorporating the steering vector estimation algorithm into the subspace decomposition-based methods, two novel robust imaging methods, robust coherent Decomposition of the time-reversal operator (R-DORT) and robust coherent time-reversal Multiple signal classification (R-TR-MUSIC), are presented. The performance of the proposed methods is evaluated using simulation studies that consider two background mismatches and different levels of signal-to-noise ratio (SNR) respectively. The simulation results demonstrate the effectiveness and the superiority of the presented methods in locating AE sources under the complex and uncertain circumstances. Moreover, the localization results based on experimental data show the potential of the proposed methods in practical applications.

Ultrasonic multi-frequency time-reversal-based imaging of extended targets

In this paper, two multi-frequency time-reversal-based imaging methods, time reversal with multiple signal classification (TR-MUSIC) and its phase-coherent form (PC-MUSIC), are explored for application to the non-destructive testing (NDT) imaging of extended target machined in solids. The size of which is on the order of the ultrasonic wavelength or larger. The principle for multi-frequency TR-based imaging method is presented, and the performance is estimated in terms of point spread function (PSF). Both TR-MUSIC and PC-MUSIC are tested with experimental ultrasonic array data acquired using the full matrix capture (FMC) process. Two experiments in metal solids with different kind of defect, side-drilled hole (SDH) as well as electrical discharge machining (EDM) lines that can be considered as extended targets, were implemented. Here, the EDM lines have different positional relationships with array. For SDH, it is shown that both TR-MUSIC and PC-MUSIC can locate the position, but fail to distinguish the shape. For EDM lines, TR-MUSIC can only detect the defect, but PC-MUSIC can assess the length based on the imaging results under some dimension of signal subspace. In addition, the effect of dimension of signal subspace on the imaging methods is also investigated, and it is shown that TR-MUSIC is sensitive to the dimension when compared with PC-MUSIC.

Super-resolution radar imaging for breast cancer detection with microwaves: the integrated information selection criteria.

This paper focuses on the data preprocessing scheme, as well as on the frequency selection and spatial filtering modules integrated with a Time-Reversal Multiple Signal Classification (TR-MUSIC) algorithm, for microwave breast imaging. This algorithm is part of the data processing chain of the Wavelia Microwave Breast Imaging (MBI) system prototype, which has been recently installed at the University Hospital of Galway, Ireland, for a first-in-human clinical trial. Indicative results from application of the algorithm on an experimental phantom dataset, and on a first patient dataset, are presented in this paper. Good correspondence between the two datasets is demonstrated, confirming the validity of the experimental setup used so far for the on-site acceptance of the Wavelia system, after installation at the hospital for clinical testing.

Sizing Subwavelength Defects With Ultrasonic Imagery: An Assessment of Super-Resolution Imaging on Simulated Rough Defects.

There is a constant drive within the nuclear power industry to improve upon the characterization capabilities of current ultrasonic inspection techniques in order to improve safety and reduce costs. Particular emphasis has been placed on the ability to characterize very small defects which could result in extended component lifespan and help reduce the frequency of in-service inspections. Super-resolution (SR) algorithms, also known as sampling methods, have been shown to demonstrate the capability to resolve scatterers separated by less than the diffraction limit when deployed in representative inspections and therefore could be used to tackle this issue. In this paper, the factorization method (FM) and the Time Reversal Multiple-Signal-Classification (TR-MUSIC) algorithms are applied to the simulated ultrasonic array inspection of small rough embedded planar defects to establish their characterization capabilities. Their performance was compared to the conventional total focusing method (TFM). A full 2-D finite-element (FE) Monte Carlo modeling study was conducted for defects with a range of sizes, orientations, and magnitude of surface roughness. The results presented show that for subwavelength defects, both the FM and TR-MUSIC algorithms were able to size and estimate defect orientation accurately for smooth cases and, for rough defects, up to a roughness of 100 [Formula: see text]. This level of roughness is representative of the thermal fatigue defects encountered in the nuclear power sector. This contrasted with the relatively poor performance of TFM in these cases which consistently oversized these defects and could not be used to estimate the defect orientation, making through-wall sizing with this method impossible.

Loose bolt detection in a complex assembly using a vibro-acoustic sensor array

Abstract A non-destructive testing strategy is proposed that combines microphone measurements and structural measurements in one array. The aim is to lower the total inspection time by reducing the number of structural sensors. This is possible by making use of the easier and faster installation of microphones as compared to structural sensors. Structural sensors are needed to limit the influence of background noise. The proposed algorithm is based on the theory of the Time-Reversal MUltiple SIgnal Classification (TR-MUSIC) algorithm. In addition to the novelty of using a vibro-acoustic array, this publication presents a strategy on how to select only the most ‘valuable’ regions of the frequency spectrum for the TR-MUSIC algorithm and an option to use the algorithm with a number of excitations below the theoretically necessary minimum. The proposed procedure is applied in an experiment that targets the localisation of loose or removed bolts in an assembly of aluminium beams and a honeycomb panel, mounted with rivets, bolts and double-sided tape. Although none of the bolts is in the line of sight of the sensor array, all introduced defects can be found in this experiment. This includes the localisation of multiple defects as well. By adding artificial measurement noise to the microphone measurements, it is demonstrated that a combined vibro-acoustic array can cope with a high ambient noise level, while the process fails if a comparable measurement error is also applied to the structural sensors.

Multifrequency TR-MUSIC Processing to Locate Soft Faults in Cables Subject to Noise

Time-reversal multiple signal classification (TR-MUSIC) has recently been shown to be an effective technique to locate multiple soft faults in wire networks, thanks to its sub-millimeter location accuracy. TR-MUSIC processes transmission and reflection data measured at a single frequency into a function of space, the pseudo spectrum, expected to present singularities only at a fault position. At frequencies high enough, the spatial periodicity that comes with the propagation of harmonic signals leads to multiples of such singularities, of which only one represents the fault position, while the remaining are ghosts faults. TR-MUSIC was therefore introduced using a single continuous-wave excitation at frequencies low enough to avoid ghosts, an approach suitable only for noiseless configurations. This paper explores the effects of noise on TR-MUSIC fault location by first highlighting its high sensitivity to noise at low frequency. A potentially lower sensitivity is shown to exist at high frequencies, where ghosts positions are found. A multifrequency processing is introduced, allowing at the same time to solve the ambiguity in the fault position and to effectively control the impact of noise on its location accuracy. The proposed processing is shown to reinstate precise super-resolved estimates of fault locations even for signal-to-noise ratios as low as 5 dB, without requiring the use of wideband signals.

Axial localization using time reversal multiple signal classification in optical scanning holography.

This paper presents a method to identify the axial location of targets in an optical scanning holography (OSH) system. By combining time reversal (TR) technique with the multiple signal classification (MUSIC) method in OSH, axial location can be detected with high resolution. Both simulation and experimental work have been carried out to verify the feasibility of the proposed work.

Soft Fault Diagnosis in Wire Networks Using Time Reversal Concept and Subspace Methods

Time-reversal (TR) techniques recently adopted from acoustics to guided wave propagation along transmission lines have proven to be effectual in locating soft faults in different wire network configurations. In this paper, we apply the TR multiple signal classification (TR-MUSIC) technique to cable testing. TR-MUSIC is shown to provide spatial resolutions in the mm range, while using continuous-wave test signals. On the contrary, the well known time-domain reflectometry (TDR) methods would require large bandwidths in the order of gigahertz for a similar performance. The TR-MUSIC accuracy is demonstrated experimentally for locating both single and multiple soft faults in several cable networks.

Non-destructive testing based on vibrations in the low to mid-frequency range

Recently, it has been shown that a Time Reversal MUltiple Signal Classification (TR-MUSIC) algorithm can be employed to detect defects in samples, which are both challenging in terms of material and in terms of geometrical complexity. This can be achieved by lowering the detection frequency as compared to most other TR and TR-MUSIC applications. In this case, the method operates in a low to mid-frequency range, where accurate models are still realizable. The method relies on the measurement of the frequency response function (FRF) between multiple excitation and sensor locations. These are gathered in a matrix, which then is decomposed in its singular vectors, serving as input for a MUSIC algorithm. In order to improve the applicability of this method, it is shown how to adapt the algorithm, in order to reduce the number of excitation locations or the number of sensors significantly. This results in a considerable speed-up for the application of this non-destructive testing strategy. Furthermore, it is investigated numerically how the robustness of the detection result under the influence of random measurement errors behaves if the number of excitation/sensor locations is reduced. Additionally, the dependency between, the decrease of the number of excitation/sensor locations and the types of defects, which can be detected is studied.

Locating Faults With High Resolution Using Single-Frequency TR-MUSIC Processing

Time-reversal multiple signal classification (TR-MUSIC) is here applied to testing cable networks in order to detect and locate soft faults. TR-MUSIC is shown to provide spatial resolution in the millimeter range while using continuous-wave (CW) test signals, even at frequencies with guided wavelengths much larger than cables length. State-of-the-art time-domain reflectometry (TDR) methods would require bandwidths in the order of hundreds of megahertz for a similar performance. As opposed to TDR, TR-MUSIC does not suffer from the ambiguity created by the existence of multiple echoes in cable networks, which can be easily misinterpreted as multiple faults, leading to false alarms. TR-MUSIC is intrinsically adapted to dealing with multiple faults, handing a direct estimate of the number of faults found in a network under test. Furthermore, the detection capabilities of TR-MUSIC are insensitive to the severity of a fault, as faults are not detected based on the intensity of their echoes as done in TDR techniques, but on a subspace approach mostly dependent on phase patterns. Accurate identification of faults from CW signals points to the possibility of designing simpler test systems, not requiring pulse generators and fast electronics. TR-MUSIC accuracy is demonstrated experimentally for locating both single as well as multiple soft faults in two cable networks. The proposed method also gives access to the reflection coefficient of each fault, thus enabling an estimate of its severity.

Efficient hybrid method for time reversal superresolution imaging

An efficient hybrid time reversal (TR) imaging method based on signal subspace and noise subspace is proposed for electromagnetic superresolution detecting and imaging. First, the locations of targets are estimated by the transmitting-mode decomposition of the TR operator (DORT) method employing the signal subspace. Then, the TR multiple signal classification (TR-MUSIC) method employing the noise subspace is used in the estimated target area to get the superresolution imaging of targets. Two examples with homogeneous and inhomogeneous background mediums are considered, respectively. The results show that the proposed hybrid method has advantages in CPU time and memory cost because of the combination of rough and fine imaging.

Iterative angle-and-time-domain gating technique for time-reversal MUSIC imaging

This study develops the preprocessing theory for time-reversal multiple signal classification (TR-MUSIC) imaging from the one-dimensional (time-domain) gating proposed in earlier papers to a two-dimensional one. Although the one-dimensional gating technique for TR-MUSIC mitigates the effect of noise as well as reduces the required number of antenna elements, the resulting image is subject to focusing errors when there are many targets in the gated region. In this paper, we propose a two-dimensional (angle-and-time-domain) gating technique based on the fast Fourier transform (FFT) and spatial FFT processing. By using these transforms and gating iteratively, we can reduce the number of targets to be detected at one time. The TR-MUSIC technique for the gated data provides more reliable images and precisely estimated coordinates compared with the previous work.

Multi-frequency time-reversal-based imaging for ultrasonic nondestructive evaluation using full matrix capture.

In this paper, two multi-frequency time-reversal (TR)-based imaging algorithms are explored for application to the nondestructive evaluation (NDE) imaging of defects in solids: time reversal with multiple signal classification (TRMUSIC) and a related phase-coherent form (PC-MUSIC). These algorithms are tested with simulated and experimental ultrasonic array data acquired using the full matrix capture (FMC) process. The performance of these algorithms is quantified in terms of their spatial resolution and robustness to noise. The effect of frequency bandwidth is investigated and the results are compared with the single-frequency versions of these algorithms. It is shown that both TR-MUSIC and PCMUSIC are capable of resolving lateral targets spaced closer than the Rayleigh limit, achieving super-resolution imaging. TR-MUSIC can locate the positions of scatterers correctly, whereas the results from PC-MUSIC are less clear because of the presence of multiple peaks in the vicinity of target. However, an advantage of PC-MUSIC is that it can overcome the elongated point spread function that appears in TR-MUSIC images, and hence provide enhanced axial resolution. For high noise levels, TR-MUSIC and PC-MUSIC are shown to provide stable images and suppress the presence of artifacts seen in their single-frequency equivalents.

Time-Reversal Imaging Using One Transmitting Antenna Based on Independent Component Analysis

Time-reversal (TR) techniques have shown promising results for detection and localization of scatterers in multiple scattering environments. These techniques exploit the TR invariance of the wave equation. Most of TR applications require the analysis of the TR operator obtained from the MDM of a TR array. Eigenvalue decomposition of the TR operator forms the basis of techniques such as decomposition of the TR operator and TR multiple signal classification. In this letter, we have introduced a new approach that is based on the independent component analysis (ICA). The ICA takes advantage of the statistical independence of scattered signals from well-resolved scatterers and breaks the mixed received signal by each receiving antenna to independent components based on maximizing the non-Gaussianity of mixed signal components. Some preprocessing steps such as centering and whitening are also required. One advantage of the TR imaging based on ICA is that imaging and focusing can be achieved using only one transmitting antenna, which lowers the complexity of the implementation compared with other techniques.

Super-resolution ultrasound imaging using a phase-coherent MUSIC method with compensation for the phase response of transducer elements.

Time-reversal with multiple signal classification (TR-MUSIC) is an imaging method for locating point-like targets beyond the classic resolution limit. In the presence of noise, however, the super-resolution capability of TR-MUSIC is diminished. Recently a new method, phase-coherent MUSIC (PC-MUSIC), was developed. This algorithm modifies TR-MUSIC to make use of phase information from multiple frequencies to reduce noise effects and preserve the super resolution. PC-MUSIC however, ignores the phase response of the transducer elements. In this paper, we account for the phase response of the transducer elements in the derivation of the PC-MUSIC algorithm. Unfortunately, the phase response of the transducer elements may not be known beforehand. We develop an experimental method to estimate this response using measured signals scattered from a glass microsphere embedded in a tissue-mimicking phantom with a homogeneous background medium of a known sound speed. We use numerical simulations to illustrate that the maximum resolution achieved with PC-MUSIC is limited by the transducer bandwidth and the signal-to-noise ratio. We perform experiments on tissue-mimicking phantoms and compare images obtained with different imaging modalities, including X-ray mammography, synthetic-aperture ultrasound imaging, TR-MUSIC, and PC-MUSIC. We demonstrate the significantly improved resolving power of PC-MUSIC.

Imaging through random multiple scattering media using integration of propagation and array signal processing

Imaging of objects through complex environment is important in several applications, including imaging of hidden objects in obscuring media such as atmospheric and ocean turbulence, rough ocean surfaces, rain, fog, snow, and biological tissues. These media are often randomly varying in space and time, and statistical treatments are necessary to obtain images with useful spatial and temporal resolutions. In recent years, there has been increasing interest in using signal processing and correlation techniques to improve resolutions and to distinguish images from clutter. This paper presents several imaging techniques for objects in the presence of random media. Time-reversal MUSIC (multiple signal classification) imaging has excellent resolution when multiple scattering is small or moderate. Modified beamformer imaging has moderately high resolution even at large multiple scattering. We also include time reversal (TR) and synthetic aperture radar (SAR) imaging for comparison. The technique involves stochastic Green's function and mutual coherence function (MCF), eigenvectors of time-reversal matrix and pseudo spectrum. Numerical examples are given to show the effectiveness of these imaging techniques.