Research Overview
The following represents a very brief introduction to
both past and on-going research. All of the work referred to on this page has been published in
some fashion. Readers interested in additional details are
referred to the published works cited when the mouse hovers over the
section title (The publications are available for download from the
Publications page).
Flow Estimation with Ultrasonic Sensor Array
The
goal of this research effort was to measure flow (of a liquid or
gas) across an interface, such as a doorway, without obstructing the
interface. This was achieved by sending an ultrasonic wave
across the interface and looking at the reflected wavefront using an
array of ultrasonic sensors. From the perspective of the
sensor array, the reflected wave will appear as though it originated
from a location behind the reflector and shifted in the
direction of flow. The use of an array of ultrasonic
sensors allows this shift to be quantified, which can then be
converted to the flow rate that was present across the interface.
Relevant Publications
- J. S. Hall, "Perpendicular fluid flow measurement with a
spatial array of ultrasonic transducers", IEEE International
Ultrasonics Symposium Proceedings, pp. 741-744, 2010.
Abstract
/
Accepted
/
Published
Abstract: The challenge of remotely measuring fluid flow through a plane of interest for a wide range of velocities is addressed using an array of ultrasonic transducers. Unlike traditional transit-time ultrasonic flow measurements, the proposed method uses the angle-of-arrival of a reflected ultrasonic wave to measure flow perpendicular to the path of propagation. The use of angle-of-arrival information avoids the inherent requirement of transit-time techniques to have a non-negligible directional component of the propagation path in the flow direction. A successful proof-of-concept was developed to experimentally validate the proposed technique.
Structural Health Monitoring
The problem being addressed by the three efforts described below
is largely that of damage detection and localization in plate-like
structures using a set of permanently attached ultrasonic
transducers. The term "plate-like" is intentionally somewhat
vague, and refers to flat, thin structures, such as aircraft skins,
storage tank walls, ship hulls, bridge support gusset plates, etc.,
that are capable of supporting ultrasonic guided waves.
Ultrasonic guided waves are elastic waves that propagate along the
plate, and are of interest for structural health monitoring
applications because they are capable of propagating relatively long
distances and are sensitive to both surface and
subsurface features.
It is important to note that although the
techniques and mathematical algorithms described here are applied to
ultrasonic guided waves for structural health monitoring, they can be
adapted to a
wide range of applications and media, from seismic and sonar
applications to radar and telecommunications.
Minimum Variance Imaging
Guided wave imaging is used to graphically display the data recorded from a
set of ultrasonic transducers. Ideally, the
image can then be used to determine if the structure is damaged, and
if so, where the damage is located.
The
figure to the left was generated using the conventional
(delay-and-sum) guided
wave imaging algorithm. Data was recorded from six
piezoelectric transducers, which are arranged in an arbitrary pattern and
depicted as small, white 'o's in the image on the left. The
structure itself is a 4'x4' plate
of 1/8" thick aluminum 6061 with a 5 mm diameter through hole drilled in the plate at the
location of the '+'. The image is shown on a 20 dB color scale
normalized so that the damage location has a value of 0 dB.
By reformulating the conventional guided wave imaging algorithm
and incorporating a technique referred to as MVDR, significant
improvements in imaging performance can be obtained. The new imaging algorithm
is referred to as minimum variance imaging. The figure below illustrates minimum variance imaging
with the same data
as that used for the previous figure. It should be pointed out that the
improved imaging performance is obtained with only minor
additional computational demands.
Although this image represents a dramatic improvement over
conventional imaging, a significant amount of information is being
ignored: that of phase information. In order to use phase
information, however, the dispersive nature of the guided waves and
any variations in the transducers must be both characterized and
compensated.
Relevant Publications
- J. S. Hall and J. E. Michaels, "Minimum variance ultrasonic
imaging applied to an in situ sparse guided
wave array", IEEE Transactions on Ultrasonics,
Ferroelectrics, and Frequency Control, 57
(10), pp. 2311-2323, 2010.
Abstract
/
Accepted
/
Published
Abstract: Ultrasonic guided wave imaging with a sparse, or spatially distributed, array can detect and localize damage over large areas. Conventional delay-and-sum images from such an array typically have a relatively high noise floor, however, and contain artifacts that often cannot be discriminated from damage. Considered here is minimum variance distortionless response (MVDR) imaging, which is a variation of delay-and-sum imaging whereby weighting coefficients are adaptively computed at each pixel location. Utilization of MVDR significantly improves image quality compared with delay-and-sum imaging, and additional improvements are obtained from incorporation of a priori scattering information in the MVDR method, use of phase information, and instantaneous windowing. Simulated data from a through-hole scatterer are used to illustrate performance improvements, and a performance metric is proposed that allows for quantitative comparisons of images from a known scatterer. Experimental results from a through-hole scatterer are also provided that illustrate imaging efficacy.
- J. S. Hall, P. McKeon, L. Satyanarayan, J. E. Michaels, N.
F. Declercq, and Y. H. Berthelot, "Minimum variance guided wave
imaging in a quasi-isotropic composite plate", Smart
Materials and Structures, 20 (2), 025013, 2011.
Abstract
/
Accepted
/
Published
Abstract: Ultrasonic guided waves are capable of rapidly interrogating large, plate-like structures for both nondestructive evaluation (NDE) and structural health monitoring (SHM) applications. Distributed sparse arrays of inexpensive piezoelectric transducers offer a cost-effective way to automate the interrogation process. However, the sparse nature of the array limits the amount of information available to perform damage detection and localization. Minimum variance techniques have been incorporated into guided wave imaging to reduce the magnitude of imaging artifacts and improve imaging performance for sparse array SHM applications. The ability of these techniques to improve imaging performance is related to the accuracy of a priori model assumptions, such as scattering characteristics and dispersion. This paper reports the application of minimum variance imaging under slightly inaccurate model assumptions, such as are expected in realistic environments. Specifically, the imaging algorithm assumes an isotropic, non-dispersive, single mode propagating environment with a scattering field independent of incident angle and frequency. In actuality, the composite material considered here is not only slightly anisotropic and dispersive but also supports multiple propagating modes, and additionally, the scattering field is dependent on incident angle, scattered angle, and frequency. An isotropic propagation velocity is estimated via calibration prior to imaging to implement the non-dispersive model assumption. Imaging performance is presented under these inaccurate assumptions to demonstrate the robustness of minimum variance imaging to common sources of imaging artifacts.
- J. S. Hall and J. E. Michaels, "Computational efficiency of
ultrasonic guided wave imaging algorithms", IEEE
Transactions on Ultrasonics, Ferroelectrics, and Frequency
Control, 58 (1), pp. 244-248, 2011.
Abstract
/
Accepted
/
Published
Abstract: Guided wave imaging techniques employed for structural health monitoring (SHM) can be computationally demanding, especially for adaptive techniques such as minimum variance distortionless response (MVDR) imaging, which requires a matrix inversion for each pixel calculation. Instantaneous windowing has been shown in previous work to improve guided wave imaging performance. The use of instantaneous windowing has the additional benefit of significantly reducing the computational requirements of image generation. This paper derives a formulation for MVDR imaging using instantaneous windowing and shows that the matrix inversion associated with MVDR imaging can be optimized, reducing the computational complexity to that of conventional delay-and-sum imaging algorithms. Additionally, a vectorized approach is presented for implementing guided wave imaging algorithms, including delay-and-sum imaging, in matrix-based software packages. The improvements in computational efficiency are quantified by measuring computation time for different array sizes, windowing assumptions, and imaging methods.
- J. S. Hall, Adaptive Dispersion Compensation and Ultrasonic Imaging for Structural Health Monitoring, Georgia Institute of Technology, 2011.
Abstract
/
Download
/
Published
Abstract: Ultrasonic guided wave imaging methods offer a cost-effective mechanism to perform in situ structural health monitoring (SHM) of large plate-like structures, such as commercial aircraft skins, ship hulls, storage tanks, and civil structures. However, current limits in imaging quality, environmental sensitivities, and implementation costs, among other things, are preventing widespread commercial adoption. The research presented here significantly advances state of the art guided wave imaging techniques using inexpensive, spatially distributed arrays of piezoelectric transducers. Novel adaptive imaging techniques are combined with in situ estimation and compensation of propagation parameters; e.g., dispersion curves and transducer transfer functions, to reduce sensitivity to unavoidable measurement inaccuracies and significantly improve resolution and reduce artifacts in guided wave images. The techniques can be used not only to detect and locate defects or damage, but also to characterize the type of damage. The improved ability to detect, locate, and now characterize defects or damage using a sparse array of ultrasonic transducers is intended to assist in the establishment of in situ guided wave imaging as a technically and economically viable tool for long-term monitoring of plate-like engineering structures.
Model-Based Parameter Estimation
Model-based parameter estimation (MBPE) is an algorithm that was
developed to provide data-driven estimates of dispersion,
propagation loss, relative sensor distances, and transducer transfer
functions, with minimal a priori information. The
algorithm is unique in that it is the only method currently
available to estimate these parameters using a distributed array of
sensors (such as considered here). This is an important
feature because these parameters change with the environment
(temperature, pressure, load, etc.). By solving for all of the
parameters simultaneously and avoiding potentially erroneous a
priori information, the resulting estimates are as accurate as
possible.
Relevant Publications
- J. S. Hall and J. E. Michaels, "Model-based parameter
estimation for characterizing wave propagation in a homogeneous
medium", Inverse Problems, 27 (3),
035002, 2011.
Abstract
/
Accepted
/
Published
Abstract: A model-based algorithm is presented that uses minimal a priori information and assumptions to adaptively estimate parameters associated with propagating waves in a homogeneous medium. These parameters include transmitter and receiver transfer functions, propagation distances, dispersion, and propagation loss. The algorithm is described in a general framework that accommodates direct arrivals from two or more transmitter–receiver pairs and can be readily adapted to handle application-specific model assumptions. Experimental validation is performed with two sets of ultrasonic guided wave data that conform to two different sets of model assumptions, demonstrating the impact of these assumptions and the ability to successfully estimate model parameters in a dispersive medium.
- J. S. Hall and J. E. Michaels, "A model-based approach to
dispersion and parameter estimation for ultrasonic guided
waves", Journal of the Acoustical Society of America,
127 (2), pp. 920-930, 2010.
Abstract
/
Accepted
/
Published
Abstract: A model-based algorithm is presented that adaptively estimates in situ ultrasonic guided wave system parameters. Dispersion curves, propagation loss, transducer distances, transmitted signal, and mode weighting coefficients are estimated using minimal a priori information and assumptions. The five-part algorithm is scalable to accommodate two or more receivers and one or more propagating modes, provided that mode separation can be achieved prior to use of the algorithm. Algorithmic performance is demonstrated on signals obtained both from theoretical dispersion curves and finite element modeling. Quantitative performance curves are presented that are based on algorithmic performance from multiple simulated test cases with varying amounts of additive noise. Results show excellent agreement between estimated and actual parameters, as well as between modeled and received signals.
- J. S. Hall, Adaptive Dispersion Compensation and Ultrasonic Imaging for Structural Health Monitoring, Georgia Institute of Technology, 2011.
Abstract
/
Download
/
Published
Abstract: Ultrasonic guided wave imaging methods offer a cost-effective mechanism to perform in situ structural health monitoring (SHM) of large plate-like structures, such as commercial aircraft skins, ship hulls, storage tanks, and civil structures. However, current limits in imaging quality, environmental sensitivities, and implementation costs, among other things, are preventing widespread commercial adoption. The research presented here significantly advances state of the art guided wave imaging techniques using inexpensive, spatially distributed arrays of piezoelectric transducers. Novel adaptive imaging techniques are combined with in situ estimation and compensation of propagation parameters; e.g., dispersion curves and transducer transfer functions, to reduce sensitivity to unavoidable measurement inaccuracies and significantly improve resolution and reduce artifacts in guided wave images. The techniques can be used not only to detect and locate defects or damage, but also to characterize the type of damage. The improved ability to detect, locate, and now characterize defects or damage using a sparse array of ultrasonic transducers is intended to assist in the establishment of in situ guided wave imaging as a technically and economically viable tool for long-term monitoring of plate-like engineering structures.
Adaptive Parameter Compensation
With estimates of both the dispersive nature of the material and
the transducer transfer functions obtained from the MBPE algorithm,
parameter compensation can be performed. The figure to the
left illustrates
imaging performance achieved by (1) adaptively estimating and
compensating for dispersion and transducer variations, and (2) using
phase information in the imaging algorithm. This figure
represents a significant improvement over both of the previous
images. It should be pointed out that all three
images were generated using the same experimental data. The
only difference between the images is how the data was interpreted
and processed. The marked improvement in imaging performance
underscores both the importance of signal processing and the
potential impact that it can have.
Relevant Publications
- J. S. Hall, Adaptive Dispersion Compensation and Ultrasonic Imaging for Structural Health Monitoring, Georgia Institute of Technology, 2011.
Abstract
/
Download
/
Published
Abstract: Ultrasonic guided wave imaging methods offer a cost-effective mechanism to perform in situ structural health monitoring (SHM) of large plate-like structures, such as commercial aircraft skins, ship hulls, storage tanks, and civil structures. However, current limits in imaging quality, environmental sensitivities, and implementation costs, among other things, are preventing widespread commercial adoption. The research presented here significantly advances state of the art guided wave imaging techniques using inexpensive, spatially distributed arrays of piezoelectric transducers. Novel adaptive imaging techniques are combined with in situ estimation and compensation of propagation parameters; e.g., dispersion curves and transducer transfer functions, to reduce sensitivity to unavoidable measurement inaccuracies and significantly improve resolution and reduce artifacts in guided wave images. The techniques can be used not only to detect and locate defects or damage, but also to characterize the type of damage. The improved ability to detect, locate, and now characterize defects or damage using a sparse array of ultrasonic transducers is intended to assist in the establishment of in situ guided wave imaging as a technically and economically viable tool for long-term monitoring of plate-like engineering structures.