Joint Time-Frequency Processing of Ultrasonic Signals

The backscattered signal information in ultrasonic testing is an effective method for characterization and detection of defects in materials. The complexity of materials like composites, mixed metals, multilayered fiber-reinforced composites and materials with complex structures used in nuclear power plants and spacecraft add new challenges towards the characterization and defect detection. Due to frequency dependent scattering and attenuation the backscattered ultrasonic signal is nonstationary in character. Therefore, joint time-frequency (t-f) representations of such signals are more revealing than the standard Fourier analysis

Discrete wavelet transform realisation using run-time reconfiguration of field programmable gate array (FPGA)s

Abstract: Designing a universal embedded hardware architecture for discrete wavelet transform is a challenging problem because of the diversity among wavelet kernel filters. In this work, the authors present three different hardware architectures for implementing multiple wavelet kernels. The first scheme utilises fixed, parallel hardware for all the required wavelet kernels, whereas the second scheme employs a processing element (PE)-based datapath that can be configured for multiple wavelet filters during run-time. The third scheme makes use of partial run-time configuration of FPGA units for dynamically programming any desired wavelet filter. As a case study, the authors present FPGA synthesis results for simultaneous implementation of six different wavelets for the proposed methods. Performance analysis and comparison of area, timing and power results are presented for the Virtex-II Pro FPGA implementations

Modeling and Parameter Estimation of Ultrasonic Backscattered Echoes

Ultrasonic backscattered echoes represent not only the impulse response of the ultrasonic transducer, but also contain information pertaining to the inhomogeneity of the propagation path, effect of frequency dependent absorption and scattering, dispersion effect, and geometric shape, size and orientation of reflectors. Therefore, a well-defined modeling of the backscattered echoes leading to the estimation of arrival time, echo skewness, center frequency, and bandwidth is highly desirable for the nondestructive evaluation of materials [1]. In this paper, we model the backscattered echoes, assuming that all parameters describing the shape of the echo are unknown. Then, iterative parameter estimation techniques such as the Gauss-Newton method [2] or Simplex-Search method [3] have been applied to estimate echo parameters. These algorithms have been evaluated in terms of rate of convergence, sub-optimal estimation due to local minima, and presence of noise

Automatic Detection of User Abilities through the SmartAbility Framework

This paper presents a proposed smartphone application for the unique SmartAbility Framework that supports interaction with technology for people with reduced physical ability, through focusing on the actions that they can perform independently. The Framework is a culmination of knowledge obtained through previously conducted technology feasibility trials and controlled usability evaluations involving the user community. The Framework is an example of ability-based design that focuses on the abilities of users instead of their disabilities. The paper includes a summary of Versions 1 and 2 of the Framework, including the results of a two-phased validation approach, conducted at the UK Mobility Roadshow and via a focus group of domain experts. A holistic model developed by adapting the House of Quality (HoQ) matrix of the Quality Function Deployment (QFD) approach is also described. A systematic literature review of sensor technologies built into smart devices establishes the capabilities of sensors in the Android and iOS operating systems. The review defines a set of inclusion and exclusion criteria, as well as search terms used to elicit literature from online repositories. The key contribution is the mapping of ability-based sensor technologies onto the Framework, to enable the future implementation of a smartphone application. Through the exploitation of the SmartAbility application, the Framework will increase technology amongst people with reduced physical ability and provide a promotional tool for assistive technology manufacturers

Introduction to the special issue

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Ultrasonic Signal Enhancement Using Order Statistic and Morphological Filters

Order statistic and morphological filters belong to a class of nonlinear filters that have recently found many applications in signal analysis and image processing. In this paper, order statistic and morphological filters have been applied to enhance the features of the ultrasonic signal when it has been contaminated by multiple interfering microstructure echoes with random amplitudes and phases. These interfering echoes (i.e., speckles or grain scattering noise) often become significant to the point where detection of flaw echoes becomes very difficult. We have examined frequency diverse order statistic and time domain morphological and recursive median filters for improved ultrasonic flaw detection. In particular, the performance of these filters is evaluated using different ranks of order statistics and different shapes of structuring elements in the application of morphological filters. The processed experimental results in testing steel samples demonstrate that these filters are capable of improving flaw detection in ultrasonic systems.</p

Morphological filters: Statistical evaluation and applications in ultrasonic NDE

In this paper, morphological filters [1-4] have been applied to detect flaw echoes in ultrasonic signals contaminated by grain scattering noise (i.e., clutters or speckles). In particular, the statistical properties of morphological operations (i.e., dilation, closing, clos-erosion and clos-opening) are examined using Monte Carlo simulation when applied to signals with uniform and Rayleigh distributions. The simulated results and their statistics (mean and variance) present an interpretation of the noise suppression capability of morphological filters and their biasing effects. This information has been utilized to design a suitable structuring element to enhance flaw-to-clutter ratio in ultrasonic testing. The processed experimental results (A-Scans and B-Scans) show that morphological filters can improve flaw visibility by suppressing grain scattering noise.</p

Modeling and Parameter Estimation of Ultrasonic Backscattered Echoes

Ultrasonic backscattered echoes represent not only the impulse response of the ultrasonic transducer, but also contain information pertaining to the inhomogeneity of the propagation path, effect of frequency dependent absorption and scattering, dispersion effect, and geometric shape, size and orientation of reflectors. Therefore, a well-defined modeling of the backscattered echoes leading to the estimation of arrival time, echo skewness, center frequency, and bandwidth is highly desirable for the nondestructive evaluation of materials [1]. In this paper, we model the backscattered echoes, assuming that all parameters describing the shape of the echo are unknown. Then, iterative parameter estimation techniques such as the Gauss-Newton method [2] or Simplex-Search method [3] have been applied to estimate echo parameters. These algorithms have been evaluated in terms of rate of convergence, sub-optimal estimation due to local minima, and presence of noise.</p

Singular Value Decomposition of Wigner Distribution for Time-Frequency Representation of Ultrasonic Echoes

Wigner distribution (WD) is an effective tool for characterizing non-stationary signals where different frequency components arrive at different times. WD was proposed in 1932 by Wigner with applications in quantum mechanics [1]. WD offers high frequency resolution, and satisfies important properties such as marginals and time/frequency shifts. However, in spite of these advantages, WD creates spurious frequency information (cross-terms) when it is applied to signals consisting of multiple echoes or to a signal corrupted by noise. The cross-terms interfere with and often mask the true time-frequency information associated with echoes of interest. Due to the random and complex nature of backscattered ultrasonic echoes, and because the echoes are not exactly Gaussian in shape, the WD of ultrasonic signals is corrupted by the cross-terms. In this paper, singular value decomposition (SVD) is used to analyze and reduce the cross-terms.</p