Ultrasonic Flaw Detection Using Signal Matching Techniques

Srinivasan, Kannan; Chiou, Chien‐Ping; Thompson, R. B.

doi:10.1007/978-1-4615-1987-4_88

Cited by 5 publications

(5 citation statements)

References 4 publications

(5 reference statements)

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“…The problem received considerable attention from the NDE community in recent decades but only limited degree of success has been achieved, and several techniques were investigated to enhance the flaw detection or reduce the clutter noise by exploring either the spatial diversity across the array aperture [1][2][3][4], or the temporal-spectral characteristics and signatures of the broadband ultrasonic signals [5][6][7][8][9][10][11][12]. Array beamforming is widely used in radar and communication systems for spatial filtering and diversity processing [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

“…The split spectrum processing method [5] obtains a frequency-diverse ensemble of narrowband signals from the broadband ultrasonic echoes through a filter bank, and then recombines them to determine if the signal originates from a real defect or grain boundaries. The matched filtering technique [8][9] computes the optimal parameters in the filter response through maximizing the SNR improvement over a set of training signals captured from the test sample, and then uses the signal matching concept to detect the echoes from a real defect [6][7]. In this paper, a novel approach based on the fractal dimension analysis of the broadband ultrasound A-scan waveform is investigated to distinguish between the echoes originating from legitimate reflectors and the material microstructure grain noise.…”

Section: Introductionmentioning

confidence: 99%

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Fractal dimension analysis for robust ultrasonic non-destructive evaluation (NDE) of coarse grained materials

Hayward²

2018

AIP Conference Proceedings

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ARTICLES YOU MAY BE INTERESTED INAbstract. Over the recent decades, there has been a growing demand on reliable and robust non-destructive evaluation (NDE) of structures and components made from coarse grained materials such as alloys, stainless steels, carbonreinforced composites and concrete; however, when inspected using ultrasound, the flaw echoes are usually contaminated by high-level, time-invariant, and correlated grain noise originating from the microstructure and grain boundaries, leading to pretty low signal-to-noise ratio (SNR) and the flaw information being obscured or completely hidden by the grain noise. In this paper, the fractal dimension analysis of the A-scan echoes is investigated as a measure of complexity of the time series to distinguish the echoes originating from the real defects and the grain noise, and then the normalized fractal dimension coefficients are applied to the amplitudes as the weighting factor to enhance the SNR and defect detection. Experiments on industrial samples of the mild steel and the stainless steel are conducted and the results confirm the great benefits of the method.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fractal dimension analysis for robust ultrasonic non-destructive evaluation (NDE) of coarse grained materials

Hayward²

2018

AIP Conference Proceedings

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“…Earlier studies use simulated flaw signals [7,8] or the superposition of actual excitation signals [5,6] to design the filter, but they are inevitably subject to significant errors, especially in NDE of coarse grain materials, where it is quite challenging to simulate a flaw signal to certain extent of similarity [8]. In the literature, the excitation signal measured in the experiments have also been used to design the matched filter, but the procedure is time consuming, or requires extra instrument to exactly record the transmitted signal, and thus not straightforward to implement in practice…”

Section: Introductionmentioning

confidence: 99%

A robust approach to optimal matched filter design in ultrasonic non-destructive evaluation (NDE)

Li¹,

Hayward²

2017

AIP Conference Proceedings

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Abstract.The matched filter was demonstrated to be a powerful yet efficient technique to enhance defect detection and imaging in ultrasonic non-destructive evaluation (NDE) of coarse grain materials, provided that the filter was properly designed and optimized. In the literature, in order to accurately approximate the defect echoes, the design utilized the real excitation signals, which made it time consuming and less straightforward to implement in practice. In this paper, we present a more robust and flexible approach to optimal matched filter design using the simulated excitation signals, and the control parameters are chosen and optimized based on the real scenario of array transducer, transmitter-receiver system response, and the test sample, as a result, the filter response is optimized and depends on the material characteristics. Experiments on industrial samples are conducted and the results confirm the great benefits of the method.

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“…The efficacy of this approach as applied to ultrasonics is directly related to the quality of the template; in essence, the efficacy is controlled by the operator's ability to predict the signal distortion caused by scattering at an unknown defect. Specifically as related to defect detection in ultrasonics, Xin et al [7], Chiou et al [8], and Srinivasan et al [9] address the difficulties in estimating the template along with the use of model-based approaches for template estimation. Eriksson et al [10] address the problem of correlation-based timeof-flight estimation when the signals have undergone unknown, nonlinear distortions.…”

Section: Introductionmentioning

confidence: 99%

Spatial Correlation Coefficient Images for Ultrasonic Detection

Cepel

Rinker

et al. 2007

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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In ultrasonics, image formation and detection are generally based on signal amplitude. In this paper, we introduce correlation coefficient images as a signalamplitude independent approach for image formation. The correlation coefficients are calculated between A-scans digitized at adjacent measurement positions. In these images, defects are revealed as regions of high or low correlation relative to the background correlations associated with noise. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular ring and crack detection in an aluminum aircraft structure.

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Ultrasonic Flaw Detection Using Signal Matching Techniques

Cited by 5 publications

References 4 publications

Fractal dimension analysis for robust ultrasonic non-destructive evaluation (NDE) of coarse grained materials

Fractal dimension analysis for robust ultrasonic non-destructive evaluation (NDE) of coarse grained materials

A robust approach to optimal matched filter design in ultrasonic non-destructive evaluation (NDE)

Spatial Correlation Coefficient Images for Ultrasonic Detection

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