Analysis of cross-correlation and wavelet de-noising for the reduction of the effects of dispersion in long-range ultrasonic testing

Mallett, R.; Mudge, Peter; Gan, Tat-Hean; Balachandran, W.

doi:10.1784/insi.2007.49.6.350

Cited by 12 publications

(12 citation statements)

References 9 publications

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“…This leads to the same architecture be applicable for the frequency ranges other than audio frequency. The architecture can be changed depending on the algorithm for ultrasonic signal processing techniques [14][15][16][17][18][19][20][21][22][23][24][25].…”

Section: Results and Verificationmentioning

confidence: 99%

“…There are various signal processing algorithms available for filtering and de-noising the ultrasonic signals such as cross-correlation, Hilbert Transform, autoregressive analysis, wavelet transform and split-spectrum processing (SSP) etc. [15][16][17][18]. The SSP algorithm for target detection was successfully implemented on Virtex-5 FPGA due to its capability to easier interfacing with ultrasonic equipment [19].…”

Section: Significance In Ultrasonic Signal Processingmentioning

confidence: 99%

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Efficient FPGA-based FIR – architecture and its significance in ultrasonic signal processing

Tiwari¹,

Ostreika²,

Platuziene³

2017

J. vibroeng.

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The presented work demonstrates the most suitable architecture for the FPGA-based signal processing which makes available various real-time filtering algorithms, such as band pass, high pass, low pass, and band-reject for FIR filters. The processor was implemented with the fixed-point arithmetic using VHDL, which can be downloadable on FPGA device. The FPGA device can be interfaced with an analog-to-digital converter (ADC), digital-to-analog converter (DAC) and a personal computer with MATLAB for the user interface and feeding coefficients and order of the filter. The core part of this paper was to find the reconfigurable and efficient architecture of the processor with only one multiplier which can work for Finite Impulse response (FIR) filter with the best-suited structure. The system will be used for automatic generation of fixed-point FIR filters. The model was also implemented in MATLAB script and the verification of results in the case of low-pass filtering confirmed that both models in MATLAB and VHDL matched to each other. All components of architecture in VHDL were designed using generics which allow changing its structure and behavior by generic values. Therefore, it is a universal filter platform where user can process the data while changing the filter parameters as per the requirement of applications. The complete design was verified by taking the example of audio signal frequency, but parameterized components of system architecture can also facilitate its applicability at ultrasonic frequencies by changing the algorithm. The significance and applicability of FPGAs in ultrasonic signal processing were also studied and reviewed. . He also works as a Lecturer at Multimedia Engineering Department of Kaunas University of Technology. He also achieved Master degree in Electronics engineering (VLSI) at University of Westminster, London, England in 2011. His current research includes development of signal and image processing methods, ultrasonic NDT of composite materials etc. Armantas Ostreika received Ph.D. degree in information technology at Kaunas University of Technology, Lithuania in 2000. He is head of Multimedia Engineering Department at Kaunas University of Technology. His current research includes digital image processing, statistical image analysis, object recognition and interpretation, image restoration, stereo and multi-view imaging, digital photogrammetric systems, video processing etc. Jūratė Platužienė received Master degree in information technology at Kaunas University of technology. She is a Lecturer at Multimedia Engineering Department of Kaunas University of Technology. The main scope of her activity is computer graphics and 3D modeling and animation.

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Section: Results and Verificationmentioning

confidence: 99%

Section: Significance In Ultrasonic Signal Processingmentioning

confidence: 99%

Efficient FPGA-based FIR – architecture and its significance in ultrasonic signal processing

Tiwari¹,

Ostreika²,

Platuziene³

2017

J. vibroeng.

View full text Add to dashboard Cite

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“…These can be categorized as cross-correlation, Hilbert transform (HT), autoregressive analysis, split spectrum processing (SSP), wavelet transform (WT), Hilbert–Huang transform (HHT), etc. [ 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. Each method can work either in time domain or frequency domain or in both the time and frequency domains.…”

Section: Ultrasonic Signal Processingmentioning

confidence: 99%

Hybrid Signal Processing Technique to Improve the Defect Estimation in Ultrasonic Non-Destructive Testing of Composite Structures

Tiwari

Raišutis

Samaitis

2017

Sensors

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This work proposes a novel hybrid signal processing technique to extract information on disbond-type defects from a single B-scan in the process of non-destructive testing (NDT) of glass fiber reinforced plastic (GFRP) material using ultrasonic guided waves (GW). The selected GFRP sample has been a segment of wind turbine blade, which possessed an aerodynamic shape. Two disbond type defects having diameters of 15 mm and 25 mm were artificially constructed on its trailing edge. The experiment has been performed using the low-frequency ultrasonic system developed at the Ultrasound Institute of Kaunas University of Technology and only one side of the sample was accessed. A special configuration of the transmitting and receiving transducers fixed on a movable panel with a separation distance of 50 mm was proposed for recording the ultrasonic guided wave signals at each one-millimeter step along the scanning distance up to 500 mm. Finally, the hybrid signal processing technique comprising the valuable features of the three most promising signal processing techniques: cross-correlation, wavelet transform, and Hilbert–Huang transform has been applied to the received signals for the extraction of defects information from a single B-scan image. The wavelet transform and cross-correlation techniques have been combined in order to extract the approximated size and location of the defects and measurements of time delays. Thereafter, Hilbert–Huang transform has been applied to the wavelet transformed signal to compare the variation of instantaneous frequencies and instantaneous amplitudes of the defect-free and defective signals.

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“…To assess the difference between the signals from unstressed samples and these ones with mechanical stresses, we use a cross-spectrum analysis [18][19][20][21][22]. This processing technique is applied to the signals obtained for one and the same distance and shifted with respect to the time of arrival.…”

Section: Signal Processing Spectral Analysismentioning

confidence: 99%

Investigation of stress-state in rolled sheets by ultrasonic techniques

Ivanova

Partalin²

2011

ultra

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Analysis of cross-correlation and wavelet de-noising for the reduction of the effects of dispersion in long-range ultrasonic testing

Cited by 12 publications

References 9 publications

Efficient FPGA-based FIR – architecture and its significance in ultrasonic signal processing

Efficient FPGA-based FIR – architecture and its significance in ultrasonic signal processing

Hybrid Signal Processing Technique to Improve the Defect Estimation in Ultrasonic Non-Destructive Testing of Composite Structures

Investigation of stress-state in rolled sheets by ultrasonic techniques

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