A comparative study of time-frequency analysis techniques in the case of signal processing for ultrasonic NDT

Raišutis, Renaldas; Tumšys, Olgirdas; Kažys, R.; Mažeika, Liudas

doi:10.1784/insi.2008.50.11.628

Cited by 9 publications

(7 citation statements)

References 16 publications

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“…[18][19][20] There are many signal processing techniques such as wavelet transform (WT), HT, cross-correlation and split spectrum processing used to improve the signal-to-noise ratio of the GW signals. [21][22][23][24][25][26] In this article, the DWT, VMD and HT are used in order to improve the accuracy in the estimation of defects. The brief description of these methods is as follows.…”

Section: Overview Of Signal Processing Of Ultrasonic Signalsmentioning

confidence: 99%

Post-processing of ultrasonic signals for the analysis of defects in wind turbine blade using guided waves

Tiwari

Raišutis

2018

The Journal of Strain Analysis for Engineering Design

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In this work, the most promising ultrasonic signal processing methods-discrete wavelet transform, variational mode decomposition and Hilbert transform-are applied for the analysis of disbond-type defects in the segment of wind turbine blade. Two disbond-type artificial defects having diameters of 81 and 25 mm were located on the main spar of wind turbine blade. The low-frequency ultrasonic system developed by Ultrasound Research Institute of the Kaunas University of Technology was used for the experimental investigation of wind turbine blade using guided waves and only one side of the blade segment was accessed. Two contact type ultrasonic transducers separated by 50 mm distance and fixed on a movable mechanical panel were used as a transmitter-receiver pair during the experiment for the ultrasonic signals recording up to the scanning distance of 250 mm with the scanning step of 1 mm. Both types of defects were marginally detected from the conventional experimental B-scan and therefore appropriate signal processing techniques were used to improve the accuracy of the analysis of defects. The discrete wavelet transform was combined with the amplitude detection method for estimating the size and location of defects. Finally, the variational mode decomposition is combined with the Hilbert transform to compare the instantaneous frequencies and amplitudes of the defect-free and defective signals as well as for the measurement of time-delays between the defect-free and defective signals.

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Section: Overview Of Signal Processing Of Ultrasonic Signalsmentioning

confidence: 99%

Post-processing of ultrasonic signals for the analysis of defects in wind turbine blade using guided waves

Tiwari

Raišutis

2018

The Journal of Strain Analysis for Engineering Design

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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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“…The range of applications is also overwhelming, but almost all of them can be grouped, if attending to their purpose, in three general groups of application: de-fect detection, characterization and imaging [3]- [6]. Finally, regarding the methodologies used, despite we would need a full book only to list the number of processing algorithms, procedures and methods used in ultrasound technologies, they can also be grouped in two sorts of methods, those based on time domain analysis and those based on frequency domain analysis, which combined lead to a third category for the methods that use both approximations combined [7], [8].…”

Section: Introductionmentioning

confidence: 99%

On the Optimization of Spread Spectrum Chirps Into Arbitrary Position and Width Pulse Signals. Application to Ultrasonic Sensors and Systems

et al. 2022

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This work presents in detail a new method for the optimization of rectangular spread spectrum excitation signals for its use in simple and low-cost ultrasonic pulsers, but that could be extended to other applications based on spread spectrum signals. Starting from rectangular linear frequency modulated (RLFM) chirps, it uses the transfer function of the transmitted signal and received echoes from reference specimens to iterate through a recursive algorithm to obtain arbitrary position and width pulse (APWP) signals with the desired bandwidth, maximizing the energy and the flatness of the spectrum, and enhancing the resolution and dynamic range of conventional chirp excitation signals. This optimization procedure can be repeated for any transducer and material, so that it achieves the best performance in each experimental environment. Such characteristics are ideal for Time-of-Flight estimation, imaging, and applications in which spectral regularity is needed, such as the Split Spectrum Processing (SSP) algorithm, which is used as example to test the performance of the proposed excitation signals. It also allows to specify and change the bandwidth reducing the need to change the transducers. The method is tested with different transducers (2 and 5 MHz focused transducers) and complex composite materials (aluminum-carbon aviation composite and high porosity GFRP composite) in immersion setup for imaging applications using SSP algorithm.INDEX TERMS Ultrasound, Spread Spectrum, chirp, arbitrary position and width pulses, Split Spectrum Processing, non destructive testing.

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A comparative study of time-frequency analysis techniques in the case of signal processing for ultrasonic NDT

Cited by 9 publications

References 16 publications

Post-processing of ultrasonic signals for the analysis of defects in wind turbine blade using guided waves

Post-processing of ultrasonic signals for the analysis of defects in wind turbine blade using guided waves

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

On the Optimization of Spread Spectrum Chirps Into Arbitrary Position and Width Pulse Signals. Application to Ultrasonic Sensors and Systems

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