Kumar anubhav Tiwari

Dr. Kumar anubhav Tiwari

Kaunas University of Technology
orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 December 2017 in Sensors
Verified
Journal Article
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Kumar anubhav TiwariKumar anubhav Tiwari
Kumar anubhav Tiwari
RRRenaldas Raisutis
Renaldas Raisutis
Vykintas SamaitisVykintas Samaitis
Vykintas Samaitis
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.

8 May 2018 in The Journal of Strain Analysis for Engineering Design
Verified
Journal Article
Open access
Kumar anubhav TiwariKumar anubhav Tiwari
Kumar anubhav Tiwari
RRRenaldas Raisutis
Renaldas Raisutis
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.

9 July 2018 in Materials
Verified
Journal Article
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Kumar anubhav TiwariKumar anubhav Tiwari
Kumar anubhav Tiwari
RRRenaldas Raisutis
Renaldas Raisutis
In this paper, the disbond-type defect presented on glass fiber reinforced plastic material is analyzed by refining the guided Lamb wave signals. A segment of wind turbine blade is considered as a test sample. The low-frequency ultrasonic measurement system is used for the non-destructive testing of the test sample using guided waves. The P-1 type macro-fiber composite transducer as a transmitter and contact-type piezoceramic transducer as a receiver are used for the testing of a sample. The disbond type defect having a diameter of 81 mm is detected from the experimental results. To improve the accuracy in locating and sizing the defects and estimation of the time of flight and phase velocity of ultrasonic guided waves in defective region, signal processing algorithm is developed by utilizing the promising properties of various ultrasonic signal processing techniques such as wavelet transform, amplitude detection, two-dimensional Fast-Fourier transform, Hilbert transform and variational mode decomposition. The discrete wavelet transform is used to denoise the guided wave signals and then, the size and location of defects are estimated by amplitude detection. The reflected wave signals from the opposite edge of the sample are removed by applying the two-dimensional Fast-Fourier transform to the experimental B-scan signal. Afterwards, variational mode decomposition and Hilbert transform are used for the phase velocity and time-delay estimation by comparing the instantaneous amplitudes of the defective and defect-free signal. The validation and the demonstration of reproducibility of the algorithm is performed by extracting the features of a 51 mm defect from another experimental B-scan.


12 March 2019 in Electronics
Verified
Journal Article
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Kumar anubhav TiwariKumar anubhav Tiwari
Kumar anubhav Tiwari
RRRenaldas Raisutis
Renaldas Raisutis
OTOlgirdas Tumšys
Olgirdas Tumšys
AOArmantas Ostreika
Armantas Ostreika
KJKęstutis Jankauskas
Kęstutis Jankauskas
JJJulijus Jakutavicius
Julijus Jakutavicius
The estimation of the size and location of defects in multi-layered composite structures by ultrasonic non-destructive testing using guided waves has attracted the attention of researchers for the last few decades. Although extensive signal processing techniques are available, there are only a few studies available based on image processing of the ultrasonic B-scan image to extract the size and location of defects via the process of ultrasonic non-destructive testing. This work presents an image processing technique for ultrasonic B-scan images to improve the estimation of the location and size of disbond-type defects in glass fiber-reinforced plastic materials with 25-mm and 51-mm diameters. The sample is a segment of a wind turbine blade with a variable thickness ranging from 3 to 24 mm. The experiment is performed by using a low-frequency ultrasonic system and a pair of contact-type piezoceramic transducers kept apart by a 50-mm distance and embedded on a moving mechanical panel. The B-scan image acquired by the ultrasonic pitch-catch technique is denoised by utilizing features of two-dimensional discrete wavelet transform. Thereafter, the normalized pixel densities are compared along the scanned distance on the region of interest of the image, and a −3 dB threshold is applied to the locations and sizes the defects in the spatial domain.

17 July 2021 in Sensors
Verified
Journal Article
Open access
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RRRenaldas Raisutis
Renaldas Raisutis
Kumar anubhav TiwariKumar anubhav Tiwari
Kumar anubhav Tiwari
EŽEgidijus Žukauskas
Egidijus Žukauskas
OTOlgirdas Tumšys
Olgirdas Tumšys
LDLina Draudviliene
Lina Draudviliene
The reliability of the wind turbine blade (WTB) evaluation using a new criterion is presented in the work. Variation of the ultrasonic guided waves (UGW) phase velocity is proposed to be used as a new criterion for defect detection. Based on an intermediate value between the maximum and minimum values, the calculation of the phase velocity threshold is used for defect detection, location and sizing. The operation of the proposed technique is verified using simulation and experimental studies. The artificially milled defect having a diameter of 81 mm on the segment of WTB is used for verification of the proposed technique. After the application of the proposed evaluation technique for analysis of the simulated B-scan image, the coordinates of defect edges have been estimated with relative errors of 3.7% and 3%, respectively. The size of the defect was estimated with a relative error of 2.7%. In the case of an experimentally measured B-scan image, the coordinates of defect edges have been estimated with relative errors of 12.5% and 3.9%, respectively. The size of the defect was estimated with a relative error of 10%. The comparative results obtained by modelling and experiment show the suitability of the proposed new criterion to be used for the defect detection tasks solving.