Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/716992
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dc.contributor.authorJaved Ahmad|Aparna Akula|Ravibabu Mulaveesala|H. K. Sardanaen_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:33Z-
dc.date.available2021-05-16T17:43:33Z-
dc.date.issueden_US
dc.identifier.isbn1530-437Xen_US
dc.identifier.other10.1109/JSEN.2018.2877726en_US
dc.identifier.urihttp://localhost/handle/Hannan/716992-
dc.description.abstractThermal non-destructive testing (TNDT) is one of the emerging inspection and evaluation techniques mostly used for subsurface defect detection in various industrial components. Besides the conventional thermography techniques (such as lock-in and pulse), recently introduced non-stationary thermal wave imaging (NSTWI) techniques gained its applicability in TNDT community due to their inherent testing capabilities such as improved sensitivity and enhanced resolution in inspecting and evaluating various solid materials for detecting subsurface defects. Barker-coded thermal wave imaging (BCTWI) is a one of the widely used NSTWI techniques, which facilitates the use of low peak power heat sources in moderate experimentation time in contrast to conventional TNDT techniques. In this paper, the pulse compression favorable NSTWI (BCTWI), the reconstructed pulsed (main lobe) data have been considered and processed using independent component analysis and named Barker-coded independent component thermography (BCICT). This proposed BCICT is implemented on a mild-steel sample to detect the artificially simulated flat bottom circular holes located at different depths inside it. The proposed technique extracts the sub-surface details such as flaws/defects hidden inside the sample by an unsupervised learning process, which helps in eliminating the manual interpretation of subsurface defects. The applicability of the proposed algorithm has been evaluated and validated experimentally with two different excitations schemes by considering the contrast and signal-to-noise ratio (SNR) as figure of merit. The results indicate that the BCICT technique offers higher contrast and SNR in comparison to conventional pulse-based TNDT technique.en_US
dc.relation.haspart08502804.pdfen_US
dc.subjectBarker coded thermal wave imaging|Active thermography|independent component analysisen_US
dc.titleBarker-Coded Thermal Wave Imaging for Non-Destructive Testing and Evaluation of Steel Materialen_US
dc.title.alternativeIEEE Sensors Journalen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Sensors Journalen_US
Appears in Collections:New Ieee 2019

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dc.contributor.authorJaved Ahmad|Aparna Akula|Ravibabu Mulaveesala|H. K. Sardanaen_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:33Z-
dc.date.available2021-05-16T17:43:33Z-
dc.date.issueden_US
dc.identifier.isbn1530-437Xen_US
dc.identifier.other10.1109/JSEN.2018.2877726en_US
dc.identifier.urihttp://localhost/handle/Hannan/716992-
dc.description.abstractThermal non-destructive testing (TNDT) is one of the emerging inspection and evaluation techniques mostly used for subsurface defect detection in various industrial components. Besides the conventional thermography techniques (such as lock-in and pulse), recently introduced non-stationary thermal wave imaging (NSTWI) techniques gained its applicability in TNDT community due to their inherent testing capabilities such as improved sensitivity and enhanced resolution in inspecting and evaluating various solid materials for detecting subsurface defects. Barker-coded thermal wave imaging (BCTWI) is a one of the widely used NSTWI techniques, which facilitates the use of low peak power heat sources in moderate experimentation time in contrast to conventional TNDT techniques. In this paper, the pulse compression favorable NSTWI (BCTWI), the reconstructed pulsed (main lobe) data have been considered and processed using independent component analysis and named Barker-coded independent component thermography (BCICT). This proposed BCICT is implemented on a mild-steel sample to detect the artificially simulated flat bottom circular holes located at different depths inside it. The proposed technique extracts the sub-surface details such as flaws/defects hidden inside the sample by an unsupervised learning process, which helps in eliminating the manual interpretation of subsurface defects. The applicability of the proposed algorithm has been evaluated and validated experimentally with two different excitations schemes by considering the contrast and signal-to-noise ratio (SNR) as figure of merit. The results indicate that the BCICT technique offers higher contrast and SNR in comparison to conventional pulse-based TNDT technique.en_US
dc.relation.haspart08502804.pdfen_US
dc.subjectBarker coded thermal wave imaging|Active thermography|independent component analysisen_US
dc.titleBarker-Coded Thermal Wave Imaging for Non-Destructive Testing and Evaluation of Steel Materialen_US
dc.title.alternativeIEEE Sensors Journalen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Sensors Journalen_US
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08502804.pdf1.63 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJaved Ahmad|Aparna Akula|Ravibabu Mulaveesala|H. K. Sardanaen_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:33Z-
dc.date.available2021-05-16T17:43:33Z-
dc.date.issueden_US
dc.identifier.isbn1530-437Xen_US
dc.identifier.other10.1109/JSEN.2018.2877726en_US
dc.identifier.urihttp://localhost/handle/Hannan/716992-
dc.description.abstractThermal non-destructive testing (TNDT) is one of the emerging inspection and evaluation techniques mostly used for subsurface defect detection in various industrial components. Besides the conventional thermography techniques (such as lock-in and pulse), recently introduced non-stationary thermal wave imaging (NSTWI) techniques gained its applicability in TNDT community due to their inherent testing capabilities such as improved sensitivity and enhanced resolution in inspecting and evaluating various solid materials for detecting subsurface defects. Barker-coded thermal wave imaging (BCTWI) is a one of the widely used NSTWI techniques, which facilitates the use of low peak power heat sources in moderate experimentation time in contrast to conventional TNDT techniques. In this paper, the pulse compression favorable NSTWI (BCTWI), the reconstructed pulsed (main lobe) data have been considered and processed using independent component analysis and named Barker-coded independent component thermography (BCICT). This proposed BCICT is implemented on a mild-steel sample to detect the artificially simulated flat bottom circular holes located at different depths inside it. The proposed technique extracts the sub-surface details such as flaws/defects hidden inside the sample by an unsupervised learning process, which helps in eliminating the manual interpretation of subsurface defects. The applicability of the proposed algorithm has been evaluated and validated experimentally with two different excitations schemes by considering the contrast and signal-to-noise ratio (SNR) as figure of merit. The results indicate that the BCICT technique offers higher contrast and SNR in comparison to conventional pulse-based TNDT technique.en_US
dc.relation.haspart08502804.pdfen_US
dc.subjectBarker coded thermal wave imaging|Active thermography|independent component analysisen_US
dc.titleBarker-Coded Thermal Wave Imaging for Non-Destructive Testing and Evaluation of Steel Materialen_US
dc.title.alternativeIEEE Sensors Journalen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Sensors Journalen_US
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08502804.pdf1.63 MBAdobe PDFThumbnail
Preview File