Ultrasonic visualization and quantitative analysis of internal defects in RTV coatings
Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. In...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hao Yang [verfasserIn] Zhibo Song [verfasserIn] Xuanxiang Zhao [verfasserIn] Fusheng Zhou [verfasserIn] Sirui Zhao [verfasserIn] Qirui Ran [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Heliyon - Elsevier, 2016, 9(2023), 10, Seite e21188- |
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| Übergeordnetes Werk: |
volume:9 ; year:2023 ; number:10 ; pages:e21188- |
| Links: |
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| DOI / URN: |
10.1016/j.heliyon.2023.e21188 |
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| Katalog-ID: |
DOAJ095293965 |
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| 520 | |a Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. The research presented in this paper enables precise assessment of debonding defect severity and establishes a reliable foundation for on-site inspection, operation, and maintenance of RTV coatings. | ||
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10.1016/j.heliyon.2023.e21188 doi (DE-627)DOAJ095293965 (DE-599)DOAJb5b00e65337e4597897c588b7c4d4ea0 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Hao Yang verfasserin aut Ultrasonic visualization and quantitative analysis of internal defects in RTV coatings 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. The research presented in this paper enables precise assessment of debonding defect severity and establishes a reliable foundation for on-site inspection, operation, and maintenance of RTV coatings. Room temperature vulcanised Interface debonding Ultrasonic detection Edge segmentation Science (General) Social sciences (General) Zhibo Song verfasserin aut Xuanxiang Zhao verfasserin aut Fusheng Zhou verfasserin aut Sirui Zhao verfasserin aut Qirui Ran verfasserin aut In Heliyon Elsevier, 2016 9(2023), 10, Seite e21188- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:9 year:2023 number:10 pages:e21188- https://doi.org/10.1016/j.heliyon.2023.e21188 kostenfrei https://doaj.org/article/b5b00e65337e4597897c588b7c4d4ea0 kostenfrei http://www.sciencedirect.com/science/article/pii/S2405844023083962 kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 9 2023 10 e21188- |
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10.1016/j.heliyon.2023.e21188 doi (DE-627)DOAJ095293965 (DE-599)DOAJb5b00e65337e4597897c588b7c4d4ea0 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Hao Yang verfasserin aut Ultrasonic visualization and quantitative analysis of internal defects in RTV coatings 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. The research presented in this paper enables precise assessment of debonding defect severity and establishes a reliable foundation for on-site inspection, operation, and maintenance of RTV coatings. Room temperature vulcanised Interface debonding Ultrasonic detection Edge segmentation Science (General) Social sciences (General) Zhibo Song verfasserin aut Xuanxiang Zhao verfasserin aut Fusheng Zhou verfasserin aut Sirui Zhao verfasserin aut Qirui Ran verfasserin aut In Heliyon Elsevier, 2016 9(2023), 10, Seite e21188- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:9 year:2023 number:10 pages:e21188- https://doi.org/10.1016/j.heliyon.2023.e21188 kostenfrei https://doaj.org/article/b5b00e65337e4597897c588b7c4d4ea0 kostenfrei http://www.sciencedirect.com/science/article/pii/S2405844023083962 kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 9 2023 10 e21188- |
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10.1016/j.heliyon.2023.e21188 doi (DE-627)DOAJ095293965 (DE-599)DOAJb5b00e65337e4597897c588b7c4d4ea0 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Hao Yang verfasserin aut Ultrasonic visualization and quantitative analysis of internal defects in RTV coatings 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. The research presented in this paper enables precise assessment of debonding defect severity and establishes a reliable foundation for on-site inspection, operation, and maintenance of RTV coatings. Room temperature vulcanised Interface debonding Ultrasonic detection Edge segmentation Science (General) Social sciences (General) Zhibo Song verfasserin aut Xuanxiang Zhao verfasserin aut Fusheng Zhou verfasserin aut Sirui Zhao verfasserin aut Qirui Ran verfasserin aut In Heliyon Elsevier, 2016 9(2023), 10, Seite e21188- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:9 year:2023 number:10 pages:e21188- https://doi.org/10.1016/j.heliyon.2023.e21188 kostenfrei https://doaj.org/article/b5b00e65337e4597897c588b7c4d4ea0 kostenfrei http://www.sciencedirect.com/science/article/pii/S2405844023083962 kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 9 2023 10 e21188- |
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10.1016/j.heliyon.2023.e21188 doi (DE-627)DOAJ095293965 (DE-599)DOAJb5b00e65337e4597897c588b7c4d4ea0 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Hao Yang verfasserin aut Ultrasonic visualization and quantitative analysis of internal defects in RTV coatings 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. The research presented in this paper enables precise assessment of debonding defect severity and establishes a reliable foundation for on-site inspection, operation, and maintenance of RTV coatings. Room temperature vulcanised Interface debonding Ultrasonic detection Edge segmentation Science (General) Social sciences (General) Zhibo Song verfasserin aut Xuanxiang Zhao verfasserin aut Fusheng Zhou verfasserin aut Sirui Zhao verfasserin aut Qirui Ran verfasserin aut In Heliyon Elsevier, 2016 9(2023), 10, Seite e21188- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:9 year:2023 number:10 pages:e21188- https://doi.org/10.1016/j.heliyon.2023.e21188 kostenfrei https://doaj.org/article/b5b00e65337e4597897c588b7c4d4ea0 kostenfrei http://www.sciencedirect.com/science/article/pii/S2405844023083962 kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 9 2023 10 e21188- |
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10.1016/j.heliyon.2023.e21188 doi (DE-627)DOAJ095293965 (DE-599)DOAJb5b00e65337e4597897c588b7c4d4ea0 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Hao Yang verfasserin aut Ultrasonic visualization and quantitative analysis of internal defects in RTV coatings 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. The research presented in this paper enables precise assessment of debonding defect severity and establishes a reliable foundation for on-site inspection, operation, and maintenance of RTV coatings. Room temperature vulcanised Interface debonding Ultrasonic detection Edge segmentation Science (General) Social sciences (General) Zhibo Song verfasserin aut Xuanxiang Zhao verfasserin aut Fusheng Zhou verfasserin aut Sirui Zhao verfasserin aut Qirui Ran verfasserin aut In Heliyon Elsevier, 2016 9(2023), 10, Seite e21188- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:9 year:2023 number:10 pages:e21188- https://doi.org/10.1016/j.heliyon.2023.e21188 kostenfrei https://doaj.org/article/b5b00e65337e4597897c588b7c4d4ea0 kostenfrei http://www.sciencedirect.com/science/article/pii/S2405844023083962 kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 9 2023 10 e21188- |
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Ultrasonic visualization and quantitative analysis of internal defects in RTV coatings |
| abstract |
Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. The research presented in this paper enables precise assessment of debonding defect severity and establishes a reliable foundation for on-site inspection, operation, and maintenance of RTV coatings. |
| abstractGer |
Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. The research presented in this paper enables precise assessment of debonding defect severity and establishes a reliable foundation for on-site inspection, operation, and maintenance of RTV coatings. |
| abstract_unstemmed |
Room temperature vulcanised (RTV) silicone rubber coatings effectively enhance the insulation properties of electrical equipment. However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. The research presented in this paper enables precise assessment of debonding defect severity and establishes a reliable foundation for on-site inspection, operation, and maintenance of RTV coatings. |
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However, RTV coatings are prone to internal defects caused by the coating process and the effects of aging during service, which can lead to debonding of the coatings. Internal debonding defects are challenging to detect and can ultimately lead to accidents due to a reduction in the insulation capacity of the equipment. To visualize the internal defect morphology of RTV coatings and quantify the defect size, an ultrasonic pulse-echo-based method for detecting and imaging debonding defects is proposed. The method involves the development of a finite element model to investigate how ultrasonic waves propagate in RTV coatings and the influence of ultrasonic probes and inspection conditions on defect echoes. Furthermore, an ultrasonic detection system specifically designed for RTV coating debonding defects is constructed. This system utilizes wavelet packets in the time-frequency domain to analyze the echo signals in both normal and defective regions. The three-dimensional reconstruction of the debonding defect morphology is accomplished by integrating ultrasonic echo amplitude and position information. Finally, the size of the debonding defects is quantified using an adaptive threshold segmentation method. The findings indicate that ultrasound waves reflected in RTV materials propagate as spherical waves, with the acoustic energy primarily concentrated near the acoustic axis. As the propagation distance increases, the sound beam disperses along the axis and extends beyond the transducer, resulting in a decrease in the sound field's directionality. The developed visual reconstruction method in this study offers the capability of three-dimensional visualization for defects present within RTV coatings, including their length, width, and depth. The accurate determination of defect size is achieved through the utilization of the adaptive threshold segmentation method, yielding an average error rate of 5.7 % across different defect types. In comparison, the maximal interclass variance method (OTSU) and the fuzzy C-means (FCM) method produced results with error rates of 9.8 % and 7.9 %, respectively. 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