A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy

Silicone rubber material is widely used in high-voltage external insulation systems due to its excellent hydrophobicity and hydrophobicity transfer performance. However, silicone rubber is a polymeric material with a poor ability to resist electrical tracking and erosion; therefore, some fillers mus...
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Autor*in:	Ping Chen [verfasserIn] Xilin Wang [verfasserIn] Xun Li [verfasserIn] Qishen Lyu [verfasserIn] Naixiao Wang [verfasserIn] Zhidong Jia [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	silicone rubber material tracking and erosion resistance laser-induced breakdown spectroscopy neural network

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 19(2019), 5, p 1087
Übergeordnetes Werk:	volume:19 ; year:2019 ; number:5, p 1087

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s19051087

Katalog-ID:	DOAJ085480746

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520			\|a Silicone rubber material is widely used in high-voltage external insulation systems due to its excellent hydrophobicity and hydrophobicity transfer performance. However, silicone rubber is a polymeric material with a poor ability to resist electrical tracking and erosion; therefore, some fillers must be added to the material for performance enhancement. The inclined plane test is a standard method used for evaluating the tracking and erosion resistance by subjecting the materials to a combination of voltage stress and contaminate droplets to produce failure. This test is time-consuming and difficult to apply in field inspection. In this paper, a new and faster way to evaluate the tracking and erosion resistance performance is proposed using laser-induced breakdown spectroscopy (LIBS). The influence of filler content on the tracking and erosion resistance performance was studied, and the filler content was characterized by thermogravimetric analysis and the LIBS technique. In this paper, the tracking and erosion resistance of silicone rubber samples was correctly classified using principal component analysis (PCA) and neural network algorithms based on LIBS spectra. The conclusions of this work are of great significance to the performance characterization of silicone rubber composite materials.
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allfields	10.3390/s19051087 doi (DE-627)DOAJ085480746 (DE-599)DOAJcd2ba758712e4b4dad237b124cea6841 DE-627 ger DE-627 rakwb eng TP1-1185 Ping Chen verfasserin aut A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Silicone rubber material is widely used in high-voltage external insulation systems due to its excellent hydrophobicity and hydrophobicity transfer performance. However, silicone rubber is a polymeric material with a poor ability to resist electrical tracking and erosion; therefore, some fillers must be added to the material for performance enhancement. The inclined plane test is a standard method used for evaluating the tracking and erosion resistance by subjecting the materials to a combination of voltage stress and contaminate droplets to produce failure. This test is time-consuming and difficult to apply in field inspection. In this paper, a new and faster way to evaluate the tracking and erosion resistance performance is proposed using laser-induced breakdown spectroscopy (LIBS). The influence of filler content on the tracking and erosion resistance performance was studied, and the filler content was characterized by thermogravimetric analysis and the LIBS technique. In this paper, the tracking and erosion resistance of silicone rubber samples was correctly classified using principal component analysis (PCA) and neural network algorithms based on LIBS spectra. The conclusions of this work are of great significance to the performance characterization of silicone rubber composite materials. silicone rubber material tracking and erosion resistance laser-induced breakdown spectroscopy neural network Chemical technology Xilin Wang verfasserin aut Xun Li verfasserin aut Qishen Lyu verfasserin aut Naixiao Wang verfasserin aut Zhidong Jia verfasserin aut In Sensors MDPI AG, 2003 19(2019), 5, p 1087 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:19 year:2019 number:5, p 1087 https://doi.org/10.3390/s19051087 kostenfrei https://doaj.org/article/cd2ba758712e4b4dad237b124cea6841 kostenfrei http://www.mdpi.com/1424-8220/19/5/1087 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2019 5, p 1087
spelling	10.3390/s19051087 doi (DE-627)DOAJ085480746 (DE-599)DOAJcd2ba758712e4b4dad237b124cea6841 DE-627 ger DE-627 rakwb eng TP1-1185 Ping Chen verfasserin aut A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Silicone rubber material is widely used in high-voltage external insulation systems due to its excellent hydrophobicity and hydrophobicity transfer performance. However, silicone rubber is a polymeric material with a poor ability to resist electrical tracking and erosion; therefore, some fillers must be added to the material for performance enhancement. The inclined plane test is a standard method used for evaluating the tracking and erosion resistance by subjecting the materials to a combination of voltage stress and contaminate droplets to produce failure. This test is time-consuming and difficult to apply in field inspection. In this paper, a new and faster way to evaluate the tracking and erosion resistance performance is proposed using laser-induced breakdown spectroscopy (LIBS). The influence of filler content on the tracking and erosion resistance performance was studied, and the filler content was characterized by thermogravimetric analysis and the LIBS technique. In this paper, the tracking and erosion resistance of silicone rubber samples was correctly classified using principal component analysis (PCA) and neural network algorithms based on LIBS spectra. The conclusions of this work are of great significance to the performance characterization of silicone rubber composite materials. silicone rubber material tracking and erosion resistance laser-induced breakdown spectroscopy neural network Chemical technology Xilin Wang verfasserin aut Xun Li verfasserin aut Qishen Lyu verfasserin aut Naixiao Wang verfasserin aut Zhidong Jia verfasserin aut In Sensors MDPI AG, 2003 19(2019), 5, p 1087 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:19 year:2019 number:5, p 1087 https://doi.org/10.3390/s19051087 kostenfrei https://doaj.org/article/cd2ba758712e4b4dad237b124cea6841 kostenfrei http://www.mdpi.com/1424-8220/19/5/1087 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2019 5, p 1087
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allfieldsSound	10.3390/s19051087 doi (DE-627)DOAJ085480746 (DE-599)DOAJcd2ba758712e4b4dad237b124cea6841 DE-627 ger DE-627 rakwb eng TP1-1185 Ping Chen verfasserin aut A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Silicone rubber material is widely used in high-voltage external insulation systems due to its excellent hydrophobicity and hydrophobicity transfer performance. However, silicone rubber is a polymeric material with a poor ability to resist electrical tracking and erosion; therefore, some fillers must be added to the material for performance enhancement. The inclined plane test is a standard method used for evaluating the tracking and erosion resistance by subjecting the materials to a combination of voltage stress and contaminate droplets to produce failure. This test is time-consuming and difficult to apply in field inspection. In this paper, a new and faster way to evaluate the tracking and erosion resistance performance is proposed using laser-induced breakdown spectroscopy (LIBS). The influence of filler content on the tracking and erosion resistance performance was studied, and the filler content was characterized by thermogravimetric analysis and the LIBS technique. In this paper, the tracking and erosion resistance of silicone rubber samples was correctly classified using principal component analysis (PCA) and neural network algorithms based on LIBS spectra. The conclusions of this work are of great significance to the performance characterization of silicone rubber composite materials. silicone rubber material tracking and erosion resistance laser-induced breakdown spectroscopy neural network Chemical technology Xilin Wang verfasserin aut Xun Li verfasserin aut Qishen Lyu verfasserin aut Naixiao Wang verfasserin aut Zhidong Jia verfasserin aut In Sensors MDPI AG, 2003 19(2019), 5, p 1087 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:19 year:2019 number:5, p 1087 https://doi.org/10.3390/s19051087 kostenfrei https://doaj.org/article/cd2ba758712e4b4dad237b124cea6841 kostenfrei http://www.mdpi.com/1424-8220/19/5/1087 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2019 5, p 1087
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authorswithroles_txt_mv	Ping Chen @@aut@@ Xilin Wang @@aut@@ Xun Li @@aut@@ Qishen Lyu @@aut@@ Naixiao Wang @@aut@@ Zhidong Jia @@aut@@
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callnumber-first	T - Technology
author	Ping Chen
spellingShingle	Ping Chen misc TP1-1185 misc silicone rubber material misc tracking and erosion resistance misc laser-induced breakdown spectroscopy misc neural network misc Chemical technology A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy
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topic_title	TP1-1185 A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy silicone rubber material tracking and erosion resistance laser-induced breakdown spectroscopy neural network
topic	misc TP1-1185 misc silicone rubber material misc tracking and erosion resistance misc laser-induced breakdown spectroscopy misc neural network misc Chemical technology
topic_unstemmed	misc TP1-1185 misc silicone rubber material misc tracking and erosion resistance misc laser-induced breakdown spectroscopy misc neural network misc Chemical technology
topic_browse	misc TP1-1185 misc silicone rubber material misc tracking and erosion resistance misc laser-induced breakdown spectroscopy misc neural network misc Chemical technology
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title	A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy
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title_full	A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy
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title_sort	quick classifying method for tracking and erosion resistance of htv silicone rubber material via laser-induced breakdown spectroscopy
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title_auth	A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy
abstract	Silicone rubber material is widely used in high-voltage external insulation systems due to its excellent hydrophobicity and hydrophobicity transfer performance. However, silicone rubber is a polymeric material with a poor ability to resist electrical tracking and erosion; therefore, some fillers must be added to the material for performance enhancement. The inclined plane test is a standard method used for evaluating the tracking and erosion resistance by subjecting the materials to a combination of voltage stress and contaminate droplets to produce failure. This test is time-consuming and difficult to apply in field inspection. In this paper, a new and faster way to evaluate the tracking and erosion resistance performance is proposed using laser-induced breakdown spectroscopy (LIBS). The influence of filler content on the tracking and erosion resistance performance was studied, and the filler content was characterized by thermogravimetric analysis and the LIBS technique. In this paper, the tracking and erosion resistance of silicone rubber samples was correctly classified using principal component analysis (PCA) and neural network algorithms based on LIBS spectra. The conclusions of this work are of great significance to the performance characterization of silicone rubber composite materials.
abstractGer	Silicone rubber material is widely used in high-voltage external insulation systems due to its excellent hydrophobicity and hydrophobicity transfer performance. However, silicone rubber is a polymeric material with a poor ability to resist electrical tracking and erosion; therefore, some fillers must be added to the material for performance enhancement. The inclined plane test is a standard method used for evaluating the tracking and erosion resistance by subjecting the materials to a combination of voltage stress and contaminate droplets to produce failure. This test is time-consuming and difficult to apply in field inspection. In this paper, a new and faster way to evaluate the tracking and erosion resistance performance is proposed using laser-induced breakdown spectroscopy (LIBS). The influence of filler content on the tracking and erosion resistance performance was studied, and the filler content was characterized by thermogravimetric analysis and the LIBS technique. In this paper, the tracking and erosion resistance of silicone rubber samples was correctly classified using principal component analysis (PCA) and neural network algorithms based on LIBS spectra. The conclusions of this work are of great significance to the performance characterization of silicone rubber composite materials.
abstract_unstemmed	Silicone rubber material is widely used in high-voltage external insulation systems due to its excellent hydrophobicity and hydrophobicity transfer performance. However, silicone rubber is a polymeric material with a poor ability to resist electrical tracking and erosion; therefore, some fillers must be added to the material for performance enhancement. The inclined plane test is a standard method used for evaluating the tracking and erosion resistance by subjecting the materials to a combination of voltage stress and contaminate droplets to produce failure. This test is time-consuming and difficult to apply in field inspection. In this paper, a new and faster way to evaluate the tracking and erosion resistance performance is proposed using laser-induced breakdown spectroscopy (LIBS). The influence of filler content on the tracking and erosion resistance performance was studied, and the filler content was characterized by thermogravimetric analysis and the LIBS technique. In this paper, the tracking and erosion resistance of silicone rubber samples was correctly classified using principal component analysis (PCA) and neural network algorithms based on LIBS spectra. The conclusions of this work are of great significance to the performance characterization of silicone rubber composite materials.
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container_issue	5, p 1087
title_short	A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy
url	https://doi.org/10.3390/s19051087 https://doaj.org/article/cd2ba758712e4b4dad237b124cea6841 http://www.mdpi.com/1424-8220/19/5/1087 https://doaj.org/toc/1424-8220
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up_date	2024-07-03T14:59:45.679Z
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A Quick Classifying Method for Tracking and Erosion Resistance of HTV Silicone Rubber Material via Laser-Induced Breakdown Spectroscopy

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