AR-Aided Smart Sensing for In-Line Condition Monitoring of IGBT Wafer
This paper describes an augmented reality (AR)-aided smart sensing technique for in-line condition monitoring of insulated-gate bipolar transistor (IGBT) wafers. A series of signal processing algorithms are applied for enabling sensor intelligence. Based on electromagnetic infrared-visible fusion (I...
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Veröffentlicht in: | IEEE transactions on industrial electronics (1982) 2019-10, Vol.66 (10), p.8197-8204 |
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creator | Li, Kongjing Tian, Gui Yun Chen, Xiaotian Tang, Chaoqing Luo, Haoze Li, Wuhua Gao, Bin He, Xiangning Wright, Nick |
description | This paper describes an augmented reality (AR)-aided smart sensing technique for in-line condition monitoring of insulated-gate bipolar transistor (IGBT) wafers. A series of signal processing algorithms are applied for enabling sensor intelligence. Based on electromagnetic infrared-visible fusion (IVF), a supplementary palpable three-dimensional thermography layer is integrated with an IGBT wafer in real world environment. Before the IVF, independent component analysis is implemented to identify defects in the wafer. The proposed AR-aided smart sensing technique enhances user's perception and interaction between the industrial systems and the surrounding world. In contrast to conventional sensor techniques, it provides nondestructive testing and evaluation based high-throughput in-line condition monitoring method. The advantages of noncontact and time efficient of this smart sensing technique potentially bring huge benefit to yield management and production efficiency. AR-aided smart sensing can improve the productivity, quality, and reliability of power electronic materials and devices, as well as in other industrial applications. |
doi_str_mv | 10.1109/TIE.2018.2886775 |
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A series of signal processing algorithms are applied for enabling sensor intelligence. Based on electromagnetic infrared-visible fusion (IVF), a supplementary palpable three-dimensional thermography layer is integrated with an IGBT wafer in real world environment. Before the IVF, independent component analysis is implemented to identify defects in the wafer. The proposed AR-aided smart sensing technique enhances user's perception and interaction between the industrial systems and the surrounding world. In contrast to conventional sensor techniques, it provides nondestructive testing and evaluation based high-throughput in-line condition monitoring method. The advantages of noncontact and time efficient of this smart sensing technique potentially bring huge benefit to yield management and production efficiency. AR-aided smart sensing can improve the productivity, quality, and reliability of power electronic materials and devices, as well as in other industrial applications.</description><identifier>ISSN: 0278-0046</identifier><identifier>EISSN: 1557-9948</identifier><identifier>DOI: 10.1109/TIE.2018.2886775</identifier><identifier>CODEN: ITIED6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Augmented reality ; Augmented reality (AR) ; Condition monitoring ; Detection ; eddy current pulsed thermography ; Electromagnetic heating ; Electromagnetics ; Electronic devices ; Electronic materials ; IGBT ; Independent component analysis ; Industrial applications ; Inspection ; Insulated gate bipolar transistors ; Nondestructive testing ; Sensors ; Signal processing ; smart sensing ; Testing ; Thermography ; wafers</subject><ispartof>IEEE transactions on industrial electronics (1982), 2019-10, Vol.66 (10), p.8197-8204</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c333t-5bc6d81b92af9fd77931bb3cb9bd82caad44d6bce1a24585c9efe77cbe0282413</citedby><cites>FETCH-LOGICAL-c333t-5bc6d81b92af9fd77931bb3cb9bd82caad44d6bce1a24585c9efe77cbe0282413</cites><orcidid>0000-0002-7563-1523 ; 0000-0003-3377-6895 ; 0000-0002-0953-0097 ; 0000-0002-6943-3715 ; 0000-0002-3749-947X ; 0000-0003-3169-4159 ; 0000-0001-5103-5068 ; 0000-0002-0345-5815</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8598823$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids></links><search><creatorcontrib>Li, Kongjing</creatorcontrib><creatorcontrib>Tian, Gui Yun</creatorcontrib><creatorcontrib>Chen, Xiaotian</creatorcontrib><creatorcontrib>Tang, Chaoqing</creatorcontrib><creatorcontrib>Luo, Haoze</creatorcontrib><creatorcontrib>Li, Wuhua</creatorcontrib><creatorcontrib>Gao, Bin</creatorcontrib><creatorcontrib>He, Xiangning</creatorcontrib><creatorcontrib>Wright, Nick</creatorcontrib><title>AR-Aided Smart Sensing for In-Line Condition Monitoring of IGBT Wafer</title><title>IEEE transactions on industrial electronics (1982)</title><addtitle>TIE</addtitle><description>This paper describes an augmented reality (AR)-aided smart sensing technique for in-line condition monitoring of insulated-gate bipolar transistor (IGBT) wafers. A series of signal processing algorithms are applied for enabling sensor intelligence. Based on electromagnetic infrared-visible fusion (IVF), a supplementary palpable three-dimensional thermography layer is integrated with an IGBT wafer in real world environment. Before the IVF, independent component analysis is implemented to identify defects in the wafer. The proposed AR-aided smart sensing technique enhances user's perception and interaction between the industrial systems and the surrounding world. In contrast to conventional sensor techniques, it provides nondestructive testing and evaluation based high-throughput in-line condition monitoring method. The advantages of noncontact and time efficient of this smart sensing technique potentially bring huge benefit to yield management and production efficiency. AR-aided smart sensing can improve the productivity, quality, and reliability of power electronic materials and devices, as well as in other industrial applications.</description><subject>Algorithms</subject><subject>Augmented reality</subject><subject>Augmented reality (AR)</subject><subject>Condition monitoring</subject><subject>Detection</subject><subject>eddy current pulsed thermography</subject><subject>Electromagnetic heating</subject><subject>Electromagnetics</subject><subject>Electronic devices</subject><subject>Electronic materials</subject><subject>IGBT</subject><subject>Independent component analysis</subject><subject>Industrial applications</subject><subject>Inspection</subject><subject>Insulated gate bipolar transistors</subject><subject>Nondestructive testing</subject><subject>Sensors</subject><subject>Signal processing</subject><subject>smart sensing</subject><subject>Testing</subject><subject>Thermography</subject><subject>wafers</subject><issn>0278-0046</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><recordid>eNo9kEtLAzEUhYMoWEf3gpuA66l5TCbJspZaByqCrbgMk5ekaFKT6cJ_75QWV3fznXO4HwC3GE0xRvJh0y2mBGExJUK0nLMzMMGM8VrKRpyDCSJc1Ag17SW4KmWLEG4YZhOwmL3Vs2CdhevvPg9w7WIJ8RP6lGEX61WIDs5TtGEIKcKXFMOQ8gFIHnbLxw386L3L1-DC91_F3ZxuBd6fFpv5c716XXbz2ao2lNKhZtq0VmAtSe-lt5xLirWmRkttBTF9b5vGtto43JOGCWak845zox0igjSYVuD-2LvL6WfvyqC2aZ_jOKkIoWxk5NhZAXSkTE6lZOfVLofxu1-FkTrIUqMsdZClTrLGyN0xEpxz_7hgUghC6R8DbGRF</recordid><startdate>20191001</startdate><enddate>20191001</enddate><creator>Li, Kongjing</creator><creator>Tian, Gui Yun</creator><creator>Chen, Xiaotian</creator><creator>Tang, Chaoqing</creator><creator>Luo, Haoze</creator><creator>Li, Wuhua</creator><creator>Gao, Bin</creator><creator>He, Xiangning</creator><creator>Wright, Nick</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-7563-1523</orcidid><orcidid>https://orcid.org/0000-0003-3377-6895</orcidid><orcidid>https://orcid.org/0000-0002-0953-0097</orcidid><orcidid>https://orcid.org/0000-0002-6943-3715</orcidid><orcidid>https://orcid.org/0000-0002-3749-947X</orcidid><orcidid>https://orcid.org/0000-0003-3169-4159</orcidid><orcidid>https://orcid.org/0000-0001-5103-5068</orcidid><orcidid>https://orcid.org/0000-0002-0345-5815</orcidid></search><sort><creationdate>20191001</creationdate><title>AR-Aided Smart Sensing for In-Line Condition Monitoring of IGBT Wafer</title><author>Li, Kongjing ; Tian, Gui Yun ; Chen, Xiaotian ; Tang, Chaoqing ; Luo, Haoze ; Li, Wuhua ; Gao, Bin ; He, Xiangning ; Wright, Nick</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c333t-5bc6d81b92af9fd77931bb3cb9bd82caad44d6bce1a24585c9efe77cbe0282413</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Augmented reality</topic><topic>Augmented reality (AR)</topic><topic>Condition monitoring</topic><topic>Detection</topic><topic>eddy current pulsed thermography</topic><topic>Electromagnetic heating</topic><topic>Electromagnetics</topic><topic>Electronic devices</topic><topic>Electronic materials</topic><topic>IGBT</topic><topic>Independent component analysis</topic><topic>Industrial applications</topic><topic>Inspection</topic><topic>Insulated gate bipolar transistors</topic><topic>Nondestructive testing</topic><topic>Sensors</topic><topic>Signal processing</topic><topic>smart sensing</topic><topic>Testing</topic><topic>Thermography</topic><topic>wafers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Kongjing</creatorcontrib><creatorcontrib>Tian, Gui Yun</creatorcontrib><creatorcontrib>Chen, Xiaotian</creatorcontrib><creatorcontrib>Tang, Chaoqing</creatorcontrib><creatorcontrib>Luo, Haoze</creatorcontrib><creatorcontrib>Li, Wuhua</creatorcontrib><creatorcontrib>Gao, Bin</creatorcontrib><creatorcontrib>He, Xiangning</creatorcontrib><creatorcontrib>Wright, Nick</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Xplore Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on industrial electronics (1982)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Kongjing</au><au>Tian, Gui Yun</au><au>Chen, Xiaotian</au><au>Tang, Chaoqing</au><au>Luo, Haoze</au><au>Li, Wuhua</au><au>Gao, Bin</au><au>He, Xiangning</au><au>Wright, Nick</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>AR-Aided Smart Sensing for In-Line Condition Monitoring of IGBT Wafer</atitle><jtitle>IEEE transactions on industrial electronics (1982)</jtitle><stitle>TIE</stitle><date>2019-10-01</date><risdate>2019</risdate><volume>66</volume><issue>10</issue><spage>8197</spage><epage>8204</epage><pages>8197-8204</pages><issn>0278-0046</issn><eissn>1557-9948</eissn><coden>ITIED6</coden><abstract>This paper describes an augmented reality (AR)-aided smart sensing technique for in-line condition monitoring of insulated-gate bipolar transistor (IGBT) wafers. A series of signal processing algorithms are applied for enabling sensor intelligence. Based on electromagnetic infrared-visible fusion (IVF), a supplementary palpable three-dimensional thermography layer is integrated with an IGBT wafer in real world environment. Before the IVF, independent component analysis is implemented to identify defects in the wafer. The proposed AR-aided smart sensing technique enhances user's perception and interaction between the industrial systems and the surrounding world. In contrast to conventional sensor techniques, it provides nondestructive testing and evaluation based high-throughput in-line condition monitoring method. The advantages of noncontact and time efficient of this smart sensing technique potentially bring huge benefit to yield management and production efficiency. AR-aided smart sensing can improve the productivity, quality, and reliability of power electronic materials and devices, as well as in other industrial applications.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIE.2018.2886775</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-7563-1523</orcidid><orcidid>https://orcid.org/0000-0003-3377-6895</orcidid><orcidid>https://orcid.org/0000-0002-0953-0097</orcidid><orcidid>https://orcid.org/0000-0002-6943-3715</orcidid><orcidid>https://orcid.org/0000-0002-3749-947X</orcidid><orcidid>https://orcid.org/0000-0003-3169-4159</orcidid><orcidid>https://orcid.org/0000-0001-5103-5068</orcidid><orcidid>https://orcid.org/0000-0002-0345-5815</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Augmented reality Augmented reality (AR) Condition monitoring Detection eddy current pulsed thermography Electromagnetic heating Electromagnetics Electronic devices Electronic materials IGBT Independent component analysis Industrial applications Inspection Insulated gate bipolar transistors Nondestructive testing Sensors Signal processing smart sensing Testing Thermography wafers |
title | AR-Aided Smart Sensing for In-Line Condition Monitoring of IGBT Wafer |
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