Fault Knowledge Acquisition of Electronic Equipment
The difficulties of acquiring fault knowledge severely handicap the development of intelligent diagnosis system (IDS) of military electronic equipment (MEE) in our country.For MEE fault diagnosis of fault original data collection difficult situation, a new method is presented,Which auto-acquires fau...
Gespeichert in:
Veröffentlicht in: | Applied Mechanics and Materials 2013-09, Vol.397-400, p.1145-1147 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1147 |
---|---|
container_issue | |
container_start_page | 1145 |
container_title | Applied Mechanics and Materials |
container_volume | 397-400 |
creator | Li, Dan Wang, Lu Zhang, Hong Zou, Feng Hua |
description | The difficulties of acquiring fault knowledge severely handicap the development of intelligent diagnosis system (IDS) of military electronic equipment (MEE) in our country.For MEE fault diagnosis of fault original data collection difficult situation, a new method is presented,Which auto-acquires fault knowledge by simulating all possible faults of equipment.The approach presented in this paper makes the work of KA engineer easier, and makes fast diagnosis fault location and fault reasons possible. |
doi_str_mv | 10.4028/www.scientific.net/AMM.397-400.1145 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1442190207</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3099807891</sourcerecordid><originalsourceid>FETCH-LOGICAL-c305t-2b6ffa5f0b58cba810492ef1aa5f375f823933f6f867bdd10275320b31c5034c3</originalsourceid><addsrcrecordid>eNqVkF1LwzAYhYMfoJv-h4KX0u7NV5tejtGpuOGNXoc2SzSja7ckpfjvzZygt1698J7DOYcHoXsMGQMiZuM4Zl5Z3QVrrMo6HWbz9TqjZZEygAxjxs_QNc5zkhZMkHM0oUALwQWj_OJbgLSkNL9CE--3ADnDTFwjuqyHNiTPXT-2evOuk7k6DNbbYPsu6U1StVoF13dWJVUU9rs44AZdmrr1-vbnTtHbsnpdPKarl4enxXyVKgo8pKTJjam5gYYL1dQCAyuJNriOP1pwIwiNg0xuRF40mw0GUnBKoKFYcaBM0Sm6O-XuXX8YtA9y2w-ui5USM0ZwCQSK6FqcXMr13jtt5N7ZXe0-JQZ5RCcjOvmLTkZ0MqKTEV3UQR7RxZTqlBJc3fmg1cefsn_kfAFpC36v</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1442190207</pqid></control><display><type>article</type><title>Fault Knowledge Acquisition of Electronic Equipment</title><source>Scientific.net Journals</source><creator>Li, Dan ; Wang, Lu ; Zhang, Hong ; Zou, Feng Hua</creator><creatorcontrib>Li, Dan ; Wang, Lu ; Zhang, Hong ; Zou, Feng Hua</creatorcontrib><description>The difficulties of acquiring fault knowledge severely handicap the development of intelligent diagnosis system (IDS) of military electronic equipment (MEE) in our country.For MEE fault diagnosis of fault original data collection difficult situation, a new method is presented,Which auto-acquires fault knowledge by simulating all possible faults of equipment.The approach presented in this paper makes the work of KA engineer easier, and makes fast diagnosis fault location and fault reasons possible.</description><identifier>ISSN: 1660-9336</identifier><identifier>ISSN: 1662-7482</identifier><identifier>ISBN: 3037858435</identifier><identifier>ISBN: 9783037858431</identifier><identifier>EISSN: 1662-7482</identifier><identifier>DOI: 10.4028/www.scientific.net/AMM.397-400.1145</identifier><language>eng</language><publisher>Zurich: Trans Tech Publications Ltd</publisher><ispartof>Applied Mechanics and Materials, 2013-09, Vol.397-400, p.1145-1147</ispartof><rights>2013 Trans Tech Publications Ltd</rights><rights>Copyright Trans Tech Publications Ltd. Sep 2013</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://www.scientific.net/Image/TitleCover/2658?width=600</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Li, Dan</creatorcontrib><creatorcontrib>Wang, Lu</creatorcontrib><creatorcontrib>Zhang, Hong</creatorcontrib><creatorcontrib>Zou, Feng Hua</creatorcontrib><title>Fault Knowledge Acquisition of Electronic Equipment</title><title>Applied Mechanics and Materials</title><description>The difficulties of acquiring fault knowledge severely handicap the development of intelligent diagnosis system (IDS) of military electronic equipment (MEE) in our country.For MEE fault diagnosis of fault original data collection difficult situation, a new method is presented,Which auto-acquires fault knowledge by simulating all possible faults of equipment.The approach presented in this paper makes the work of KA engineer easier, and makes fast diagnosis fault location and fault reasons possible.</description><issn>1660-9336</issn><issn>1662-7482</issn><issn>1662-7482</issn><isbn>3037858435</isbn><isbn>9783037858431</isbn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqVkF1LwzAYhYMfoJv-h4KX0u7NV5tejtGpuOGNXoc2SzSja7ckpfjvzZygt1698J7DOYcHoXsMGQMiZuM4Zl5Z3QVrrMo6HWbz9TqjZZEygAxjxs_QNc5zkhZMkHM0oUALwQWj_OJbgLSkNL9CE--3ADnDTFwjuqyHNiTPXT-2evOuk7k6DNbbYPsu6U1StVoF13dWJVUU9rs44AZdmrr1-vbnTtHbsnpdPKarl4enxXyVKgo8pKTJjam5gYYL1dQCAyuJNriOP1pwIwiNg0xuRF40mw0GUnBKoKFYcaBM0Sm6O-XuXX8YtA9y2w-ui5USM0ZwCQSK6FqcXMr13jtt5N7ZXe0-JQZ5RCcjOvmLTkZ0MqKTEV3UQR7RxZTqlBJc3fmg1cefsn_kfAFpC36v</recordid><startdate>20130901</startdate><enddate>20130901</enddate><creator>Li, Dan</creator><creator>Wang, Lu</creator><creator>Zhang, Hong</creator><creator>Zou, Feng Hua</creator><general>Trans Tech Publications Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>7TB</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BFMQW</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>KB.</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20130901</creationdate><title>Fault Knowledge Acquisition of Electronic Equipment</title><author>Li, Dan ; Wang, Lu ; Zhang, Hong ; Zou, Feng Hua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c305t-2b6ffa5f0b58cba810492ef1aa5f375f823933f6f867bdd10275320b31c5034c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Dan</creatorcontrib><creatorcontrib>Wang, Lu</creatorcontrib><creatorcontrib>Zhang, Hong</creatorcontrib><creatorcontrib>Zou, Feng Hua</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Continental Europe Database</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>Materials Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Materials Science Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>Applied Mechanics and Materials</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Dan</au><au>Wang, Lu</au><au>Zhang, Hong</au><au>Zou, Feng Hua</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fault Knowledge Acquisition of Electronic Equipment</atitle><jtitle>Applied Mechanics and Materials</jtitle><date>2013-09-01</date><risdate>2013</risdate><volume>397-400</volume><spage>1145</spage><epage>1147</epage><pages>1145-1147</pages><issn>1660-9336</issn><issn>1662-7482</issn><eissn>1662-7482</eissn><isbn>3037858435</isbn><isbn>9783037858431</isbn><abstract>The difficulties of acquiring fault knowledge severely handicap the development of intelligent diagnosis system (IDS) of military electronic equipment (MEE) in our country.For MEE fault diagnosis of fault original data collection difficult situation, a new method is presented,Which auto-acquires fault knowledge by simulating all possible faults of equipment.The approach presented in this paper makes the work of KA engineer easier, and makes fast diagnosis fault location and fault reasons possible.</abstract><cop>Zurich</cop><pub>Trans Tech Publications Ltd</pub><doi>10.4028/www.scientific.net/AMM.397-400.1145</doi><tpages>3</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1660-9336 |
ispartof | Applied Mechanics and Materials, 2013-09, Vol.397-400, p.1145-1147 |
issn | 1660-9336 1662-7482 1662-7482 |
language | eng |
recordid | cdi_proquest_journals_1442190207 |
source | Scientific.net Journals |
title | Fault Knowledge Acquisition of Electronic Equipment |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-02T00%3A44%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Fault%20Knowledge%20Acquisition%20of%20Electronic%20Equipment&rft.jtitle=Applied%20Mechanics%20and%20Materials&rft.au=Li,%20Dan&rft.date=2013-09-01&rft.volume=397-400&rft.spage=1145&rft.epage=1147&rft.pages=1145-1147&rft.issn=1660-9336&rft.eissn=1662-7482&rft.isbn=3037858435&rft.isbn_list=9783037858431&rft_id=info:doi/10.4028/www.scientific.net/AMM.397-400.1145&rft_dat=%3Cproquest_cross%3E3099807891%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1442190207&rft_id=info:pmid/&rfr_iscdi=true |