Fault detection and reporting in line monitoring systems
In general, a system and method consistent with the present disclosure provides automated line monitoring using a machine learning fault classifier for determining whether a signature associated with the high loss loopback (HLLB) data matches a predetermined fault signature. The fault classifier may...
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creator | Xu, Yunlu Liss, Jonathan M Kram, Richard |
description | In general, a system and method consistent with the present disclosure provides automated line monitoring using a machine learning fault classifier for determining whether a signature associated with the high loss loopback (HLLB) data matches a predetermined fault signature. The fault classifier may be applied to signatures generated in response to line monitoring signals of two different wavelengths. A fault may be reported only if the fault classifier indicates a fault in response to the signature for both wavelengths. A second fault classifier may also be used and a fault may be reported only if both the first and second fault classifiers indicate a fault in response to the signature for both wavelengths. A system consistent with the present disclosure may also, or alternatively, be configured to report the value of a pump degradation, span loss, or repeater failure fault, and may also, or alternatively, report the directionality of a span loss fault or the location of a fiber break fault. |
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The fault classifier may be applied to signatures generated in response to line monitoring signals of two different wavelengths. A fault may be reported only if the fault classifier indicates a fault in response to the signature for both wavelengths. A second fault classifier may also be used and a fault may be reported only if both the first and second fault classifiers indicate a fault in response to the signature for both wavelengths. A system consistent with the present disclosure may also, or alternatively, be configured to report the value of a pump degradation, span loss, or repeater failure fault, and may also, or alternatively, report the directionality of a span loss fault or the location of a fiber break fault.</description><language>eng</language><subject>ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRICITY ; TRANSMISSION</subject><creationdate>2019</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20190903&DB=EPODOC&CC=US&NR=10404362B1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20190903&DB=EPODOC&CC=US&NR=10404362B1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Xu, Yunlu</creatorcontrib><creatorcontrib>Liss, Jonathan M</creatorcontrib><creatorcontrib>Kram, Richard</creatorcontrib><title>Fault detection and reporting in line monitoring systems</title><description>In general, a system and method consistent with the present disclosure provides automated line monitoring using a machine learning fault classifier for determining whether a signature associated with the high loss loopback (HLLB) data matches a predetermined fault signature. 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A system consistent with the present disclosure may also, or alternatively, be configured to report the value of a pump degradation, span loss, or repeater failure fault, and may also, or alternatively, report the directionality of a span loss fault or the location of a fiber break fault.</description><subject>ELECTRIC COMMUNICATION TECHNIQUE</subject><subject>ELECTRICITY</subject><subject>TRANSMISSION</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2019</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLBwSyzNKVFISS1JTS7JzM9TSMxLUShKLcgvKsnMS1fIzFPIycxLVcjNz8ssyS8CCRVXFpek5hbzMLCmJeYUp_JCaW4GRTfXEGcPXaDe-NTigsTk1LzUkvjQYEMDEwMTYzMjJ0NjYtQAACy7Lr4</recordid><startdate>20190903</startdate><enddate>20190903</enddate><creator>Xu, Yunlu</creator><creator>Liss, Jonathan M</creator><creator>Kram, Richard</creator><scope>EVB</scope></search><sort><creationdate>20190903</creationdate><title>Fault detection and reporting in line monitoring systems</title><author>Xu, Yunlu ; Liss, Jonathan M ; Kram, Richard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US10404362B13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2019</creationdate><topic>ELECTRIC COMMUNICATION TECHNIQUE</topic><topic>ELECTRICITY</topic><topic>TRANSMISSION</topic><toplevel>online_resources</toplevel><creatorcontrib>Xu, Yunlu</creatorcontrib><creatorcontrib>Liss, Jonathan M</creatorcontrib><creatorcontrib>Kram, Richard</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Xu, Yunlu</au><au>Liss, Jonathan M</au><au>Kram, Richard</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Fault detection and reporting in line monitoring systems</title><date>2019-09-03</date><risdate>2019</risdate><abstract>In general, a system and method consistent with the present disclosure provides automated line monitoring using a machine learning fault classifier for determining whether a signature associated with the high loss loopback (HLLB) data matches a predetermined fault signature. The fault classifier may be applied to signatures generated in response to line monitoring signals of two different wavelengths. A fault may be reported only if the fault classifier indicates a fault in response to the signature for both wavelengths. A second fault classifier may also be used and a fault may be reported only if both the first and second fault classifiers indicate a fault in response to the signature for both wavelengths. A system consistent with the present disclosure may also, or alternatively, be configured to report the value of a pump degradation, span loss, or repeater failure fault, and may also, or alternatively, report the directionality of a span loss fault or the location of a fiber break fault.</abstract><oa>free_for_read</oa></addata></record> |
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subjects | ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY TRANSMISSION |
title | Fault detection and reporting in line monitoring systems |
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