Process monitoring in principal component subspace: part 1 - fault reconstruction study
The principal component analysis (PCA) is a kind of data-driven modeling method that has wide applications in the field of industrial process monitoring and product quality control. However, it was shown that some faults can only be detected in the principal component subspace (PCS) and the T/sup 2/...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 5124 vol.6 |
|---|---|
| container_issue | |
| container_start_page | 5119 |
| container_title | |
| container_volume | 6 |
| creator | Haiqing Wang Ning Jiang Diancai Yang |
| description | The principal component analysis (PCA) is a kind of data-driven modeling method that has wide applications in the field of industrial process monitoring and product quality control. However, it was shown that some faults can only be detected in the principal component subspace (PCS) and the T/sup 2/ statistic in PCS is more robust than SPE statistic while the latter is in the residual subspace (RS). A reconstruction approach for these faults in the PCS is proposed to estimate the fault magnitude and then judge its type. The reconstructability conditions both for complete and partial ones are derived mathematically and the obtained results are illustrated and verified by simulation studies on a double-effective evaporator. |
| doi_str_mv | 10.1109/ICSMC.2004.1401006 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>pascalfrancis_6IE</sourceid><recordid>TN_cdi_pascalfrancis_primary_17524257</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1401006</ieee_id><sourcerecordid>17524257</sourcerecordid><originalsourceid>FETCH-LOGICAL-i205t-d60320b33253a73b94745d47137fb7cf4f06368057ceddc29ea5eefd605015d93</originalsourceid><addsrcrecordid>eNpFUEtLxDAYDD7A3dU_oJdcPHb98m69SfGxsKKgorclTROJdNOSpIf99xYqeJqBeTAMQpcE1oRAdbOp357rNQXga8KBAMgjtKBCqYJIIY7RElQJrBRSqhO0ICBpUVH6dYaWKf0AUOCkXKDP19gbmxLe98HnPvrwjX3Aw0SMH3SHTb8f-mBDxmls0qCNvcWDjhkTXGCnxy7jaE0fUo6jyb4POOWxPZyjU6e7ZC_-cIU-Hu7f66di-_K4qe-2hacgctFKYBQaxqhgWrGm4oqLlivClGuUcdyBZLIEoYxtW0Mrq4W1booJIKKt2Apdz72DTkZ3Luppd9pN-_c6HnZECcqnUybf1ezz1tp_eT6O_QJB1GBC</addsrcrecordid><sourcetype>Index Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Process monitoring in principal component subspace: part 1 - fault reconstruction study</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Haiqing Wang ; Ning Jiang ; Diancai Yang</creator><creatorcontrib>Haiqing Wang ; Ning Jiang ; Diancai Yang</creatorcontrib><description>The principal component analysis (PCA) is a kind of data-driven modeling method that has wide applications in the field of industrial process monitoring and product quality control. However, it was shown that some faults can only be detected in the principal component subspace (PCS) and the T/sup 2/ statistic in PCS is more robust than SPE statistic while the latter is in the residual subspace (RS). A reconstruction approach for these faults in the PCS is proposed to estimate the fault magnitude and then judge its type. The reconstructability conditions both for complete and partial ones are derived mathematically and the obtained results are illustrated and verified by simulation studies on a double-effective evaporator.</description><identifier>ISSN: 1062-922X</identifier><identifier>ISBN: 0780385667</identifier><identifier>ISBN: 9780780385665</identifier><identifier>EISSN: 2577-1655</identifier><identifier>DOI: 10.1109/ICSMC.2004.1401006</identifier><language>eng</language><publisher>Piscataway NJ: IEEE</publisher><subject>Applied sciences ; Chemical analysis ; Computer science; control theory; systems ; Control theory. Systems ; Exact sciences and technology ; Fault detection ; Fault diagnosis ; Industrial control ; Monitoring ; Personal communication networks ; Principal component analysis ; Process control ; Quality control ; Testing</subject><ispartof>2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2004, Vol.6, p.5119-5124 vol.6</ispartof><rights>2006 INIST-CNRS</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1401006$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,4036,4037,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1401006$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17524257$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Haiqing Wang</creatorcontrib><creatorcontrib>Ning Jiang</creatorcontrib><creatorcontrib>Diancai Yang</creatorcontrib><title>Process monitoring in principal component subspace: part 1 - fault reconstruction study</title><title>2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)</title><addtitle>ICSMC</addtitle><description>The principal component analysis (PCA) is a kind of data-driven modeling method that has wide applications in the field of industrial process monitoring and product quality control. However, it was shown that some faults can only be detected in the principal component subspace (PCS) and the T/sup 2/ statistic in PCS is more robust than SPE statistic while the latter is in the residual subspace (RS). A reconstruction approach for these faults in the PCS is proposed to estimate the fault magnitude and then judge its type. The reconstructability conditions both for complete and partial ones are derived mathematically and the obtained results are illustrated and verified by simulation studies on a double-effective evaporator.</description><subject>Applied sciences</subject><subject>Chemical analysis</subject><subject>Computer science; control theory; systems</subject><subject>Control theory. Systems</subject><subject>Exact sciences and technology</subject><subject>Fault detection</subject><subject>Fault diagnosis</subject><subject>Industrial control</subject><subject>Monitoring</subject><subject>Personal communication networks</subject><subject>Principal component analysis</subject><subject>Process control</subject><subject>Quality control</subject><subject>Testing</subject><issn>1062-922X</issn><issn>2577-1655</issn><isbn>0780385667</isbn><isbn>9780780385665</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFUEtLxDAYDD7A3dU_oJdcPHb98m69SfGxsKKgorclTROJdNOSpIf99xYqeJqBeTAMQpcE1oRAdbOp357rNQXga8KBAMgjtKBCqYJIIY7RElQJrBRSqhO0ICBpUVH6dYaWKf0AUOCkXKDP19gbmxLe98HnPvrwjX3Aw0SMH3SHTb8f-mBDxmls0qCNvcWDjhkTXGCnxy7jaE0fUo6jyb4POOWxPZyjU6e7ZC_-cIU-Hu7f66di-_K4qe-2hacgctFKYBQaxqhgWrGm4oqLlivClGuUcdyBZLIEoYxtW0Mrq4W1booJIKKt2Apdz72DTkZ3Luppd9pN-_c6HnZECcqnUybf1ezz1tp_eT6O_QJB1GBC</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Haiqing Wang</creator><creator>Ning Jiang</creator><creator>Diancai Yang</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>IQODW</scope></search><sort><creationdate>2004</creationdate><title>Process monitoring in principal component subspace: part 1 - fault reconstruction study</title><author>Haiqing Wang ; Ning Jiang ; Diancai Yang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i205t-d60320b33253a73b94745d47137fb7cf4f06368057ceddc29ea5eefd605015d93</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Applied sciences</topic><topic>Chemical analysis</topic><topic>Computer science; control theory; systems</topic><topic>Control theory. Systems</topic><topic>Exact sciences and technology</topic><topic>Fault detection</topic><topic>Fault diagnosis</topic><topic>Industrial control</topic><topic>Monitoring</topic><topic>Personal communication networks</topic><topic>Principal component analysis</topic><topic>Process control</topic><topic>Quality control</topic><topic>Testing</topic><toplevel>online_resources</toplevel><creatorcontrib>Haiqing Wang</creatorcontrib><creatorcontrib>Ning Jiang</creatorcontrib><creatorcontrib>Diancai Yang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEL</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Haiqing Wang</au><au>Ning Jiang</au><au>Diancai Yang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Process monitoring in principal component subspace: part 1 - fault reconstruction study</atitle><btitle>2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)</btitle><stitle>ICSMC</stitle><date>2004</date><risdate>2004</risdate><volume>6</volume><spage>5119</spage><epage>5124 vol.6</epage><pages>5119-5124 vol.6</pages><issn>1062-922X</issn><eissn>2577-1655</eissn><isbn>0780385667</isbn><isbn>9780780385665</isbn><abstract>The principal component analysis (PCA) is a kind of data-driven modeling method that has wide applications in the field of industrial process monitoring and product quality control. However, it was shown that some faults can only be detected in the principal component subspace (PCS) and the T/sup 2/ statistic in PCS is more robust than SPE statistic while the latter is in the residual subspace (RS). A reconstruction approach for these faults in the PCS is proposed to estimate the fault magnitude and then judge its type. The reconstructability conditions both for complete and partial ones are derived mathematically and the obtained results are illustrated and verified by simulation studies on a double-effective evaporator.</abstract><cop>Piscataway NJ</cop><pub>IEEE</pub><doi>10.1109/ICSMC.2004.1401006</doi></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1062-922X |
| ispartof | 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2004, Vol.6, p.5119-5124 vol.6 |
| issn | 1062-922X 2577-1655 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_17524257 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Applied sciences Chemical analysis Computer science control theory systems Control theory. Systems Exact sciences and technology Fault detection Fault diagnosis Industrial control Monitoring Personal communication networks Principal component analysis Process control Quality control Testing |
| title | Process monitoring in principal component subspace: part 1 - fault reconstruction study |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T08%3A10%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-pascalfrancis_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Process%20monitoring%20in%20principal%20component%20subspace:%20part%201%20-%20fault%20reconstruction%20study&rft.btitle=2004%20IEEE%20International%20Conference%20on%20Systems,%20Man%20and%20Cybernetics%20(IEEE%20Cat.%20No.04CH37583)&rft.au=Haiqing%20Wang&rft.date=2004&rft.volume=6&rft.spage=5119&rft.epage=5124%20vol.6&rft.pages=5119-5124%20vol.6&rft.issn=1062-922X&rft.eissn=2577-1655&rft.isbn=0780385667&rft.isbn_list=9780780385665&rft_id=info:doi/10.1109/ICSMC.2004.1401006&rft_dat=%3Cpascalfrancis_6IE%3E17524257%3C/pascalfrancis_6IE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=1401006&rfr_iscdi=true |