A nonparametric fault isolation approach through one-class classification algorithms
DC Field | Value | Language |
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dc.contributor.author | Kim, Seoung Bum | - |
dc.contributor.author | Sukchotrat, Thuntee | - |
dc.contributor.author | Park, Sun-Kyoung | - |
dc.date.accessioned | 2021-09-07T21:17:41Z | - |
dc.date.available | 2021-09-07T21:17:41Z | - |
dc.date.created | 2021-06-14 | - |
dc.date.issued | 2011 | - |
dc.identifier.issn | 0740-817X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/114879 | - |
dc.description.abstract | Multivariate control charts provide control limits for the monitoring of processes and detection of abnormal events so that processes can be improved. However, these multivariate control charts provide limited information about the contribution of any specific variable to the out-of-control alarm. Although many fault isolation methods have been developed to address this deficiency, most of these methods require a parametric distributional assumption that restricts their applicability to specific problems of process control and thus limits their broader usefulness. This study proposes a nonparametric fault isolation method based on a one-class classification algorithm that overcomes the limitation posed by the parametric assumption in existing fault isolation methods. The proposed approach decomposes the monitoring statistics obtained from a one-class classification algorithm into components that reflect the contribution of each variable to the out-of-control signal. A bootstrap approach is used to determine the significance of each variable. A simulation study is presented that examines the performance of the proposed method under various scenarios and to results are compared with those obtained using the T2 decomposition method. The simulation results reveal that the proposed method outperforms the T2 decomposition method in non-normal distribution cases. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | TAYLOR & FRANCIS INC | - |
dc.subject | MULTIVARIATE CONTROL CHART | - |
dc.subject | SUPPORT VECTOR METHODS | - |
dc.subject | T-2 | - |
dc.subject | IDENTIFICATION | - |
dc.subject | DECOMPOSITION | - |
dc.title | A nonparametric fault isolation approach through one-class classification algorithms | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Seoung Bum | - |
dc.identifier.doi | 10.1080/0740817X.2010.523769 | - |
dc.identifier.scopusid | 2-s2.0-79953687096 | - |
dc.identifier.wosid | 000289248400003 | - |
dc.identifier.bibliographicCitation | IIE TRANSACTIONS, v.43, no.7, pp.505 - 517 | - |
dc.relation.isPartOf | IIE TRANSACTIONS | - |
dc.citation.title | IIE TRANSACTIONS | - |
dc.citation.volume | 43 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 505 | - |
dc.citation.endPage | 517 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Operations Research & Management Science | - |
dc.relation.journalWebOfScienceCategory | Engineering, Industrial | - |
dc.relation.journalWebOfScienceCategory | Operations Research & Management Science | - |
dc.subject.keywordPlus | MULTIVARIATE CONTROL CHART | - |
dc.subject.keywordPlus | SUPPORT VECTOR METHODS | - |
dc.subject.keywordPlus | T-2 | - |
dc.subject.keywordPlus | IDENTIFICATION | - |
dc.subject.keywordPlus | DECOMPOSITION | - |
dc.subject.keywordAuthor | Decomposition | - |
dc.subject.keywordAuthor | fault isolation | - |
dc.subject.keywordAuthor | multivariate statistical process control | - |
dc.subject.keywordAuthor | nonparametric | - |
dc.subject.keywordAuthor | one-class classification algorithm | - |
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